Factors Influencing Operating Speeds

and Safety on Rural and Suburban Roads

PUBLICATION NO. FHWA-HRT-15-030 MAY 2015

Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296
FOREWORD

The overall goal of the Federal Highway Administration’s Speed Management Program is to 

improve the safety of the Nation’s highways through the reduction of speeding and speed-related 

crashes. Drivers who exceed the speed limit or drive too fast for the conditions are involved in 

nearly one-third of all fatal crashes. Each year, more than 13,000 people are killed in speedingrelated crashes. The majority of speeding-related crashes occur on roads that are not part of the 

interstate system. Local streets and collectors have the highest speeding-related fatality rate on a 

per vehicle miles driven basis. The challenge facing the safety professional is to design roadways 

so that drivers better understand the nature of the roadway and adjust their speed appropriately. 

Design guidance is needed so that roadways are designed and/or retrofitted to induce drivers to 

drive at more appropriate speeds.

This report documents the component factors affecting speed and safety on rural and suburban 

roadways that are not limited access. The report also describes the treatments that have the 

potential to reduce speed-related crashes.

Monique Evans 

Director, Office of Safety 

Research and Development 

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for the use 

of the information contained in this document. This report does not constitute a standard, 

specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trademarks or 

manufacturers’ names appear in this report only because they are considered essential to the 

objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public understanding. Standards 

and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its 

information. FHWA periodically reviews quality issues and adjusts its programs and processes to 

ensure continuous quality improvement.
TECHNICAL REPORT DOCUMENTATION PAGE

1. Report No.

FHWA-HRT-15-030

2. Government Accession No. 3. Recipient’s Catalog No.

4. Title and Subtitle

Factors Influencing Operating Speeds and Safety on Rural and Suburban Roads

5. Report Date

May 2015

6. Performing Organization Code

N/A

7. Author(s)

Leverson Boodlal, P.E; Eric T. Donnell, Ph.D., P.E; Richard J. Porter, Ph.D., P.E; 

Dileep Garimella; Thanh Le; Kevin Croshaw; Scott Himes, Ph.D.; Philip Kulis; 

Jonathan Wood

8. Performing Organization Report 

No.

N/A

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

N/A

KLS Engineering, 

LLC

45155 Research Pl, 

Suite 200 

Ashburn, VA 20147

Thomas D. Larson Pennsylvania 

Transportation Institute

The Pennsylvania State University

201 Transportation Research Bldg

University Park, PA 16802

University of Utah

201 Presidents Circle

Room 201 

Salt Lake City, UT 

84112

11. Contract or Grant No.

DFTH61-10-C-00057

12. Sponsoring Agency Name and Address

Federal Highway Administration

Turner-Fairbank Highway Research Center

Office of Safety Research and Development

6300 Georgetown Pike, Room T-303, McLean, VA 22101

13. Type of Report and Period 

Covered

Final Report: September 2010–July 

2014

14. Sponsoring Agency Code

15. Supplementary Notes

FHWA COTR: Clayton Chen and Abdul Zineddin, Office of Safety Research and Development

16. Abstract

The objective of this project was to develop a technical report that describes treatments that result in driver self-selection of 

appropriate operational speeds on curve and tangent sections. The study was conducted in two phases. The first phase included a 

review of literature on design features and current practices associated with safer operating speeds and identification of 

treatments for field evaluations. The second phase involved evaluating treatments to determine their effectiveness in reducing 

speeds on two-lane horizontal curves in rural and suburban areas. High-friction surface treatment was evaluated at four 

treatment sites and three control sites in West Virginia. The speed and encroachment analyses found no consistent differences 

between the before and after time periods. The friction analysis, however, clearly demonstrated that the friction supply 

increased. Optical speed bars (OSB) were implemented and evaluated at seven sites in Massachusetts, four sites in Arizona, and 

eight sites in Alabama. Two different designs were tested as part of this research, and the results yielded inconsistent speed 

reductions at all the test sites. Based on the results, it can be concluded that the OSB designs used in this research were 

unsuccessful in reducing vehicle speeds. The safety effects of lane-width–shoulder-width combinations on rural two-lane, twoway road segments in Minnesota and Illinois were also estimated as part of this study. Parameters for lane width indicators 

showed that, with shoulder width ignored, the expected number of total (i.e., all types and severities) crashes increases as lane 

width decreases, but it is difficult to distinguish the performance of an 11-ft lane width from that of a 12-ft lane width. The main 

effect of shoulder width was a decrease in the expected number of crashes as shoulder width increased. In addition, the 

interaction of the lane width indicator and shoulder width showed that shoulder width has the greatest effect on safety when the 

lane width equals 10 ft. Shoulder width also has a greater effect on safety when the lane width is 11 ft than when the lane width 

is 12 ft.

17. Key Words

Horizontal curves, speeding related crashes, high friction 

surface treatment, optical speed bars, lane-width–shoulderwidth combinations

18. Distribution Statement

No restrictions. This document is available to the public 

through NTIS: National Technical Information Service,

Springfield, VA 22161.

http://www.ntis.gov

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

376

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
ii
TABLE OF CONTENTS

CHAPTER 1. INTRODUCTION................................................................................................ 1

SCOPE OF RESEARCH AND REPORT ORGANIZATION............................................. 2

CHAPTER 2. BACKGROUND AND LITERATURE REVIEW............................................ 3

DEFINING RURAL AND SUBURBAN ROADWAYS........................................................ 3

SPEED CONCEPTS................................................................................................................. 6

Relationship Among Design, Running, Operating, and Posted Speeds.................................. 6

Design Speed .......................................................................................................................... 6

Other Design Criteria .............................................................................................................. 9

Speeding-Related Outcomes of U.S. Design Practice .......................................................... 14

Relationship Between Speed and Safety............................................................................... 16

Geometric Design Features................................................................................................... 18

Engineering Treatments for Reducing Speeds...................................................................... 25

CHAPTER 3. GENERAL METHODOLOGIES AND SCOPE ............................................ 27

CRASH ANALYSIS FINDINGS SUMMARY .................................................................... 29

CHAPTER 4. OPERATIONAL EFFECTS OF HIGH-FRICTION SURFACE 

TREATMENT ON RURAL, TWO-LANE CURVES....................................................... 31

OVERVIEW............................................................................................................................ 31

SITE SELECTION................................................................................................................. 31

SITE CHARACTERISTICS ................................................................................................. 31

INSTALLATION.................................................................................................................... 32

OPERATING SPEED EVALUATION METHODOLOGY .............................................. 32

Data-Collection Equipment and Locations........................................................................... 33

Sample Size Determination................................................................................................... 35

Data-Collection Periods and Durations ................................................................................ 37

Statistical Analysis................................................................................................................ 37

HFST ENCROACHMENT EVALUATION METHODOLOGY ..................................... 41

Data-Collection Locations and Periods................................................................................. 41

Analysis Methods.................................................................................................................. 41

FRICTION EVALUATION METHODOLOGY ................................................................ 42

Data-Collection Protocol ...................................................................................................... 43

Analysis................................................................................................................................. 44

BEFORE-PERIOD DATA SUMMARY .............................................................................. 46

West Virginia Route 32 Treatment Site (T1 in Table 6)....................................................... 46

West Virginia Route 32 Comparison Site (C1 in Table 6) ................................................... 50

U.S. Route 33 Treatment Site (T2 in Table 6)...................................................................... 53

U.S. Route 33 Comparison Site (C2 in Table 6)................................................................... 56

U.S. Route 219 Treatment Site A—Mile Marker 6.32 (T3 in Table 6)................................ 59

U.S. Route 219 Treatment Site B―Mile Marker 5.81 (T4 in Table 6)................................ 63

U.S. Route 219 Comparison Site (C3/C4 in Table 6)........................................................... 67

COMPARISON OF BEFORE AND AFTER PERIOD DATA.......................................... 70

Mean Operating Speed Results............................................................................................. 70

Mean Operating Speed Summary ......................................................................................... 80

Change in Mean Operating Speed ........................................................................................ 80

iii
Vehicles Exceeding Posted Speed Limit .............................................................................. 83

Speed Variance Analysis ...................................................................................................... 86

Encroachment Data ............................................................................................................... 89

Friction Data ......................................................................................................................... 92

SUMMARY OF HFST EVALUATION FINDINGS ........................................................ 100

5. SPEED EFFECTS OF OPTICAL SPEED BARS ON RURAL AND SUBURBAN 

ROADS................................................................................................................................. 101

OVERVIEW.......................................................................................................................... 101

SITE SELECTION............................................................................................................... 102

TREATMENT DESIGN ...................................................................................................... 102

Design for Massachusetts and Arizona Sites...................................................................... 102

Design for Alabama Sites ................................................................................................... 103

SITE CHARACTERISTICS ............................................................................................... 105

INSTALLATION.................................................................................................................. 107

OPERATING SPEED EVALUATION METHODOLOGY ............................................ 107

Data-Collection Procedures ................................................................................................ 107

Performance Measures and Analysis Methods................................................................... 109

BEFORE PERIOD DATA SUMMARY............................................................................. 109

Arizona................................................................................................................................ 109

Alabama .............................................................................................................................. 121

Massachusetts ..................................................................................................................... 145

COMPARISON OF BEFORE AND AFTER PERIOD SPEED DATA.......................... 166

Mean Operating Speeds...................................................................................................... 167

Arizona................................................................................................................................ 167

Alabama .............................................................................................................................. 177

Massachusetts ..................................................................................................................... 200

Speed Difference Analysis.................................................................................................. 214

Analysis of Variance for Speed Differences....................................................................... 220

Vehicles Exceeding the Posted Speed Limit....................................................................... 223

Speed Variance Analysis .................................................................................................... 227

SUMMARY ........................................................................................................................... 231

6. SAFETY EFFECTS OF LANE-WIDTH–SHOULDER-WIDTH COMBINATIONS 

ON RURAL, TWO-LANE ROADS .................................................................................. 233

OVERVIEW.......................................................................................................................... 233

DATA COLLECTION......................................................................................................... 235

DATA COLLECTION SOURCES, TOOLS, AND STRATEGIES ................................ 236

Database Verification and Enrichment ............................................................................... 237

Geometric Features............................................................................................................. 237

Segment Location ............................................................................................................... 238

Segment Definition ............................................................................................................. 245

Cross-Section Features........................................................................................................ 245

Horizontal Alignment ......................................................................................................... 249

Other Features..................................................................................................................... 252

TRAFFIC DATA .................................................................................................................. 253

CRASH DATA ...................................................................................................................... 254

SAFETY DATA ANALYSIS METHODOLOGIES ......................................................... 256

iv
Analysis of Expected Crash Frequency .............................................................................. 256

Analysis of Crash Severity.................................................................................................. 258

MODEL ESTIMATION RESULTS AND DISCUSSION................................................ 258

7. SUMMARY, CONCLUSIONS, AND CONSIDERATIONS............................................ 265

HIGH FRICTION SURFACE TREATMENT EVALUATION FINDINGS ................. 265

HFST Conclusions.............................................................................................................. 267

HFST Considerations for Future Research ......................................................................... 267

OPTICAL SPEED BAR EVALUATION FINDINGS ...................................................... 267

OSB Conclusions................................................................................................................ 269

OSB Considerations for Future Research ........................................................................... 269

LANE-WIDTH–SHOULDER-WIDTH COMBINATION EVALUATION 

FINDINGS....................................................................................................................... 270

Lane-Width–Shoulder-Width Combination Conclusions................................................... 270

Lane-Width–Shoulder-Width Combination Considerations for Future Research.............. 270

APPENDIX A. CRASH MODIFICATION FACTORS FOR GEOMETRIC DESIGN 

FEATURES ......................................................................................................................... 273

APPENDIX B. CATALOG OF TRAFFIC ENGINEERING TREATMENTS.................. 275

SPEED TABLE..................................................................................................................... 276

Description.......................................................................................................................... 276

Design Details..................................................................................................................... 276

Safety Effectiveness............................................................................................................ 276

Speed Reduction Effectiveness........................................................................................... 276

Cost ..................................................................................................................................... 276

LATERAL SHIFT................................................................................................................ 277

Description.......................................................................................................................... 277

Design Details..................................................................................................................... 277

Safety Effectiveness............................................................................................................ 277

Speed Reduction Effectiveness........................................................................................... 277

Cost ..................................................................................................................................... 277

SPEED KIDNEY................................................................................................................... 278

Description.......................................................................................................................... 278

Design Details..................................................................................................................... 278

Safety Effectiveness............................................................................................................ 278

Speed Reduction Effectiveness........................................................................................... 278

Cost ..................................................................................................................................... 278

TUBULAR CHANNELIZERS............................................................................................ 279

Description.......................................................................................................................... 279

Design Details..................................................................................................................... 279

Safety Effectiveness............................................................................................................ 279

Speed Reduction Effectiveness........................................................................................... 279

Cost ..................................................................................................................................... 279

TRANSVERSE RUMBLE STRIPS.................................................................................... 280

Description.......................................................................................................................... 280

Design Details..................................................................................................................... 280

Safety Effectiveness............................................................................................................ 280

v
Effectiveness to Reduce Speed ........................................................................................... 280

Cost ..................................................................................................................................... 280

LONGITUDINAL RUMBLE STRIPS ............................................................................... 281

Description.......................................................................................................................... 281

Design Details..................................................................................................................... 281

Safety Effectiveness............................................................................................................ 281

Speed Reduction Effectiveness........................................................................................... 281

Cost ..................................................................................................................................... 281

CONVERGING CHEVRON MARKING PATTERN...................................................... 282

Description.......................................................................................................................... 282

Design Details..................................................................................................................... 282

Safety Effectiveness............................................................................................................ 283

Speed Reduction Effectiveness........................................................................................... 283

Cost ..................................................................................................................................... 283

TRANSVERSE MARKINGS .............................................................................................. 284

Description.......................................................................................................................... 284

Design Details..................................................................................................................... 284

Safety Effectiveness............................................................................................................ 284

Speed Reduction Effectiveness........................................................................................... 284

Cost ..................................................................................................................................... 285

OPTICAL SPEED BARS..................................................................................................... 286

Description.......................................................................................................................... 286

Design Details..................................................................................................................... 286

Safety Effectiveness............................................................................................................ 287

Speed Reduction Effectiveness........................................................................................... 287

Cost ..................................................................................................................................... 288

SPEED LIMIT PAVEMENT LEGEND............................................................................. 289

Description.......................................................................................................................... 289

Design Details..................................................................................................................... 289

Safety Effectiveness............................................................................................................ 289

Speed Reduction Effectiveness........................................................................................... 289

Cost ..................................................................................................................................... 289

ENHANCED SPEED LIMIT LEGEND WITH COLORED SURFACING .................. 290

Description.......................................................................................................................... 290

Design Details..................................................................................................................... 290

Safety Effectiveness............................................................................................................ 290

Speed Reduction Effectiveness........................................................................................... 290

Cost ..................................................................................................................................... 290

SLOW PAVEMENT LEGEND........................................................................................... 291

Description.......................................................................................................................... 291

Design Details..................................................................................................................... 291

Safety Effectiveness............................................................................................................ 291

Speed Reduction Effectiveness........................................................................................... 291

Cost ..................................................................................................................................... 291

ZIGZAG PAVEMENT MARKINGS ................................................................................. 292

Description.......................................................................................................................... 292

vi
Design Details..................................................................................................................... 292

Safety Effectiveness............................................................................................................ 292

Speed Reduction Effectiveness........................................................................................... 292

Cost ..................................................................................................................................... 292

PAINTED MEDIANS........................................................................................................... 293

Description.......................................................................................................................... 293

Design Details..................................................................................................................... 293

Safety Effectiveness............................................................................................................ 293

Speed Reduction Effectiveness........................................................................................... 293

Cost ..................................................................................................................................... 293

ADD SHOULDER MARKINGS TO NARROW LANE .................................................. 294

Description.......................................................................................................................... 294

Design Details..................................................................................................................... 294

Safety Effectiveness............................................................................................................ 294

Speed Reduction Effectiveness........................................................................................... 294

Cost ..................................................................................................................................... 294

ADD CENTERLINE AND EDGE LINE............................................................................ 295

Description.......................................................................................................................... 295

Design Details..................................................................................................................... 295

Safety Effectiveness............................................................................................................ 295

Speed Reduction Effectiveness........................................................................................... 295

Cost ..................................................................................................................................... 296

SPEED FEEDBACK SIGN.................................................................................................. 297

Description.......................................................................................................................... 297

Design Details..................................................................................................................... 297

Safety Effectiveness............................................................................................................ 297

Speed Reduction Effectiveness........................................................................................... 297

Cost ..................................................................................................................................... 297

SPEED-ACTIVATED WARNING SIGN .......................................................................... 298

Description.......................................................................................................................... 298

Design Details..................................................................................................................... 298

Safety Effectiveness............................................................................................................ 298

Speed Reduction Effectiveness........................................................................................... 298

Cost ..................................................................................................................................... 298

SPEED-ACTIVATED SPEED LIMIT REMINDER SIGN ............................................. 299

Description.......................................................................................................................... 299

Design Details..................................................................................................................... 299

Safety Effectiveness............................................................................................................ 299

Speed Reduction Effectiveness........................................................................................... 299

Cost ..................................................................................................................................... 299

VARIABLE SPEED LIMIT SIGN ..................................................................................... 300

Description.......................................................................................................................... 300

Design Details..................................................................................................................... 300

Safety Effectiveness............................................................................................................ 300

Speed Reduction Effectiveness........................................................................................... 300

Cost ..................................................................................................................................... 301

vii
TRANSVERSE PAVEMENT MARKINGS WITH SPEED FEEDBACK SIGN.......... 302

Description.......................................................................................................................... 302

Design Details..................................................................................................................... 302

Safety Effectiveness............................................................................................................ 302

Speed Reduction Effectiveness........................................................................................... 302

Cost ..................................................................................................................................... 302

ADVISORY SPEED LIMIT SIGN ..................................................................................... 303

Description.......................................................................................................................... 303

Design Details..................................................................................................................... 303

Safety Effectiveness............................................................................................................ 303

Speed Reduction Effectiveness........................................................................................... 303

Cost ..................................................................................................................................... 303

RED BORDER SPEED LIMIT SIGN................................................................................ 304

Description.......................................................................................................................... 304

Design Details..................................................................................................................... 304

Safety Effectiveness............................................................................................................ 304

Speed Reduction Effectiveness........................................................................................... 304

Cost ..................................................................................................................................... 304

ONE-DIRECTION LARGE ARROW (W1-6) SIGN........................................................ 305

Description.......................................................................................................................... 305

Design Details..................................................................................................................... 305

Safety Effectiveness............................................................................................................ 305

Speed Reduction Effectiveness........................................................................................... 305

Cost ..................................................................................................................................... 305

ADD FLASHERS TO EXISTING CURVE WARNING SIGN ....................................... 306

Description.......................................................................................................................... 306

Design Details..................................................................................................................... 306

Safety Effectiveness............................................................................................................ 306

Speed Reduction Effectiveness........................................................................................... 306

Cost ..................................................................................................................................... 306

ADD FLAGS TO EXISTING CURVE WARNING SIGN............................................... 307

Description.......................................................................................................................... 307

Design Details..................................................................................................................... 307

Safety Effectiveness............................................................................................................ 307

Speed Reduction Effectiveness........................................................................................... 307

Cost ..................................................................................................................................... 307

COMBINATION HORIZONTAL ALIGNMENT/ADVISORY SIGN........................... 308

Description.......................................................................................................................... 308

Design Details..................................................................................................................... 308

Safety Effectiveness............................................................................................................ 308

Speed Reduction Effectiveness:.......................................................................................... 308

Cost ..................................................................................................................................... 309

CHEVRON SIGN ................................................................................................................. 310

Description.......................................................................................................................... 310

Design Details..................................................................................................................... 310

Safety Effectiveness............................................................................................................ 310

viii
Speed Reduction Effectiveness........................................................................................... 310

Cost ..................................................................................................................................... 311

CURVE WARNING SIGN AND CHEVRON SIGN AND FLASHING BEACONS .... 312

Description.......................................................................................................................... 312

Design Details..................................................................................................................... 312

Safety Effectiveness............................................................................................................ 312

Speed Reduction Effectiveness........................................................................................... 312

Cost ..................................................................................................................................... 312

CURVE WARNING SIGN AND CHEVRON SIGN ........................................................ 313

Description.......................................................................................................................... 313

Design Details..................................................................................................................... 313

Safety Effectiveness............................................................................................................ 313

Speed Reduction Effectiveness........................................................................................... 313

Cost ..................................................................................................................................... 313

DELINEATOR POST.......................................................................................................... 314

Description.......................................................................................................................... 314

Design Details..................................................................................................................... 314

Safety Effectiveness............................................................................................................ 314

Speed Reduction Effectiveness........................................................................................... 314

Cost ..................................................................................................................................... 315

MEDIAN BARRIERS .......................................................................................................... 316

Description.......................................................................................................................... 316

Design Details..................................................................................................................... 316

Safety Effectiveness............................................................................................................ 316

Speed Reduction Effectiveness........................................................................................... 316

Cost ..................................................................................................................................... 316

ROADSIDE BARRIERS...................................................................................................... 317

Description.......................................................................................................................... 317

Design Details..................................................................................................................... 317

Safety Effectiveness............................................................................................................ 317

Speed Reduction Effectiveness........................................................................................... 317

Cost ..................................................................................................................................... 317

LANE WIDENING............................................................................................................... 318

Description.......................................................................................................................... 318

Design Details..................................................................................................................... 318

Safety Effectiveness............................................................................................................ 318

Speed Reduction Effectiveness........................................................................................... 318

Cost ..................................................................................................................................... 318

TWO-WAY LEFT-TURN LANE ....................................................................................... 319

Description.......................................................................................................................... 319

Design Details..................................................................................................................... 319

Safety Effectiveness............................................................................................................ 319

Speed Reduction Effectiveness........................................................................................... 319

Cost ..................................................................................................................................... 319

ADDITIONAL LANE (OR ROAD DUPLICATION) ...................................................... 320

Description.......................................................................................................................... 320

ix
Design Details..................................................................................................................... 320

Safety Effectiveness............................................................................................................ 320

Speed Reduction Effectiveness........................................................................................... 320

Cost ..................................................................................................................................... 320

PAVING SHOULDERS....................................................................................................... 321

Description.......................................................................................................................... 321

Design Details..................................................................................................................... 321

Safety Effectiveness............................................................................................................ 321

Speed Reduction Effectiveness........................................................................................... 321

Cost ..................................................................................................................................... 321

ROAD SURFACE UPGRADES.......................................................................................... 322

Description.......................................................................................................................... 322

Design Details..................................................................................................................... 322

Safety Effectiveness............................................................................................................ 322

Speed Reduction Effectiveness........................................................................................... 322

Cost ..................................................................................................................................... 322

GATEWAY TREATMENT................................................................................................. 323

Description.......................................................................................................................... 323

Design Details..................................................................................................................... 323

Safety Effectiveness............................................................................................................ 323

Speed Reduction Effectiveness........................................................................................... 323

Cost ..................................................................................................................................... 323

APPENDIX C. SAFETY EFFECTS OF LANE-WIDTH AND SHOULDER-WIDTH 

COMBINATIONS ON RURAL, TWO-LANE ROADS (ADDITIONAL 

MODELING RESULTS) ................................................................................................... 325

ACKNOWLEDGMENTS........................................................................................................ 339

REFERENCES.......................................................................................................................... 341

BIBLIOGRAPHY..................................................................................................................... 353

x
LIST OF FIGURES

Figure 1. Graph. Approximate relationships between design and running speeds for urban 

conditions (figure 1 from Porter et al., 2012) ........................................................................... 8

Figure 2. Graph. Comparison of maximum side friction factor used for design to available 

side friction (figure 2 from Porter et al., 2012)....................................................................... 10

Figure 3. Graph. Comparison of minimum curve radius used for design to minimum curve 

radii (figure 3 from Porter et al., 2012)................................................................................... 10

Figure 4. Graph. Maximum side friction factor assumed for design (figure 3-6 from 

AASHTO 2011)...................................................................................................................... 12

Figure 5. Equation. Minimum radius of horizontal curvature ...................................................... 12

Figure 6. Equation. Required side friction factor ......................................................................... 13

Figure 7. Chart. Observed speed-related outcomes of the typical U.S. design practice 

(figure 2a from Donnell et al., 2009)...................................................................................... 15

Figure 8. Graph. Observed relationships between design speed and operating speeds 

(figure 5 from Porter et al., 2012)........................................................................................... 15

Figure 9. Diagram. Conceptual speed-related outcomes of U.S. road design practice (adapted 

from figure 1 in Tarris et al., 2000) ........................................................................................ 16

Figure 10. Graph. Relationship between change in travel speed during a crash and the 

probability of fatality (plotted model estimated by Joksch) ................................................... 18

Figure 11. Graph. CMFs for combinations of lane and shoulder widths for two-lane rural 

highways (Average Annual Daily Traffic > 2,000 vehicles/day)........................................... 21

Figure 12. Graph. CMFs for combinations of lane and shoulder widths for two-lane rural 

highways (figure 1 in Gross et al., 2009)................................................................................ 22

Figure 13. Graph. Relationships among horizontal curve radius, speed, and safety for 

two-lane rural highways.......................................................................................................... 23

Figure 14. Graph. Relationship between lane width and speed and safety for two-lane rural 

highways. ................................................................................................................................ 24

Figure 15. Graph. Relationship between shoulder width and speed and safety for rural, 

two-lane highways.................................................................................................................. 25

Figure 16. Photo. Photograph of a horizontal curve without the HFST ....................................... 33

Figure 17. Photo. Photograph of a horizontal curve with the HFST ............................................ 33

Figure 18. Diagram. Location of traffic sensors for treatment and control sites (not to scale) ... 35

Figure 19. Equation. Minimum number of measured speeds....................................................... 35

Figure 20. Equation. Sum of the sample in before-after comparison groups............................... 36

Figure 21. Equation. t-statistic to test for the difference between two sample means at each 

study site ................................................................................................................................. 38

Figure 22. Equation. Percentage of speeding vehicles ................................................................. 39

Figure 23. Equation. Percent reduction of speeding vehicles....................................................... 39

Figure 24. Equation. Z-statistic to determine the speed difference between a pair of before 

and after periods...................................................................................................................... 40

xi
Figure 25. Equation. Combined proportion of vehicles speeding during the before and after 

data-collection periods............................................................................................................ 40

Figure 26. Equation. F-test to compare the speed variance in the before and after periods. ........ 40

Figure 27. Equation Proportion of vehicles encroaching on the edge line or centerline. ............. 41

Figure 28. Equation. Z-statistic to determine the proportion of vehicles encroaching on a 

lane line during the before and after data-collection periods.................................................. 42

Figure 29. Equation. Combined proportion of vehicles encroaching on a lane line between 

the before and after data-collection periods............................................................................ 42

Figure 30. Photo. Dynamic friction tester..................................................................................... 43

Figure 31. Graph. Road friction curves (for illustrative purposes only)....................................... 45

Figure 32. Equation. Side friction demand ................................................................................... 45

Figure 33. Diagram. Geometric layout of WV Route 32 treatment site (not to scale). ................ 47

Figure 34. Graph. Graphical representation of speeds at the WV Route 32 treatment site.......... 49

Figure 35. Diagram. Geometric layout of the WV Route 32 comparison site (not to scale)........ 51

Figure 36. Graph. Graphical representation of speeds at the WV Route 32 comparison site ...... 52

Figure 37. Diagram. Geometric layout of the U.S. Route 33 treatment site (not to scale)........... 54

Figure 38. Graph. Graphical representation of speeds at the U.S. Route 33 treatment site.......... 55

Figure 39. Diagram. Geometric layout of the U.S. Route 33 comparison site (not to scale) ....... 57

Figure 40. Graph. Graphical representation of speeds at the U.S. Route 33 comparison site...... 58

Figure 41. Diagram. Geometric layout of the U.S. Route 219 treatment A site (not to scale)..... 60

Figure 42. Graph. Graphical representation of speeds at the U.S. Route 219 treatment A site.... 62

Figure 43. Diagram. Geometric layout of the U.S. Route 219 treatment B site (not to scale). .... 64

Figure 44. Graph. Graphical representation of speeds at the U.S. Route 219 treatment B site.... 66

Figure 45. Diagram. Geometric layout of the U.S. Route 219 comparison site (not to scale) ..... 67

Figure 46. Graph. Graphical representation of speeds at the U.S. Route 219 comparison site.... 69

Figure 47. Graph. WV Route 32 treatment site operating speeds (PSL = 55 mph)...................... 72

Figure 48. Graph. WV Route 32 comparison site operating speeds (PSL = 55 mph).................. 72

Figure 49. Graph. U.S. Route 33 treatment site operating speeds (PSL = 55 mph). .................... 75

Figure 50. Graph. U.S. Route 33 comparison site operating speeds (PSL = 55 mph) ................. 75

Figure 51. Graph. U.S. Route 219 treatment site A (MM 6.32) operating speeds 

(PSL = 55 mph)....................................................................................................................... 79

Figure 52. Graph. U.S. Route 219 treatment site B (MM 5.81) operating speeds 

(PSL=55 mph)......................................................................................................................... 79

Figure 53. Graph. U.S. Route 219 comparison site operating speeds (PSL = 55 mph) ............... 80

Figure 54. Graph. Side friction supply before and after for WV Route 32 sites. ......................... 96

Figure 55. Graph. Side friction supply before and after for U.S. Route 33 sites.......................... 97

Figure 56. Graph. Side friction supply before and after for U.S. Route 219 sites........................ 97

Figure 57. Equation. Side friction demand ................................................................................... 98

Figure 58. Photo. OSB example ................................................................................................. 101

xii
Figure 59. Equation. Length of OSB treatment .......................................................................... 104

Figure 60. Equation. Individual placement of the OSBs............................................................ 104

Figure 61. Diagram. OSB data-collection setup (not to scale) ................................................... 108

Figure 62. Diagram. Geometric layout of northbound Pierce Ferry Road (not to scale) ........... 111

Figure 63. Graph. Graphical representation of speeds on northbound Pierce Ferry Road. ........ 113

Figure 64. Diagram. Geometric layout of southbound Shinarump Road (not to scale) ............. 113

Figure 65. Graph. Graphical representation of speeds on southbound Shinarump Road........... 115

Figure 66. Diagram. Geometric layout of southbound Diamond Bar Road in the before 

period (not to scale) .............................................................................................................. 116

Figure 67. Diagram. Geometric layout of southbound Diamond Bar Road in the after 

periods (not to scale)............................................................................................................. 116

Figure 68. Graph. Graphical representation of speeds on southbound Diamond Bar Road....... 118

Figure 69. Diagram. Geometric layout of southbound County Route 1 (not to scale)............... 119

Figure 70. Graph. Graphical representation of speeds on southbound County Route 1............. 121

Figure 71. Diagram. Geometric layout of Alabama Location #1 (not to scale) ......................... 122

Figure 72. Graph. Graphical representation of speeds at Alabama Location #1 ........................ 124

Figure 73. Diagram. Geometric layout of Alabama Location #2 (not to scale) ......................... 125

Figure 74. Graph. Graphical representation of speeds at Alabama Location #2 ........................ 127

Figure 75. Diagram. Geometric layout of Alabama Location #3 (not to scale) ......................... 128

Figure 76. Graph. Graphical representation of speeds at Alabama Location #3 ........................ 130

Figure 77. Diagram. Geometric layout of Alabama Location #4 (not to scale) ......................... 131

Figure 78. Graph. Graphical representation of speeds at Alabama Location #4 ........................ 133

Figure 79. Diagram. Geometric layout of Alabama Location #5 (not to scale) ......................... 134

Figure 80. Graph. Graphical representation of speeds at Alabama Location #5. ....................... 136

Figure 81. Diagram. Geometric layout of Alabama Location #6 (not to scale) ......................... 137

Figure 82. Graph. Graphical representation of speeds at Alabama Location #6 ........................ 139

Figure 83. Diagram. Geometric layout of Alabama Location #7 (not to scale) ......................... 140

Figure 84. Graph. Graphical representation of speeds at Alabama Location #7. ....................... 142

Figure 85. Diagram. Geometric layout of Alabama Location #8 (not to scale). ........................ 143

Figure 86. Graph. Graphical representation of speeds at Alabama Location #8. ....................... 145

Figure 87. Diagram. Geometric layout of southbound Tucker Road (not to scale).................... 146

Figure 88. Graph. Graphical representation of speeds on southbound Tucker Road. ................ 148

Figure 89. Diagram. Geometric layout of northbound Tucker Road (not to scale).................... 149

Figure 90. Graph. Graphical representation of speeds on northbound Tucker Road ................. 151

Figure 91. Diagram. Geometric layout of southbound Reed Road (not to scale)....................... 152

Figure 92. Graph. Graphical representation of speeds on southbound Reed Road .................... 154

Figure 93. Diagram. Geometric layout of southbound New Boston Road (not to scale)........... 155

Figure 94. Graph. Graphical representation of speeds on southbound New Boston Road......... 157

Figure 95. Diagram. Geometric layout of northbound New Boston Road (not to scale). .......... 158

xiii
Figure 96. Graph. Graphical representation of speeds on northbound New Boston Road......... 160

Figure 97. Diagram. Geometric layout of southbound Braley Hill Road (not to scale)............. 161

Figure 98. Graph. Graphical representation of speeds on southbound Braley Hill Road........... 163

Figure 99. Diagram. Geometric layout of northbound Braley Hill Road (not to scale) ............. 164

Figure 100. Graph. Graphical representation of speeds on northbound Braley Hill Road......... 166

Figure 101. Graph. Operating speeds comparison on northbound Pierce Ferry Road 

(PSL = 55 mph)..................................................................................................................... 169

Figure 102. Graph. Operating speeds comparison on southbound Shinarump Road 

(PSL = 45 mph)..................................................................................................................... 172

Figure 103. Graph. Operating speeds comparison on southbound Diamond Bar Road 

(PSL = 45 mph)..................................................................................................................... 174

Figure 104. Graph. Operating speeds comparison on southbound County Route 1 

(PSL = 35 mph)..................................................................................................................... 177

Figure 105. Graph. Operating speeds comparison at Alabama Location #1 (PSL = 55 mph) ... 180

Figure 106. Graph. Operating speeds comparison at Alabama Location #2 (PSL = 55 mph) ... 183

Figure 107. Graph. Operating speeds comparison at Alabama Location #3 (PSL = 55 mph) ... 185

Figure 108. Graph. Operating speeds comparison at Alabama Location #4 (PSL = 35 mph) ... 189

Figure 109. Graph. Operating speeds comparison at Alabama Location #5 (PSL = 40 mph) ... 192

Figure 110. Graph. Operating speeds comparison at Alabama Location #6 (PSL = 40 mph) ... 194

Figure 111. Graph. Operating speeds comparison at Alabama Location #7 (PSL = 35 mph) ... 197

Figure 112. Graph. Operating speeds comparison at Alabama Location #8 (PSL = 35 mph) ... 199

Figure 113. Graph. Operating speeds comparison at southbound Tucker Road 

(PSL = 30 mph)..................................................................................................................... 202

Figure 114. Graph. Operating speeds comparison at northbound Tucker Road 

(PSL = 35 mph)..................................................................................................................... 204

Figure 115. Graph. Operating speeds comparison at southbound Reed Road 

(PSL = 25 mph)..................................................................................................................... 206

Figure 116. Graph. Operating speeds comparison on southbound New Boston Road 

(PSL = 35 mph)..................................................................................................................... 208

Figure 117. Graph. Operating speeds comparison on northbound New Boston Road 

(PSL = 35 mph)..................................................................................................................... 210

Figure 118. Graph. Operating speeds comparison at southbound Braley Hill Road 

(PSL = 30 mph)..................................................................................................................... 212

Figure 119. Graph. Operating speeds comparison at northbound Braley Hill Road 

(PSL = 40 mph)..................................................................................................................... 214

Figure 120. Chart. Location information in Minnesota’s HSIS Roadway File. ......................... 239

Figure 121. Chart. Location information of the roadway segment in GIS File (Minnesota) ..... 239

Figure 122. Photo. Locate and mark the point of interest in Google EarthTM using its 

coordinates (Minnesota)........................................................................................................ 240

Figure 123. Chart. Location information in Illinois HSIS Roadway data file............................ 241

xiv
Figure 124. Equation. Reference point milepost ........................................................................ 241

Figure 125. Equation. Reference point milepost by reversing the direction of increasing 

station.................................................................................................................................... 242

Figure 126. Chart. Location information of the roadway segment in GIS file (Illinois)............ 243

Figure 127. Chart. Identify coordinate information associated with the roadway segment 

(Illinois)................................................................................................................................. 244

Figure 128. Photo. Locate and mark the roadway segment in Google EarthTM with its coordinates

............................................................................................................................................... 244

Figure 129. Photo. Measurement of cross-section features in Google EarthTM.......................... 246

Figure 130. Photo. Conceptual illustration of calculating lane................................................... 246

Figure 131. Photo. Visual checks of cross-section features in Google Street ViewTM............... 247

Figure 132. Photo. Screenshot of estimating deflection angles in Google EarthTM ................... 250

Figure 133. Equation. Smallest distance between PI and all points along the curve.................. 250

Figure 134. Equation. Curve radius............................................................................................ 251

Figure 135. Equation. Length of the curve ................................................................................. 251

Figure 136. Equation. Expected number of crashes of type i on segment j................................ 256

Figure 137. Equation. Variance of crashes of type i on segment j ............................................. 257

Figure 138. Equation. Probability of accident n with severity i ................................................. 258

Figure 139. Graph. CMFs for lane-width–shoulder-width combinations developed directly 

from regression model parameters, total crashes (all types and severities) on rural, 

two-lane roads (developed from model estimation results in table 104).............................. 261

Figure 140. Graph. CMFs for lane-width–shoulder-width combinations developed directly 

from regression model parameters, fatal-plus-injury crashes (all types) on rural, 

two-lane roads (developed from model estimation results in table 105).............................. 262

Figure 141. Photo. Speed table ................................................................................................... 276

Figure 142. Photo. Lateral shift .................................................................................................. 277

Figure 143. Photo. Speed kidney ................................................................................................ 278

Figure 144. Photo. Tubular channelizers.................................................................................... 279

Figure 145. Photo. Transverse rumble strips.............................................................................. 280

Figure 146. Photo. Longitudinal rumble strips........................................................................... 281

Figure 147. Photo. Converging chevron marking pattern........................................................... 282

Figure 148. Equation. Decreasing velocity linear equation........................................................ 282

Figure 149. Photo. Transverse markings .................................................................................... 284

Figure 150. Photo. Optical speed bars........................................................................................ 286

Figure 151. Illustration. Peripheral Design (2009 MUTCD, Part 3B. 22).................................. 286

Figure 152. Illustration. Peripheral Design Variation, Mohave County, AZ ............................. 287

Figure 153. Photo. OSB Variation, Iowa State University......................................................... 287

Figure 154. Photo. Speed limit pavement legend ....................................................................... 289

Figure 155. Photo. Enhanced speed limit legend with colored surfacing................................... 290

Figure 156. Photo. Slow pavement legend ................................................................................. 291

xv
Figure 157. Photo. Zigzag pavement markings.......................................................................... 292

Figure 158. Photo. Painted medians ........................................................................................... 293

Figure 159. Photo. Add shoulder markings to narrow lane ........................................................ 294

Figure 160. Photo. Add centerline and edge line........................................................................ 295

Figure 161. Photo. Speed feedback sign..................................................................................... 297

Figure 162. Photo. Speed-activated warning sign ...................................................................... 298

Figure 163. Photo. Speed-activated speed limit reminder sign .................................................. 299

Figure 164. Photo. Variable speed limit sign.............................................................................. 300

Figure 165. Photo. Transverse pavement markings with speed feedback sign .......................... 302

Figure 166. Photo. Advisory speed limit sign............................................................................. 303

Figure 167. Photo. Red border speed limit sign.......................................................................... 304

Figure 168. Photo. One-direction large arrow (W1-6) sign........................................................ 305

Figure 169. Photo. Add flashers to existing curve warning sign ................................................ 306

Figure 170. Photo. Curve warning sign with flags ..................................................................... 307

Figure 171. Photo. Combination horizontal alignment/advisory sign ........................................ 308

Figure 172. Photo. Chevron sign ................................................................................................ 310

Figure 173. Curve warning sign and chevron sign and flashing beacons................................... 312

Figure 174. Photo. Curve warning sign and chevron sign.......................................................... 313

Figure 175. Photo. Delineator post ............................................................................................. 314

Figure 176. Photo. Median barriers ............................................................................................ 316

Figure 177. Photo. Roadside barriers.......................................................................................... 317

Figure 178. Photo. Lane widening.............................................................................................. 318

Figure 179. Photo. Two-way left-turn lane................................................................................. 319

Figure 180. Photo. Additional lane............................................................................................. 320

Figure 181. Photo. Paving shoulder............................................................................................ 321

Figure 182. Photo. Road surface................................................................................................. 322

Figure 183. Photo. Gateway treatment ....................................................................................... 323

xvi
LIST OF TABLES

Table 1. Quantifiable characteristics of land use contexts (PennDOT and NJDOT, 2008) ........... 5

Table 2. Relationship between design speed and average running speed (table 3-6 in 

AASHTO 2011)........................................................................................................................ 8

Table 3. Minimum radii and superelevation for low-speed urban streets (part of 

figure 3-13b from AASHTO 2011) ........................................................................................ 13

Table 4. Results of iterative inferred design speed calculations................................................... 14

Table 5. Statistical associations between vehicle operating speeds and geometric design 

features. (Information gathered from TRB Operational Effects of Geometrics 

Committee, 2011) ................................................................................................................... 19

Table 6. West Virginia HFST site characteristics......................................................................... 32

Table 7. Sample size determination.............................................................................................. 36

Table 8. Sample size estimates for comparative research studies ................................................ 36

Table 9. WV Route 32 treatment site before data......................................................................... 48

Table 10. WV Route 32 treatment site friction data ..................................................................... 49

Table 11. WV Route 32 comparison site before data ................................................................... 52

Table 12. WV Route 32 comparison site friction data.................................................................. 53

Table 13. U.S. Route 33 treatment site before data ...................................................................... 55

Table 14. U.S. Route 33 treatment site friction data..................................................................... 56

Table 15. U.S. Route 33 comparison site before data................................................................... 58

Table 16. U.S. Route 33 comparison site friction data ................................................................. 59

Table 17. U.S. Route 219 treatment A site before data ................................................................ 61

Table 18. U.S. Route 219 treatment A site friction data............................................................... 62

Table 19. U.S. Route 219 treatment B site before data................................................................. 65

Table 20. U.S. Route 219 treatment B site friction data............................................................... 66

Table 21. U.S. Route 219 comparison site before data................................................................. 68

Table 22. U.S. Route 219 comparison site friction data. .............................................................. 69

Table 23. Operating speeds at WV Route 32 sites before and after treatment. ............................ 71

Table 24. Operating speeds at U.S. Route 33 before and after treatment..................................... 74

Table 25. Operating speeds at U.S. Route 219 before and after treatment................................... 78

Table 26. Change in speed from PC to curve midpoint................................................................ 82

Table 27. Number of vehicles exceeding the PSL by site ............................................................ 85

Table 28. Number of vehicles exceeding the advisory speed by site. .......................................... 86

Table 29. Change in standard deviation of speed ......................................................................... 88

Table 30. Number of encroachments and braking vehicles by site .............................................. 91

Table 31. SN65 friction data from the before period.................................................................... 92

Table 32. SN65 friction data from the immediate after period..................................................... 93

Table 33. SN65 friction data from the second after period........................................................... 93

xvii
Table 34. Before and after friction data for comparison............................................................... 94

Table 35. SN65 estimated available side friction before treatment application. .......................... 95

Table 36. SN65 Estimated available side friction first after treatment application...................... 95

Table 37. SN65 estimated available side friction second after treatment application.................. 96

Table 38. Descriptive statistics for passenger cars for margin of safety analysis......................... 99

Table 39. Friction demand and supply comparison.................................................................... 100

Table 40. OSB treatment location site characteristics. ............................................................... 106

Table 41. Northbound Pierce Ferry Road before data ................................................................ 112

Table 42. Southbound Shinarump Road before data .................................................................. 114

Table 43. Southbound Diamond Bar Road before data. ............................................................. 117

Table 44. Southbound County Route 1 before data.................................................................... 120

Table 45. Alabama Location #1 before data............................................................................... 123

Table 46. Alabama Location #2 before data............................................................................... 126

Table 47. Alabama Location #3 before data............................................................................... 129

Table 48. Alabama Location #4 before data............................................................................... 132

Table 49. Alabama Location #5 before data............................................................................... 135

Table 50. Alabama Location #6 before data............................................................................... 138

Table 51. Alabama Location #7 before data............................................................................... 141

Table 52. Alabama Location #8 before data............................................................................... 144

Table 53. Southbound Tucker Road before data ........................................................................ 147

Table 54. Northbound Tucker Road before data ........................................................................ 150

Table 55. Southbound Reed Road before data............................................................................ 153

Table 56. Southbound New Boston Road before data................................................................ 156

Table 57. Northbound New Boston Road before data................................................................ 159

Table 58. Southbound Braley Hill Road before data.................................................................. 162

Table 59. Northbound Braley Hill Road before data.................................................................. 165

Table 60. Before-after operating speeds at northbound Pierce Ferry Road................................ 168

Table 61. Before-after operating speeds at southbound Shinarump Road.................................. 170

Table 62. Before-after operating speeds at southbound Diamond Bar Road ............................. 173

Table 63. Before-after operating speeds at southbound County Route 1. .................................. 175

Table 64. Before-after operating speeds at Alabama Location #1.............................................. 178

Table 65. Before-after operating speeds at Alabama Location #2.............................................. 181

Table 66. Before-after operating speeds at Alabama Location #3.............................................. 184

Table 67. Before-after operating speeds at Alabama Location #4.............................................. 187

Table 68. Before-after operating speeds at Alabama Location #5.............................................. 190

Table 69. Before-after operating speeds at Alabama Location #6.............................................. 193

Table 70. Before-after operating speeds at Alabama Location #7.............................................. 195

Table 71. Before-after operating speeds at Alabama Location #8.............................................. 198

xviii
Table 72. Before-after operating speeds at southbound Tucker Road........................................ 201

Table 73. Before-after operating speeds at northbound Tucker Road. ....................................... 203

Table 74. Before-after operating speeds at southbound Reed Road........................................... 205

Table 75. Before-after operating speeds at southbound New Boston Road ............................... 207

Table 76. Before-after operating speeds at northbound New Boston Road ............................... 209

Table 77. Before-after operating speeds at southbound Braley Hill Road ................................. 211

Table 78. Before-after operating speeds at northbound Braley Hill Road ................................. 213

Table 79. Change in speeds for Arizona sites............................................................................. 215

Table 80. Change in speeds for Alabama sites........................................................................... 217

Table 81. Change in speeds for Massachusetts sites................................................................... 219

Table 82. Speed difference between the control point and the curve midpoint.......................... 220

Table 83. Speed difference between the approach and the PC................................................... 221

Table 84. Speed difference between the control point and the PC. ............................................ 221

Table 85. Speed difference between the control point and the curve midpoint.......................... 221

Table 86. Speed difference between the approach and the PC................................................... 222

Table 87. Speed difference control Point to PC.......................................................................... 222

Table 88. Difference between the control point and the curve midpoint.................................... 222

Table 89. Difference between the approach and the PC............................................................. 222

Table 90. Difference between the control point and the PC....................................................... 222

Table 91. Number of vehicles exceeding the PSL in Arizona.................................................... 224

Table 92. Number of vehicles exceeding the PSL in Alabama .................................................. 225

Table 93. Number of vehicles exceeding the PSL in Massachusetts.......................................... 227

Table 94. Change in standard deviation of speed in Arizona ..................................................... 228

Table 95. Change in standard deviation of speed in Alabama.................................................... 229

Table 96. Change in standard deviation of speed in Massachusetts........................................... 230

Table 97. Number of segments by lane-width and shoulder-width............................................ 248

Table 98. Number of segments with roadside barriers. .............................................................. 248

Table 99. Number of segments by driveway presence ............................................................... 248

Table 100. Alignment indices for quantifying horizontal alignment characteristics (based 

on Fitzpatrick et al., 2000).................................................................................................... 252

Table 101. Number of segments with no-passing zone, one-sided passing zone, and 

shoulder rumble strip ............................................................................................................ 253

Table 102. Descriptive statistics for geometric, traffic control, and traffic variables. ............... 254

Table 103. Descriptive statistics for crash variables................................................................... 256

Table 104. Negative binomial regression model estimation results for total crashes (all 

types and severities).............................................................................................................. 259

Table 105. Negative binomial regression model estimation results for fatal-plus-injury 

crashes (All types)................................................................................................................. 260

Table 106. CMFs for Geometric Design Features...................................................................... 273

xix
Table 107. Negative binomial regression model estimation results for property damage 

only crashes (all severities)................................................................................................... 325

Table 108. Negative binomial regression model estimation results for single-vehicle crashes 

(all severities)........................................................................................................................ 326

Table 109. Negative binomial regression model estimation results for multiple-vehicle 

crashes (all severities)........................................................................................................... 327

Table 110. Negative binomial regression model estimation results for key lane 

width/shoulder width crashes (all severities)........................................................................ 328

Table 111. Negative binomial regression model estimation results for single-vehicle 

crashes (fatal-plus-injury). .................................................................................................... 329

Table 112. Negative binomial regression model estimation results for multiple-vehicle 

crashes (fatal-plus-injury). .................................................................................................... 330

Table 113. Negative binomial regression model estimation results for key lane-width/shoulderwidth crashes (fatal-plus-injury). .......................................................................................... 331

Table 114. Negative binomial regression model estimation results for single-vehicle 

crashes (PDO). ...................................................................................................................... 332

Table 115. Negative binomial regression model estimation results for multiple-vehicle 

crashes (PDO). ...................................................................................................................... 333

Table 116. Negative binomial regression model estimation results for key lane-width/

shoulder-width crashes (PDO).............................................................................................. 334

Table 117. Multinomial logit model estimation results for total crashes (all types and 

severities)—base outcome: PDO. ......................................................................................... 335

Table 118. Multinomial logit model estimation results for fatal-plus-injury crashes (all types)—

base outcome: possible injury............................................................................................... 337

xx
LIST OF ABBREVIATIONS

AASHTO American Association of State Highway and Transportation Officials

ALDOT Alabama Department of Transportation 

ANOVA Analysis of Variance

CMF Crash Modification Factors

CT Circular Texture

DF Dynamic Friction

FHWA Federal Highway Administration 

GIS Geographic Information System

HCM Highway Capacity Manual

HDM Highway Data Management

HFST High Friction Surface Treatment

HSIS Highway Safety Information System

HSM Highway Safety Manual

IFI International Friction Index

KML Keyhole Markup Language

MCPW Mohave County Public Works

MM Mile Marker 

MPD Mean Profile Depth

MPH Miles per Hour

MUTCD Manual on Uniform Traffic Control Devices 

NCHRP National Cooperative Highway Research Program

NHTSA National Highway Traffic Safety Administration

NJDOT New Jersey Department of Transportation

OSB Optical Speed Bars

P.E. Professional Engineer

PC Point of Curvature

PDO Property Damage Only

PennDOT Pennsylvania Department of Transportation 

PI Point of Intersection

PSL Posted Speed Limit

PT Point of Tangent

PTOE Professional Traffic Operations Engineer

RSA Road Safety Audit

SD Standard Deviation

SDF Severity Distribution Function

SN Skid Number

SRPEDD Southeast Regional Planning and Economic Development District 

TRB Transportation Research Board

TWLTL Two-Way Left-Turn Lane

VBA Visual Basic for Applications

WVDOT West Virginia Department of Transportation

xxi

CHAPTER 1. INTRODUCTION

United States traffic safety statistics show that fatalities resulting from motor vehicle crashes

decreased from 2005 through 2011, but increased slightly in 2012. Despite these encouraging 

trends, the National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis 

Reporting System reported approximately 5.6 million traffic crashes in 2012, including 

33,561 fatalities and more than 2.3 million injuries.

(1) Rural fatalities accounted for 54 percent 

(18,170) of all traffic fatalities in 2012, although 19 percent of the U.S. population lived in rural 

areas. Further, in 2012, the fatality rate per 100 million vehicle mi traveled was 2.4 times higher 

in rural areas than in urban areas. This disparity between rural and urban road fatal crash rates 

has not changed appreciably in more than a decade.

(2)

NHTSA defines speeding-related crashes as “the driver behavior of exceeding the posted speed 

limit (PSL) or driving too fast for conditions,” which has been cited as a contributing factor in 

approximately 31 percent of traffic fatalities in the United States.

(3)

This same research shows 

that a significant percentage of crashes occurring at night and on rural roads are speeding related. 

Speeding-related factors were also prevalent among single-vehicle run-off-road crashes and 

crashes on horizontal curves. It should be noted that speeding-related crash statistics that are 

compiled and reported annually by NHTSA rely on databases consisting of electronically coded 

police accident reports. Therefore, an element of subjectivity (i.e., the reporting officer’s expert 

opinion of whether speed was a contributory cause of a crash) is present. The extent of reporting

bias is unknown. 

The relationship between operating speeds and safety is not entirely clear. There is no consensus 

regarding the association between speed and crash frequency; however, there is agreement that 

crash outcomes will be more severe as speed increases. Therefore, it is important to consider 

how roadway and roadside features influence driver speed choice. Roadway and roadside

features provide cues to drivers that influence their speed selections. Supplemental measures, 

such as traffic control devices and speed management strategies, are sometimes used to influence 

driver speed selections to be more consistent with target operating speeds. Designing a roadway 

to influence drivers to travel at a particular “target speed,” while discouraging them from 

traveling at an excessive or inappropriate speed, may help to prevent speeding-related crashes or 

reduce their severity when they do occur. In such cases, free-flow operating speeds near design 

speeds and posted speeds are likely correlated with community goals and expectations. The 

Federal Highway Administration’s (FHWA) Speed Concepts: Informational Guide reviewed a 

number of speed management practices and technologies and describes speed-based technical 

processes that often lead to operating speeds higher than design speeds and PSLs.(4)

The FHWA 

suite of speed management resources also includes Engineering Countermeasures for Reducing 

Speeds: A Desktop Reference of Potential Effectiveness and Speed Management: A Manual for 

Local Rural Road Owners.

(5,6)

This report builds on these previous efforts by further exploring technical speed-related design 

processes and their speed outcomes as well as highway and traffic engineering features that 

influence operating speeds and safety on rural and suburban roads.

1
SCOPE OF RESEARCH AND REPORT ORGANIZATION

The objective of this project was to develop a technical report that describes features and 

treatments that influence operating speeds on curve and tangent sections of rural and suburban 

roads. The research team gathered information for the report from a review and critical synthesis 

of published literature as well as new research conducted as part of this project.

The remainder of this report is organized into the following chapters:

• Chapter 2 provides background and the results of a synthesis of literature related to 

the characteristics of rural and suburban roads, speed-related outcomes of current 

design and operational practices, and traffic engineering treatments, as well as design 

and retrofit decisions and practices that influence operating speeds.

• Chapter 3 describes the process of defining the scope of the research conducted as 

part of this project.

• Chapter 4 describes an operational evaluation of the high-friction surface treatments

(HFST) applied to horizontal curves on rural two-lane roads in West Virginia.

• Chapter 5 documents a speed evaluation of optical speed bar (OSB) treatments 

applied to rural and suburban road segments in Arizona, Alabama, and 

Massachusetts.

• Chapter 6 presents an observational, cross-sectional study on the safety effects of lane 

width and shoulder width combinations on rural two-lane, two-way road segments. 

• Chapter 7 summarizes the entire research effort, provides general conclusions, and 

outlines general considerations for future studies.

2
CHAPTER 2. BACKGROUND AND LITERATURE REVIEW

This chapter consists of three main sections. The first section briefly describes characteristics of 

rural and suburban roads. The second section describes the speed-related outcomes of current 

design and operational practices—specifically, the discussion explains why intermediate and

lower speed roads sometimes operate in a state of design, operating, and posted speed discord, as 

defined by the FHWA Speed Concepts Guide.

(4)

The third section identifies traffic engineering 

treatments, as well as design and retrofit decisions and practices, that influence operating speeds. 

DEFINING RURAL AND SUBURBAN ROADWAYS

Roadway design criteria differ by functional classification, which includes a definition of area 

type—urbanized, small urban area, or rural.(7)U.S. Bureau of Census designates the urbanized 

areas as having populations of 50,000 or more. Small urban areas have populations of 5,000 or 

more and are not within urbanized areas.(7)State transportation department functional 

classification maps provide the boundaries that define the extent of both urbanized and small 

urban areas. Rural areas are all remaining areas in a State outside the urbanized and small urban 

area boundaries. Road designers consider whether an existing or planned road is urban or rural, 

with urban including both urbanized and small urban areas. State transportation department

functional classification maps vary in terminology use but appear consistent with intent. For 

example, the Utah Department of Transportation delineates urban and small urban areas.

(8)

Washington State Department of Transportation shows city limits and urban boundaries.

(9)

Virginia Department of Transportation maps include boundaries for urbanized areas and small 

urban clusters.

(10) New Jersey Department of Transportation (NJDOT) shows only one type of 

urban boundary.

(11)

Although different terms are used, the boundaries seem to be consistently 

based on the FHWA and U.S. Census Bureau definitions. This is not surprising because State 

functional classification requirements are tied to the FHWA Federal-aid Program.(7)

The preceding discussion demonstrates that by using State transportation department functional 

classification maps, any existing or planned road can be designated as urban or rural. Suburban 

road designations are not as definite. The general definition of suburban is “the residential area 

on the outskirts of a city or large town,” but land uses can be more than just residential.

(12) The 

U.S. Department of Justice defines “suburban” as a census block group no more than 30 mi from 

an urban area with a density of at least 500 people per mi2 but fewer than 2,000 people per 

mi2.

(13) Ban and Ahlquist defined four geographic areas of cities—urban zone, urban cluster, 

suburban, and exurban.

(14) They defined suburban areas as those areas located between urban 

clusters and exurban areas, but with blurred boundaries. They define these areas as follows:

• Urban cluster: census block groups of at least 2,500 people but less than 50,000 

people.

• Suburban: non-central county classified as metropolitan.

• Exurban: metropolitan counties outside the ring of suburban counties.

3
The U.S. Department of Agriculture describes a rural area as countryside or settlements of fewer 

than 2,500 people, implying that the areas between urban boundaries and rural areas with 

populations greater than 2,500 may be considered suburban.(15)

Some published documents have tried to summarize common physical characteristics of 

suburban areas. The FHWA Urban Boundary and Federal Functional Classification Handbook

provides general arterial spacing observations by area type: 1⁄2 to 1 mi in urban areas, 1 to 2 mi in 

suburban areas, and 2 to 3 mi in low-density areas.(16) The FHWA publication Access 

Management in the Vicinity of Intersections describes suburban areas as consisting of large-scale 

residential, commercial, industrial, or retail developments typically separated by larger distances 

than in urban areas.

(17)

The following characteristics describe suburban areas:

• Medium-to-long block lengths, 400 ft to 1 mi.

• Signalized intersections on arterials and major collectors.

• Speeds from 35 to 55 miles per hour (mph).

• 30,000 to 50,000 vehicles per day on mainline roadways.

• 5,000 to 15,000 vehicles per day on side streets and nonresidential driveways.

• Moderate-to-large setback of structures.

• Non-traversable medians or continuous two-way left-turn lanes (TWLTL).

• Left and right turn lanes.

• Six or fewer traffic signals per mi.

The FHWA University Course on Bicycle and Pedestrian Transportation offers the idea that 

three types of land use imply suburban character:

(18)

1. Individual tract subdivisions, planned as units, with a sense of order derived from inroad systems. The units consist mostly of single-family, residential homes. Some 

warehousing, shopping, and medical developments may also fall into this category.

2. A linear arterial that is the main source of a community’s image. No organized land-use 

planning occurred, and the arterial serves a mix of long trips and local business 

transactions.

3. Bypassed land that was skipped during the initial development of the area for cheaper 

land and was filled in later with a mix of land uses.

The Texas Department of Transportation’s Roadway Design Manual defines a suburban roadway 

as a high-speed roadway that serves as a transition between urban streets and high-speed, rural 

highways.

(19) It is typically 1 to 3 mi long, has light-to-moderate driveway densities (10 to 30 

driveways per mi), and has both rural and urban characteristics. The specific mixed 

characteristics identified were high-speed operations while using curb and gutter for drainage.

The Pennsylvania Department of Transportation’s (PennDOT) and NJDOT’s Smart 

Transportation Guidebook defines the following seven “context areas” from least to most

developed:

(20)

4
1. Rural.

2. Suburban neighborhood.

3. Suburban corridor.

4. Suburban center.

5. Town/village neighborhood.

6. Town center.

7. Urban core.

The PennDOT and NJDOT guidebook includes a set of quantifiable characteristics for each of 

the seven context areas and a recommendation to base identified land use on this information.

Table 1 summarizes the quantifiable characteristics. 

Table 1. Quantifiable characteristics of land use contexts (PennDOT and NJDOT, 2008).

(20)

Characteristic Rural

Suburban 

Neighborhood

Suburban 

Corridor

Suburban 

Center

Town/Village 

Neighborhood

Town 

Center

Urban 

Core

Density Units

(DU)1

1 DU/

20 ac 1–8 DU/ac 2–30 DU/ac 3–20 DU/ac 4–30 DU/ac 8–50 DU/ac

16–75 

DU/ac

Building 

Coverage N/A < 20 percent 20–35% 35–45% 35–50% 50–70% 70–100%

Lot Size/Area 20 ac 5,000–80,000 

ft2

20,000–

200,000 ft2

25,000–

100,000 ft2

2,000–

12,000 ft2

2,000–

20,000 ft2

25,000–

100,000 ft2

Lot Frontage2 N/A 50–200 ft 100–500 ft 100–300 ft 18–50 ft 25–200 ft 100–

300 ft

Block 

Dimensions N/A 400 ft wide byvaries

200 ft wide 

by varies

300 ft wide 

by varies 200 by 400 ft 200 by 400 ft 200–400 ft

Maximum

Height

1–3 

stories 1.5–3 stories

1 story 

retail; 3–5 

story office

2–5 stories 2–5 stories 1–3 

stories

3–60 

stories

Minimum/

Maximum

Setback

Varies 20–80 ft 20–80 ft 20–80 ft 10–20 ft 0–20 ft 0–20 ft

1

The guidebook does not define a density unit and may instead refer to a dwelling unit; dwelling units per acre are 

used in the guidebook to define high-, medium-, and low-density areas. 2

The distance measured between points where side property lines meet road right-of-way lines.

N/A = Not Applicable

Land use contexts should be broadly defined for road segments greater than 600 ft in length 

because of practical limitations on the frequency of changing the roadway typical section over a 

short stretch of road.

(20)

The Smart Transportation Guidebook includes a “matrix of design values” with design criteria as 

rows and land use contexts as columns for five different roadway types: 1) regional arterial, 

2) community arterial, 3) community collector, 4) neighborhood collector, and 5) local road.(20)

This roadway typology is different than the existing functional classification system outlined by 

FHWA and was proposed to capture the actual role of the roadway in the surrounding 

community.(7) Access, mobility, and speed are considered on the road segment of interest as 

opposed to using only one functional classification for an entire highway.

The literature review on area type definitions demonstrated the lack of an objective definition for 

“suburban.” Suburban areas may be inside or outside of urban boundaries. Physical 

5
characteristics vary. Because the scope of this research project is rural and suburban roads, the 

research team relied on State-specific definitions of these area types when gathering information

about rural and suburban roads in that State.

SPEED CONCEPTS

This section describes the relationships among design, operating, and posted speed limits during 

the project development process (pre- to post-construction). In addition, it also discusses the

known relationship between speed and safety, including both crash frequency and severity.

Relationship Among Design, Running, Operating, and Posted Speeds

This section discusses road geometric design practices and speed-related outcomes, with 

particular focus on the concepts of design speed, operating speed, and posted speed. Several 

sections draw significantly on the FHWA’s Speed Concepts: Informational Guide and 

Understanding Speed Concepts, as well as on follow-up work to the informational guide 

published by Porter et al.(4,21,22) The following sections use both operating speed and running 

speed to describe relationships between design speed and observed speeds. Operating speed is 

“the speed at which drivers are observed operating their vehicles during free-flow conditions.”

Running speed is “the speed at which an individual vehicle travels over a highway section.”

Operating speeds and running speeds during off-peak, low-volume conditions provide similar 

insights on how drivers select speeds based on the road geometrics, particularly on uninterrupted 

flow facilities.

U.S. transportation agencies develop designs and prepare plans for road construction. Designers 

rely on a set of adopted standards and policies that include design criteria. The most commonly 

adopted policy is A Policy on Geometric Design of Highways and Streets (Green Book), 

published by the American Association of State Highway and Transportation Officials 

(AASHTO).

(23) Design criteria in the Green Book are based on research and practice and are 

generally expressed as minimum, maximum, or ranges of values for design elements (e.g., 

minimum horizontal curve radius, maximum grade). When adopting or recommending design 

criteria, individual State transportation departments and other transportation agencies, as well as 

AASHTO, consider factors such as safety, efficiency, driver comfort, aesthetics, construction 

cost, and future maintenance activities. AASHTO updates design criteria in the Green Book as 

meaningful research results become available. The process a designer follows to establish design 

criteria for any given project remains essentially unchanged since the earliest design 

policies.(24,25)

Design Speed 

U.S. road geometric design practice is based on selecting and applying a design speed. The 

design speed is usually selected during preliminary design activities and influences subsequent 

design decisions. Fitzpatrick et al. provided a synthesis of design speed selection practices.(26)

Donnell et al. provided the inputs to and outcomes of design speed selection.(4)

6
A review of AASHTO design policies revealed three different design speed definitions:

• Pre-1954: The maximum appropriately uniform speed that probably will be adopted 

by the faster group of drivers but not, necessarily, by the small percentage of reckless 

ones.(27)

• 1954−2001: The maximum safe speed maintained over a specified section of highway 

when conditions are so favorable that the design features of the highway govern.

(23)

• 2001–present: A selected speed used to determine the various geometric design 

features of the roadway.

(28, 29)

Although the wording has changed, the basic application and interpretation has not. Definitions 

and supplemental guidance on design speed selection imply the design speed is conceptually 

consistent with operating speeds at the higher end of the speed distribution observed on a road 

segment. In other words, the majority of drivers will travel at or below the design speed. The 

second implication is that drivers traveling at or below the design speed are traveling at safe 

speeds. Drivers traveling above the design speed also travel above the safe speed. Subsequent 

research and analysis have shown that traveling above the design speed is not necessarily less 

safe than traveling below the design speed. There are documented cases where the PSL is higher 

than the design speed but less than inferred design speed, the “maximum speed for which all 

critical design-speed-related criteria are met at a particular location.”

(21) There has been no 

thorough research regarding safety performance on road segments with different design speeds, 

inferred design speed, operating speed, and posted speed relationships.

As early as 1954 and 1957, AASHTO design policies described the expected relationships 

between the design speed and average running speed―and current policy reflects these. The 

policies suggested that running speeds would be close to design speeds when design speeds were 

low. It was also recognized that “some sections of low design speed highways are frequently 

overdriven, with an appreciable number of drivers exceeding the design speed.” (24) Design 

policy noted that the speed selected by most drivers would increase as design speed increased, 

but at a lower rate. AASHTO provides the following example(22):

Comparing the observed average speeds with calculated design speeds, it is found 

that on sections of highway having a 30-mph design speed the average running 

speed is approximately 90 percent of the design speed. The ratio gradually 

decreases to about 70 percent for highway sections with a design speed of 

70 mph. (p. 40)

AASHTO expanded the design speed and running speed relationships to include numbers for 

both low volume and peak volumes.(24) Figure 1 illustrates these relationships.(22) Table 2

provides current design speed–running speed relationships. 

7
Reproduced with permission of the Transportation Research Board

Figure 1. Graph. Approximate relationships between design and running speeds for urban 

conditions (figure 1 from Porter et al., 2012).

(22)

Table 2. Relationship between design speed and average running speed (table 3-6 in

AASHTO 2011).

(28)

Design Speed 

(mph)

Average Running Speed 

(mph)

Design Speed 

(mph)

Average Running Speed 

(mph)

15 15 50 44

20 20 55 48

25 24 60 52

30 28 65 55

35 32 70 58

40 36 75 61

45 40 80 64

Figure 1 and table 2 illustrate that current practice related to selecting design speed continues to 

be influenced by early design speed definitions and the ideal design speed and running speed 

relationships. The early definitions suggest selecting a high design speed if a majority of the 

drivers will select speeds below the design speed and the design speed reflects a maximum safe 

speed. Operating speeds will likely be close to their targeted range because they are not expected 

to increase at a rate directly proportional to design speed. There will also be a larger buffer 

between operating speeds and design speeds at higher design speed values, which is desirable 

because (at the time) design speed represented the maximum safe speed. However, the design 

speed definition has changed. The current definition removes direct references to safety but 

reflects the same basic philosophy in supplemental guidance related to design speed selection 

until recently(29)

:

15

25

35

45

55

65

25 35 45 55 65

Running Speed, mph

Design Speed, mph

8
Except for local streets...every effort should be made to use as high a design speed 

as practical to attain a desired degree of safety....(p. 67)

AASHTO states that “every effort should be made to attain a desired combination of safety, 

mobility, and efficiency within the constraints of environmental quality, economics, aesthetics, 

and social and political impacts.”(28)

Once planners select a design speed, they then determine minimum (or maximum) design values 

for a number of elements. The next section discusses these other design criteria. 

Other Design Criteria

Design criteria most directly related to design speed are for horizontal curvature (superelevation, 

side friction, and curve radius relationships) and required stopping sight distance. The maximum 

side friction factor and maximum rate of superelevation parameters are the parameters used to 

establish the minimum radius of curvature. The values for maximum side friction factor are 

based on driver comfort, not on physical side friction supply and demand relationships. The 

result is a significant “margin of safety” between friction values used for design and friction 

supply at the road surface–tire interface at the point of impending skid. Figure 2 provides an 

example.(22) The numbers for side friction supply were based on a recent re-analysis of findings 

by Harwood et al.(30) They are applicable for roadways on level or near-level grades; National 

Cooperative Highway Research Program (NCHRP) Project 15-39 is currently investigating 

aspects of friction supply within horizontal curves on steep grades.(31) Figure 3 illustrates the 

effect of the margin of safety on determining the minimum radius of curve.

(22) An additional

relationship provided shows the minimum radius of curve based on truck rollover thresholds for 

trucks traveling at the design speed. Harwood et al. also provides the basis for the rollover 

threshold numbers.(30) Side friction demand is one factor used to determine horizontal curve 

signing needs. Bonneson et al. provided a detailed review of related published literature and 

curve signing guidelines.(32)

9
Source: Transportation Research Board

Figure 2. Graph. Comparison of maximum side friction factor used for design to available 

side friction (figure 2 from Porter et al., 2012).(22)

Reproduced with permission of the Transportation Research Board

Figure 3. Graph. Comparison of minimum curve radius used for design to minimum curve 

radii (figure 3 from Porter et al., 2012).

(22)

The perception-reaction time and the deceleration rate supply the parameters used to establish 

the minimum required stopping sight distance. The currently recommended design is a 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

10 20 30 40 50 60 70 80 90

Side Friction Factor, f

Design Speed, mph

Available ‘f’, point of impending skid for 

passenger cars, wet pavement

“Margin of Safety”

Maximum ‘f’ used for design

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Minimum Curve Radius, feet

10 20 30 40 50 60 70 80 90

Design Speed, mph

Minimum curve radius used for design

Minimum curve radius based on actual f, 

passenger cars, wet pavement

Minimum curve radius 

based on truck rollover

10
perception-reaction time of 2.5 s.(28) The 2.5-s perception-reaction time is based on a synthesis of 

four studies and is believed to encompass the capabilities of most drivers, including older 

drivers, and to exceed the 90th percentile of reaction time for all drivers. (See reference 28 and 

33 through 36.) A deceleration rate of 11.2 ft/s is used for design.(37) This value is based on 

research by Fambro et al.(36) Most drivers decelerate at rates greater than 14.8 ft/s and 

approximately 90 percent decelerate at rates greater than 11.2 ft/s. These rates are well within 

those required for drivers to maintain steering control during braking on wet surfaces.(28)

A conservative design approach becomes apparent when comparing the limiting parameter 

values used for the design of horizontal curves and calculating required stopping sight distance to 

the observed parameter values found in published research results. Friction supply is 

significantly greater than maximum friction used for design. The perception-reaction time used 

for design represents a 90th percentile value (i.e., 90 percent of drivers have faster perceptionreaction times). Deceleration rates assumed for design represent a 10th percentile value (i.e., 

90 percent of drivers decelerate at higher rates). The conservative approach is consistent with 

other engineering disciplines when there is variability in design parameters. Values suggest that a 

majority of drivers can traverse a horizontal curve or stop prior to hitting an object in the 

roadway if they are traveling at a rate higher than the design speed—even if the minimum design 

values have been used. 

Actual design values are determined once minimum values are established. The Green Book

recommends that “Above-minimum design criteria for specific design elements should be used, 

where practical...” and “Although the selected design speed establishes the limiting values of 

curve radius and minimum sight distance that should be used in design, there should be no 

restriction on the use of flatter horizontal curves or greater sight distances where such 

improvements can be provided as part of an economical design.”

(28) The process results in the 

inferred design speed, defined above as meeting the maximum speed for which all critical design 

speed-related criteria at a particular location are greater than the design speed. Speed-related road 

cues perceived by the driver (e.g., available sight distance, degree of curvature) are more 

associated with inferred design speed than with design speed. Operating speeds have been shown 

to increase as inferred design speed increases.(21,38,39)The following example illustrates some of 

the key concepts discussed here.

Example

A suburban road is classified as an urban collector. The design speed is 35 mph and the 

maximum rate of superelevation is 6 percent. The road is undivided with a normal crown of 

2 percent. 

The maximum side friction factor for a 35 mph design speed is 0.18 (see figure 4).

11
Source: AASHTO

Figure 4. Graph. Maximum side friction factor assumed for design (figure 3-6 from 

AASHTO 2011).

(28)

The equation in figure 5 then computes the minimum radius for horizontal curves on this road:

Figure 5. Equation. Minimum radius of horizontal curvature.

Where:

Rmin = minimum radius of horizontal curvature (ft).

V = design speed (mph).

emax = maximum rate of superelevation (percent).

fmax = maximum side friction factor.

The calculation to determine minimum radius of horizontal curvature for the suburban road in 

this example, with a 35-mph design speed, 6-percent maximum rate of superelevation, and 

0.18 maximum side friction factor, is 340 ft.

Assume a radius of 1,000 ft is selected for a curve on this suburban road based on the Green 

Book guidance that “there should be no restriction on the use of flatter horizontal curves or 

15(0.01 ) max max

2

min

e f

V R

+ =

12
greater sight distances where such improvements can be provided as part of an economical 

design.” (28)

The cross section would remain at normal crown for this selected radius if superelevation and 

side friction are distributed according to Method 2 (see table 3). 

Table 3. Minimum radii and superelevation for low-speed urban streets (part of 

figure 3-13b from AASHTO 2011).

(28)

e

(%)

Vd = 

15 mph

R (ft)

Vd = 

20 mph

R (ft)

Vd = 

25 mph

R (ft)

Vd = 

30 mph

R (ft)

Vd = 

35 mph

R (ft)

Vd = 

40 mph

R (ft)

Vd = 

45 mph

R (ft)

-6.0 58 127 245 429 681 1,067 1,500

-5.0 56 121 231 400 628 970 1,350

-4.0 54 116 219 375 583 889 1227

-3.0 52 111 208 353 544 821 1125

-2.8 51 110 206 349 537 808 1107

-2.6 51 109 204 345 530 796 1089

-2.4 51 108 202 341 524 784 1071

-2.2 50 108 200 337 517 773 1055

-2.0 50 107 198 333 510 762 1039

-1.5 49 105 194 324 495 736 1000

0 47 99 181 300 454 667 900

1.5 45 94 170 279 419 610 818

2.0 44 92 167 273 408 593 794

2.2 44 91 165 270 404 586 785

2.4 44 91 164 268 400 580 776

2.6 43 90 183 265 396 573 767

Source: AASHTO

The inferred design speed in this case is the maximum speed that meets the side friction factor 

criterion for the horizontal curve. A superelevation value of -2 percent is used for the inferred 

design speed calculations because the adverse cross slope in one travel direction will result in a 

component of the vehicle’s weight pointed to the outside of the curve. (The opposite travel 

direction would have a superelevation of +2 percent and, as a result, a higher inferred design 

speed.) The equation in figure 6 computes the required side friction factor for a vehicle 

traversing a horizontal curve:

Figure 6. Equation. Required side friction factor.

Where:

f = required side friction factor.

V = speed of vehicle traversing the horizontal curve (mph).

R = radius of horizontal curvature (ft).

e = superelevation (percent).

e

R

V f 0.01

15

2

= −

13
The inferred design speed estimate for the horizontal curve uses an iterative process. Table 4

summarizes the results. Donnell et al. provides additional detail on how to perform inferred 

design speed calculations.(21)

Table 4. Results of iterative inferred design speed calculations.

Iteration V f Comment

1 35 0.102 The required side friction, 0.102, is less than the maximum for 35 mph, 0.18. 

The inferred design speed is higher than 35 mph.

2 45 0.155 The required side friction, 0.155, is greater than the maximum for 45 mph, 

0.15. The inferred design speed is lower than 45 mph.

3 40* 0.127 The required side friction, 0.127, is less than the maximum for 40 mph, 0.16. 

The inferred design speed is 40 mph.

*The inferred design speed in this example is calculated to the nearest 5-mph increment for which the design side 

friction is satisfied. If one were to assume a linear change in friction with each unit increase in the speed, the 

inferred design speed could be calculated to the nearest 1 mph, using the process described in this example.

The calculations used to populate table 4 were based on the maximum side friction factors used 

for design. As previously noted, the design values are significantly lower than limiting values of 

side friction (see figure 4). The curve in this example would have an inferred design speed of 

approximately 80 mph using the calculations based on side friction supply for passenger cars on 

wet pavement at the point of impending skid.

Speeding-Related Outcomes of U.S. Design Practice 

Donnell et al. describes and illustrates the speed-related outcomes of U.S. road design practice. 

Figure 7 illustrates a typical outcome on low- to intermediate-speed roads.(21) While design speed 

is determined during the design process, inferred design speeds are determined implicitly (but 

typically not considered or calculated) as a result of geometric design decisions. The inferred 

design speeds are often higher than the design speed because designers are encouraged to exceed 

minimum values determined for geometric design features that are determined based on the 

design speed. The result is that many design features meet criteria for design speeds far greater 

than the design speed (shown by the inferred design speed line above the designated design 

speed line in figure 7). Initial posted speeds are generally equal to or less than the design 

speed.

(26) As figure 7 shows, actual operating speeds may be higher than both the speed limit and 

the design speed after a road is open to traffic. 

14
Reproduced with permission of the Transportation Research Board

Figure 7. Chart. Observed speed-related outcomes of the typical U.S. design practice 

(figure 2a from Donnell et al., 2009).(21)

Observations show that mean operating speeds tend to be higher than design speeds of 

approximately 45 to 50 mph or less (the exact crossing point appears to depend on facility type). 

Observed 85th percentile speeds tend to be higher than design speeds of approximately 55 mph 

or less. Figure 8 illustrates these findings.(22)

Reproduced with permission of the Transportation Research Board

Figure 8. Graph. Observed relationships between design speed and operating speeds

(figure 5 from Porter et al., 2012).(22)

15

25

35

45

55

65

25 35 45 55 65

Running Speed, mph

Design Speed, mph

15
Tarris et al. first illustrated conceptually possible speed-related outcomes of U.S. road design 

practice on road segments with a series of tangents and curves (see figure 9).

(40)

The figure 

compiles many of the ideas of the preceding discussion. Donnell et al. later used a series of case 

studies with field data that invalidated the concepts portrayed in this figure.(4)

Reproduced with permission of the Transportation Research Board

Figure 9. Diagram. Conceptual speed-related outcomes of U.S. road design practice 

(adapted from figure 1 in Tarris et al., 2000).(40)

Donnell et al. defined the terms “speed harmony” and “speed discord.”

(4,21)

• Speed harmony: Condition resulting when the designated design speed is within a 

specified range (i.e., ± 5 mph) of the observed 85th percentile operating speed; the 

85th percentile operating speed is within a specified range (i.e., ± 5 mph) of the PSL. 

The inferred design speed is equal to or greater than the designated design speed; the 

posted speed is less than or equal to the designated design speed.

• Speed discord: Roadway design that produces a condition in which the design speed 

is lower than the PSL, various operating speed measures, or both.

Design that results in speed harmony is generally desired.

Relationship Between Speed and Safety

Speeding and relationships between operating speed and safety are poorly understood, likely a 

result of confusing terminologies, inconsistent crash coding, and conflicting research results. 

Consider the following:

16
• Discussions that relate speed to safety sometimes reference studies that show a 

“u-shaped curve”—while faster vehicles have an increased crash risk, so do slower 

moving vehicles.(41,42)

• Annual compiled and reported speeding-related crash statistics rely on databases 

consisting of electronically coded police crash reports (e.g., Fatality Analysis 

Reporting System, General Estimates System, and other State crash databases). These 

data reflect an element of subjectivity (i.e., the reporting officer’s expert opinion of 

whether speed was a contributory cause of a crash); however, the extent of this 

reporting bias is unknown.

• Speed is central to decisions made throughout the lifecycle of highways and streets. 

Agencies and units within agencies (e.g., design, traffic control, operations, 

enforcement) have different responsibilities and use unique terminologies to define 

speed (e.g., safe speed, design speed, inferred design speed, operating speed, 

regulatory speed, posted speed, Nth percentile speed). Conclusions about whether 

traffic in general or a particular driver was “traveling too fast for conditions” would 

also likely vary between groups.

Two separate literature reviews on speed and safety, citing 73 and 65 published sources, 

respectively, concluded that “although evidence tended to support the notion that accident risk 

increased with speed, more study was needed to determine when changes in speed limit affect 

accidents or to predict the sizes of these effects.”

(43,44,45)

Although these issues can confuse the speed-safety paradigm, defined relationships among

distance, time, and speed lead to the following six conclusions:

• The distance that a vehicle travels as a driver reacts to a particular scenario in the 

roadway ahead (e.g., lead vehicle slowing or stopping, pedestrian or bicyclist crossing 

traveled way) increases as speed increases.

• Braking distance increases as travel speed increases for a given deceleration rate.

• The time available to recover from a roadside encroachment decreases as speed 

increases.

• The probability that the forces required for a vehicle to maintain a circular path on a 

horizontal curve will exceed available forces (from friction and vehicle weight) 

increases as speed increases.

• The distance a vehicle travels while a driver is distracted (e.g., eye glances away from 

roadway ahead) increases as speed increases.

• The rate at which a driver must process information increases as speed increases. 

These points indicate that, all else being equal, drivers traveling at faster speeds may be less 

likely to successfully react to unexpected situations (e.g., changes in lead vehicle behavior, 

17
nonmotorized users crossing traveled way, changes in roadway alignment, roadside 

encroachments) than drivers traveling at slower speeds. 

The energy dissipated during a crash is directly proportional to the square of travel speed at the 

time of the crash. Impact forces affecting drivers increase as this initial speed increases and as 

the time over which energy is dissipated decreases. Therefore, the crash severity (i.e., probability 

of fatality or severe injury) increases as initial travel speed increases. Figure 10 depicts previous 

research (Joksch et al.) that demonstrates an exponential relationship.

(46)

Figure 10. Graph. Relationship between change in travel speed during a crash and the 

probability of fatality (plotted model estimated by Joksch).(46)

The challenge to road designers, traffic engineers, and safety professionals is to design and 

retrofit roadways so that drivers choose speeds consistent with the intended operating speed of a 

facility (indirectly defined by the design speed, speed limit, and/or advisory speed). 

Geometric Design Features

There are well-documented relationships among geometric design features, speed, and safety in 

the design consistency and crash prediction modeling literature for rural, two-lane highways. 

Similar literature on other rural and suburban roadway types is less developed. This section 

provides a general summary of the relationships among geometric design features, operating 

speeds, and safety on rural and suburban roadways. The discussion focuses on horizontal 

alignment, vertical grades, and cross-section elements. The research team reviewed domestic and 

international literature.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

Probability of fatality

Change in speed (mph)

18
In much of the design consistency literature, researchers use statistical models to estimate the 

association between operating speeds and geometric design features. The most commonly 

modeled operating speed measures are the mean or 85th percentile speeds of a sample of drivers 

(mostly free-flow passenger cars, with free-flow defined as having a magnitude of a preceding 

headway greater than some value). The Operational Effects of Geometrics Committee (AHB65) 

of the Transportation Research Board (TRB) prepared the Modeling Operating Speed Synthesis 

Report, which is a combination of operating speed models developed in different regions of the 

world.(47) The research team used this report to prepare table 5, which summarizes modeled 

associations between design elements and operating speeds. The values shown are individual or 

range of estimated parameters from linear regression models. They represent the expected 

change in the magnitude and direction of operating speed associated with a unit change of the 

design element. For example, the lane width parameter of 2.08 indicates that operating speed is 

expected to decrease by 2.08 mph for every 1 ft reduction in lane widths. The parameter for the 

grade of horizontal curve approach tangent indicates that operating speed is expected to decrease 

by 1.47 mph for every 1 percent increase in grade. 

Table 5. Statistical associations between vehicle operating speeds and geometric design 

features. (Information gathered from TRB Operational Effects of Geometrics Committee, 

2011).(47)

Geometric Feature

Change in Operating Speed per Unit Change 

in Geometric Feature (mph)

Rural Two-Lane 

Highways

Rural MultiLane HighwaysSuburban 

Highways

Lane width (ft) 0.032–2.08 N/A N/A

Paved shoulder width (ft) 0.015–0.17 0.328 N/A

Length of horizontal curve approach 

tangent (ft) -0.005–0.008 N/A N/A

Grade of horizontal curve approach 

tangent (percent) -1.47–3.11 N/A N/A

Length of horizontal curve departure 

tangent (ft) -0.002–0.023 N/A N/A

Grade of horizontal curve departure 

tangent (percent) -1.45– -0.224 N/A N/A

Length of horizontal curve (ft) -0.009–0.001 0.00002 N/A

Horizontal curve deflection angle 

(degrees) -0.21– -0.08 N/A N/A

Radius of horizontal curve (ft) 0.001–0.026 0.0005 N/A

Degree of horizontal curve -0.481– -0.189 N/A -17.90– -23.4

Rate of vertical curvature (ft/ft) 0.011 N/A N/A

N/A = Not Available

Much of the work on statistical modeling of vehicle operating speeds has been for rural, two-lane 

highways. It appears that a unit decrease in the lane width is associated with a decrease in 

operating speed, although the magnitude of the decrease varies widely across published research. 

Similarly, a unit decrease in the paved shoulder width is consistently associated with a decrease 

in operating speeds. Narrowing lane and shoulder widths appears to be a possible speedreduction measure on rural, two-lane highways. The research team also found consistency across 

two-lane rural highway speed prediction modeling research for the grade of the horizontal curve 

departure tangent, the horizontal curve deflection angle, and the degree of horizontal curve. All 

19
signs in table 5 for these variables are negative, which indicates that a unit increase in any of 

these dimensions is associated with a decrease in operating speeds. This suggests that increasing 

grades on the departure tangent, increasing the horizontal curve deflection angle, or increasing 

the degree of curve, will produce lower vehicle operating speeds. Note that the degree of 

horizontal curve is inversely related to the radius of curve, thus increasing the radius of curve is 

expected to increase operating speeds, which table 5 also illustrates. Porter et al. noted that the 

sensitivity of operating speeds to changes in geometry is relatively small:

(22)

The concept that road geometry can be adjusted to achieve consistency between 

target speeds and operating speeds is based on the premise that changes in 

geometry will affect operating speeds. Research has shown, however, that 

operating speeds may not be influenced by geometric design decisions unless very 

constrained dimensions are used. This may be counterintuitive given that 

geometric design criteria are dependent on design speed. (pp. 43–44)

There is limited published research relating geometric design features to vehicle operating speeds 

on rural, multi-lane highways and suburban roads. However, the statistical associations in table 5

for these two roadway types appear to confirm the findings for rural, two-lane highways—

narrower paved shoulders and sharper horizontal curves are both associated with lower operating 

speeds, but the relationships are not highly sensitive.

Changes in road geometry associated with reductions in speeds (e.g., smaller horizontal curve 

radii, narrower lane widths, and narrower shoulder widths) are sometimes associated with 

increases in expected crash frequency. The following paragraphs discuss this phenomenon at 

greater length.

The Highway Safety Manual (HSM) contains crash modification factors (CMF) for geometric 

design features, particularly for rural, two-lane highways. Appendix A of this document includes 

available HSM CMFs for various geometric design features. In some cases, there are references 

to a figure or a table from the HSM. In other cases, an expected value is provided for the CMF 

with a standard error of the estimate. 

Figure 11 shows an HSM sample of the lane width and shoulder width CMFs for rural, two-lane 

highways. In this case, the baseline condition is a 12-ft travel lane and a 6-ft shoulder, which has 

a combined CMF equal to 1.00 (i.e., the base condition). As illustrated in figure 11, it is expected 

that narrowing the lane width, shoulder width, or both will increase crash frequency. It is 

expected that CMFs related to other geometric elements, as well as to other facility types, follow 

similar patterns; narrower, geometries will result in higher crash frequencies. 

20
Figure 11. Graph. CMFs for combinations of lane and shoulder widths for two-lane rural 

highways (Average Annual Daily Traffic > 2,000 vehicles/day).

Gross et al. developed CMFs for lane-width–shoulder-width combinations on rural, two-lane 

highways; these are plotted in figure 12.

(48) The interactions between lane width and shoulder 

width were accounted for during CMF estimation by using a case-control methodology. Results 

yield the following conclusions:

• Shoulder width has a larger effect on safety when lanes are narrow, but the effect of 

shoulder width decreases as lane width increases.

• An increase in lane width does not always result in an increase in safety, particularly 

when shoulder widths are wider.

• Rural, two-lane highway segments with lane-width–shoulder-width combinations 

totaling 16 to 17 ft (e.g., 10-ft lanes with 6-ft shoulders; 11-ft lanes with 6-ft 

shoulders, 12-ft lanes with 5-ft shoulders) may be safer than rural, two-lane highway 

segments meeting HSM base conditions (i.e., 12-ft lanes with 6 ft shoulders). 

Estimated interactions between lane and shoulder width by Bonneson and Pratt have similar 

implications—the safety effect of lane width depends on the shoulder width. (49)

1

1.2

1.4

1.6

10 11 12

CMF

Lane Width (ft)

21
Reproduced with permission of the Transportation Research Board

Figure 12. Graph. CMFs for combinations of lane and shoulder widths for two-lane rural 

highways (figure 1 in Gross et al., 2009).

(48)

Much of the research cited earlier in this section treats speed and safety effects of geometric 

design elements independently. Crash prediction algorithms currently in the HSM would lead 

geometric designers to conclude that larger radii horizontal curves, flatter vertical grades, and 

wider lane and shoulder widths will result in lower expected crash frequencies than geometric 

designs with smaller radius curves, narrower lane and shoulder widths, and steeper vertical 

grades. Speed prediction algorithms suggest that wider and flatter geometric designs produce 

higher vehicle operating speeds than do more curvilinear designs with narrower cross sections. 

Researchers explored the simultaneous effects of geometric design decisions on speed and safety 

by overlaying the results from the independently conducted speed and safety studies. Figure 13

through figure 15 provide the results.

The solid line in figure 13 represents the predicted 85th percentile speed for free-flow passenger 

cars as a function of horizontal curve radius on two-lane rural highways. The research team used 

models reported by Fitzpatrick et al. to create the operating speed line.(50) The dashed line 

represents the CMF for horizontal curve radius on two-lane rural highways from the HSM.

(37)

Horizontal curve radius clearly influences vehicle operating speeds; however, the effect is 

nominal until the radius falls below approximately 1,000 ft. Similarly, the expected crash 

frequency changes only nominally until the horizontal curve radius falls below 1,000 ft. 

0.6

0.8

1

1.2

1.4

1.6

10 11 12

CMF

Lane Width (ft)

22
Figure 13. Graph. Relationships among horizontal curve radius, speed, and safety for twolane rural highways.

Figure 14 shows the speed and safety effects for lane width on rural, two-lane highways. The 

solid line shows the predicted 85th percentile speed for free-flow passenger cars as a function of 

lane width on rural, two-lane highways. The research team used models reported by Lamm and 

Choueiri to create the operating speed line.(51) The dashed lines show the CMFs for lane width on 

rural, two-lane highways from the HSM for two levels of average daily traffic volumes.(37) The 

lane width is linearly related to the predicted operating speed—wider lane widths are associated 

with higher speeds. The expected crash frequency changes nominally for lane widths between 

11 and 12 ft; however, the CMF increases significantly as lane widths are reduced below 11 ft. 

The lane width CMFs reported is applicable to run-off-road, sideswipe, and head-on collisions. 

23
Figure 14. Graph. Relationship between lane width and speed and safety for two-lane rural 

highways.

Figure 15 shows the speed and safety effect tradeoff for the shoulder width on rural, two-lane 

highways. The solid line shows the predicted 85th percentile speed for free-flow passenger cars, 

as a function of shoulder width on rural, two-lane highways. Again, the research team used 

models reported by Lamm and Choueiri to create the operating speed line.(51)The dashed lines 

show the CMFs for shoulder width on rural, two-lane highways from the HSM for two levels of 

average daily traffic volumes.(37) The shoulder width is linearly related to the predicted operating 

speed—wider shoulder widths are associated with higher speeds. The expected crash frequency 

decreases in a linear manner as the shoulder width increases from 0 to 8 ft. As with lane width, 

the shoulder width CMFs reported are applicable to run-off-road, sideswipe, and head-on 

collisions.

The overall conclusion to be inferred from the speed and safety assessment of geometric design 

features is that more forgiving geometric designs generally tend to improve safety performance 

(i.e., fewer expected crashes), according to the HSM; however, more, smaller radii and narrower 

cross sections tend to produce lower vehicle operating speeds. The study by Gross et al. 

indicated that narrower cross-section geometries are not necessarily less safe and that the 

interactions between lane and shoulder widths are important to consider when evaluating safety 

effects (see figure 12, for example).(48) Because there was enough evidence to support exploring 

different combinations of cross-section elements (e.g., lane and shoulder widths) as a strategy to 

reduce operating speeds and improve safety on rural and suburban roads, FHWA recommended a 

new safety study on rural, two-lane roadway cross-section allocation. The study was conducted 

as part of the research project associated with this informational guide.

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

10

20

30

40

50

60

70

9 10 11 12

Speed (mph)

Lane Width (ft)

Crash Modification Factor

HSM CMF: ADT >2,000 

HSM CMF: 400 < ADT <2,000 

24
Figure 15. Graph. Relationship between shoulder width and speed and safety for rural, 

two-lane highways.

Engineering Treatments for Reducing Speeds

Traffic engineering treatments may affect speed or speeding-related crashes on rural or suburban 

roadways. Agencies sometimes implement speed-related traffic engineering treatments on or 

near a roadway section with the intention to modify driver operating speeds or reduce speedingrelated crashes. The literature review identified more than 40 traffic engineering 

countermeasures that show promise of speed reductions or safety improvements on rural and 

suburban road segments. Appendix B includes a tabular summary of the countermeasures 

identified in both the international and domestic literature. This appendix also provides a 

description of the treatment, a photograph of the treatment (when available), the safety and 

operational effectiveness of each treatment, and cost information (if available). Readers are also 

referred to Engineering Countermeasures for Reducing Speeds: A Desktop Reference of 

Potential Effectiveness, Speed Management: A Manual for Local Rural Road Owners, and 

Toolbox of Countermeasures for Rural Two-Lane Curves.

(5,6,52)

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

10

20

30

40

50

60

70

0 2 4 6 8

Speed (mph)

Shoulder Width (ft)

HSM CMF: 400 < ADT <2,000 

HSM CMF: ADT >2,000 

Crash Modification Factor

Expected 85th Percentile Operating Speed

25

CHAPTER 3. GENERAL METHODOLOGIES AND SCOPE

The research team identified several treatments for possible field evaluations during this study 

and based the following list of possible treatments for field evaluations on findings of the 

literature review and State outreach efforts:

• Converging chevron markings: Published literature shows this treatment has 

reduced vehicle speeds by 2 to 3 mph on rural highways; however, there have been no 

documented safety evaluations to date.(53) This treatment can be applied using 

standard pavement marking materials and seems easy to maintain. 

• Narrower allocations of lane and shoulders widths on existing pavement: Design 

consistency literature has shown that narrowing travel lanes or shoulders is associated 

with reduced speed.

(48) Recent research suggests that reallocating lane and shoulder 

widths on an existing pavement can possibly improve safety.(53)

• Speed tables: Studies show this low-speed treatment can significantly reduce travel 

speeds on suburban streets, yet little is known about the safety effects of this 

treatment.(53,54)

• Enhanced speed limit legend with colored surfacing: The Iowa Department of 

Transportation documented that this treatment can significantly reduce vehicle 

operating speeds, but the sample of evaluation sites used is small and no safety 

evaluations have been documented to date.(53) This treatment can be applied using 

standard pavement marking materials and is seemingly easy to maintain. 

• Transverse markings or OSBs: Published literature shows that this treatment has

reduced vehicle speeds by 1 to 5 mph on rural; however, there are no documented 

safety evaluations to date. Highways. (See references 53 and 55 through 58.) This 

treatment can be applied using standard pavement marking materials and seems easy 

to maintain. 

• Red border speed limit sign: Treatment has been shown to reduce vehicle operating 

speeds; however, there are no documented safety evaluations to date.(59) The costs to 

manufacture, install, and maintain this treatment are low.

• HFST: A single evaluation in Florida shows that this novel treatment can reduce 

vehicle operating speeds along curves; however, there are no robust safety 

evaluations reported to date.(60) There appear to be several candidate evaluation sites 

in four States. (Note: A before-after safety evaluation of this treatment is being 

completed under a separate FHWA project, “Evaluations of Low-Cost Safety 

Improvements Pooled Fund Study” (FHWA-HRT-14-065)).

• Zigzag pavement markings: This novel treatment has shown to reduce vehicle 

speeds; however, there are no safety evaluations reported to date.(61) This treatment 

can be applied using standard pavement marking materials and seems easy to 

maintain.

27
• Speed feedback signs: At least seven studies (not including those in school zones)

show significant speed reductions result following speed feedback signs; however, 

the safety effects of these often short-term (less than 1 year) treatments is unknown.

(See references 53 and 62 through 67.)

The FHWA technical review panel for this project organized these nine treatments into three 

groups: 1) treatments it has a high interest in evaluating, 2) treatments it has only a moderate 

interest in evaluating, and 3) treatments it has only a low interest in evaluating. 

The panel’s highest interest treatments were the following, in no particular order:

• HFST.

• Narrower allocations of lane/shoulder widths on existing pavement.

• Converging chevron markings.

Its moderate interest treatments were the following, in no particular order:

• Zigzag pavement markings.

• Transverse markings/OSBs.

The panel’s low interest treatments were the following, in no particular order:

• Speed tables.

• Enhanced speed limit legend with color surfacing.

• Red border speed limit signs.

• Speed feedback signs.

The research team also assessed treatments based on State and local agency interests and their 

willingness to install them for this study purpose. For example, converging chevron pavement 

markings were not included in a treatment evaluation because of a lack of existing treatment

locations on rural and suburban highways and the reluctance of agencies to install and maintain 

this treatment for the purposes of this study.

Based on feedback from FHWA, the current study completed the following evaluations:

• An observational before-after speed and driver behavior evaluation of the HFST on 

rural, two-lane horizontal curves. An observational before-after safety evaluation is 

being completed under a separate FHWA project, “Evaluations of Low-Cost Safety 

Improvements Pooled Fund Study (ELCSI–PFS)” (FHWA-HRT-14-065). Phase VI 

of this effort, Safety Performance Evaluation, includes the HFST safety evaluation.

• An observational before-after speed study of the OSB treatment on rural and 

suburban roads. In addition, the research team compiled all before-period crash data 

for the OSB treatment sites and comparable reference group sites into an analysis 

database and delivered to FHWA for future safety evaluations. At the time this final 

report was being prepared, less than 1 year had passed since the OSB treatments were 

deployed at most of the treatment sites. An adequate after-period was therefore not 

28
available for the safety evaluation. It is recommended that additional after-period 

crash data be collected during the years 2014 through 2016, and these data be added 

to the existing analysis database prior to completing the safety evaluation.

• A cross-sectional safety evaluation of the allocation of lane and shoulder width on 

existing rural, two-lane highways.

It should be noted that the FHWA selection of treatments to study as part of this effort is not 

necessarily correlated with magnitudes of expected speed reductions.

CRASH ANALYSIS FINDINGS SUMMARY

In addition to the operational and safety evaluations completed for the current study, the research 

team also examined State and local transportation agency police accident reports and completed 

a speeding-related, clinical crash analysis. The purpose of this assessment was to determine 

which speeding-related crash characteristics (e.g., driver age, gender, degree of familiarity with 

the crash location, weather conditions, and other factors) may influence speeding-related crash 

occurrence. This detailed analysis was intended to provide insights into crash causation that 

could not otherwise be determined by analyzing only electronically coded data. To perform this 

evaluation, the research team reviewed police reports from the following jurisdictions:

• Bedford, Shenandoah, and Stafford counties in Virginia.

• Huntingdon County in Pennsylvania.

• Van Buren County (Lawrence Village) and Grand Traverse County in Michigan.

• Hillsborough, Brevard, and Volusia counties in Florida.

The analysis considered speeding-related crashes that occurred in rural and small urban areas 

(population fewer than 50,000 persons), in the years 2004 to 2008. Most local transportation 

agencies that provided hardcopy speeding-related crash reports did not provide data concerning 

the total number of crashes occurring within the jurisdiction during the analysis period.

Therefore, the proportion of the speeding-related crashes in the total crashes was not known. 

The research team used the coding provided on the police accident report to identify speedingrelated crashes. The following three driver actions, either singly or in combination, were 

identified as speed-related crashes:

• Speeding.

• Driving too fast for conditions.

• Failure to maintain proper speed. 

When reviewing the hardcopy police accident reports, the research team not only assessed the 

coding provided by the investigating officer, but also reviewed the narrative and diagram of the 

crash location. 

The research team identified a total of 1,895 nonintersection speeding-related crashes in the nine 

counties (four States) listed above; the team then excluded crashes with the following 

characteristics:

29
• Crashes involving drivers under the influence of alcohol or drugs.

• Collisions with animals.

• Crashes involving motorcyclists or tractor semi-trailers.

• Crashes involving roadway surface conditions that were icy, snow-covered, or with 

loose gravel.

These precipitating events in these crashes might not necessarily be attributable to speeding;

consequently, driver impairment, poor weather conditions, differences in vehicle size and 

weight, and unexpected animal crossings were considered as factors not necessarily associated 

with speeding. After excluding these four crash types, 586 (30.9 percent) crashes met the 

speeding-related crash criteria described above.

The general findings from the clinical speeding-related crash analysis indicate the following:

• Nearly 62 percent of the 586 speeding-related crashes occurred on curves. While the 

mileage of horizontal curve and tangent alignment data within the nine counties in the 

analysis were not available for the current study, literature suggests that crashes on 

curves are three times as likely as crashes on tangents. Assuming that the mileage of 

curved roadway segments is lower than tangent roadway mileage in the data analysis 

files used in this study, the findings appear to support past research related to 

speeding-related crash occurrence.

o Approximately 44 percent of all crashes on curves involved drivers younger than 

21 years old, or with less than 3 years of driving experience.

o A significant proportion (54 percent) of speeding-related curve crashes occurred

on roadways that were likely familiar to the at-fault driver (within 10 mi of driver 

residence).

o Almost 59 percent of all crashes on curves occurred on dry roadways with about 

45 percent of crashes occurring during the daytime. 

• About 38 percent of the analyzed speeding-related crashes occurred on tangents.

o About 40 percent of all crashes involved drivers younger than 21 years or with 

less than 3 years of driving experience.

o Nearly 69 percent of speeding-related crashes occurred on roadways that were

likely familiar to the at-fault driver (within 10 mi of driver residence).

o Almost 54 percent of all crashes occurred on dry roadways while about 73 percent

occurred during daytime travel periods.

The findings from the clinical crash analysis suggest that inexperienced drivers are more likely to 

be involved in speeding-related crashes on curved alignments when compared with tangent 

alignments. In general, however, speeding-related crashes appear more likely on curved road 

segments when compared with tangent roadway segments. Speeding-related crashes on curves 

appear overrepresented at night when compared with daytime speeding-related crashes.

30
CHAPTER 4. OPERATIONAL EFFECTS OF HIGH-FRICTION SURFACE

TREATMENT ON RURAL, TWO-LANE CURVES

Because a current observational before-after traffic safety evaluation is being performed for the 

HFST under another FHWA contract (Evaluation of Low-Cost Safety Improvements Pooled 

Fund Study), this study did not assess crash frequency or severity. Rather, the current study 

assesses the speed effects of HFST, as well as encroachments onto the shoulder or into the 

opposing travel lanes. 

This section describes the HFST site selection criteria, site characteristics and data-collection,

and analysis methods used for evaluation.

OVERVIEW 

HFST can improve the skid-resistance properties of highway pavements. These surfaces are 

typically cold-applied treatments using a resin to bond polish- and abrasion-resistant aggregate to 

an existing pavement structure.

(68) HFST has been applied in the United States on horizontal 

curves along roadway segments and on freeway interchange ramps; to delineate pedestrian, 

bicycle, and bus lanes; and on bridge decks. The roadway segment treatments are intended to 

reduce roadway departure crashes on horizontal curves and are applicable to the present study.

SITE SELECTION 

Through outreach efforts to State transportation agencies, the research team identified several 

HFST horizontal curve treatment sites on two-lane rural roadways in West Virginia for use in 

this study. The West Virginia Department of Transportation (WVDOT) identified many highrisk locations on horizontal curves that were subject to run-off-road crashes and, in an effort to 

reduce injuries and fatalities, began implementing HFST in May 2011 as a low-cost, site-specific 

safety solution on the identified high-risk locations. The following roadways were selected for 

use in this study:

• West Virginia Route 32, mile marker (MM) 2.51, Randolph County.

• U.S. Route 33, MM 0.40, Pendleton County.

• U.S. Route 219, MM 5.81, Randolph County.

• U.S. Route 219, MM 6.32, Randolph County.

In addition to the four treatment sites, the research team identified three corresponding control 

sites. One of these control sites was located on the same route as two treatment sites and thus 

served as a control site for both treatment locations.

SITE CHARACTERISTICS

Table 6 shows the various site-specific data for all of the treatment and control sites. The 

research team selected treatment and control sites with the intent of collecting data at locations 

with varying horizontal curve radii. Control sites were located along the same route as the 

treatment sites. The research team tried to find control sites that were similar to the treatment 

sites with respect to horizontal curve direction, curve radius, curve length, superelevation, and 

PSL (including the advisory speed). The evaluation results section of this chapter provides a plan 

31
view sketch and details concerning each data-collection site, which show the data-collection 

locations with respect to the limits of each curve. 

Table 6. West Virginia HFST site characteristics.

Site 

Number County Route

Radius 

of 

Curve 

(ft)

Length 

of 

Curve 

(ft)

Curve 

Direction

Vertical 

Grade 

(percent)

Superelevation 

(percent)

Posted/

Advisory 

Speed 

Limit 

(mph)

T1 Randolph WV 32 680.4 1,080.5 Right -0.5 8.0 55/40

C1 Randolph WV 32 1073.3 1,213.6 Right -3.5 7.0 55/50

T2 Pendleton U.S. 33 210.0 539.2 Left -8.0 6.0 55/25

C2 Pendleton U.S. 33 264.8 693.6 Left -7.5 8.5 55/25

T3 Randolph U.S. 219

MM 6.32 605.1 753.8 Right -2.0 11.0 55/30

C3/C4 Randolph U.S. 219 544.6 826.9 Right -6.5 12.0 55/30

T4 Randolph U.S. 219

MM 5.81 272.9 673.4 Right -3.0 12.0 55/25

MM = Mile Marker

The Before-Period Data Summary section later in this chapter describes the specific 

characteristics of each data-collection site. 

INSTALLATION 

Contractors for WVDOT installed HFST at the test sites between May 22, 2012, and 

June 4, 2012. HFST was applied by a self-contained, fully automated application vehicle in one 

pass up to 12 ft wide.

OPERATING SPEED EVALUATION METHODOLOGY

The research team employed observational before-after study to evaluate the effects of HFST on 

vehicle operating speeds. Because the intent is that HFST increases the available friction at the 

road surface–tire interface, this treatment may increase vehicle operating speeds. The basis for 

this hypothesis is that HFST improves the friction supply, and therefore, drivers may increase 

their travel speed and demand higher friction. Further, the HFST provides a color contrast when 

applied adjacent to older pavement surfaces and appears similar to a new pavement surface. This 

appearance may also encourage higher vehicle operating speeds. However, because an HFST 

typically is applied only between the limits of the horizontal curve (point of curvature (PC) to 

point of tangent (PT)), it is also possible that this treatment will have little influence on driver 

speed choice. An increase or no change in operating speeds will not necessarily imply a 

treatment failure. Comparisons of required versus available side friction for the speeds observed 

during this study, combined with the results of an ongoing FHWA safety evaluation of HFST, 

will indicate treatment effectiveness. The research team has also included an encroachment 

evaluation to supplement the speed evaluations and the parallel safety effort. Figure 16 and

figure 17 show an example of a curve without the high-friction surface and the same curve with 

the high-friction surface, respectively.

32
Source: Pennsylvania State University

Figure 16. Photo. Photograph of a horizontal curve without the HFST.

Source: Pennsylvania State University

Figure 17. Photo. Photograph of a horizontal curve with the HFST.

The observational before-after evaluations were performed at four treatment sites, and three 

corresponding control sites. (One control site was located on the same route as two treatment 

sites and thus served as a control site for both treatment locations.) The control sites were located 

on the same roadway and had similar geometric features (i.e., lane width and curve radius) when 

compared with the treatment sites. The team collected data at each site for one before period and 

two after periods. This section of the report describes the data-collection equipment and 

locations, sample size requirements, data-collection periods and durations, and the statistical 

analysis methodology for the speed study.

Data-Collection Equipment and Locations

The research team used on-pavement traffic sensors to collect speed data. HI-STAR® sensors 

use vehicle magnetic-imaging technology to record vehicle count, speed, headway, time, 

33
pavement temperature, pavement condition (dry or wet), and vehicle length. These sensors are 

nonintrusive, thus reducing the possibility of drivers adjusting their speeds because of visible 

equipment and human observers. The dimensions of the sensors are 6.5 by 5.5 inches with a 

thickness of 0.625 inches. Each sensor is placed in the center of the travel lane and as a vehicle 

passes over it, the sensor captures changes in the magnetic field. A rubber cover protected the 

sensor and reduced its conspicuity on asphalt surfaces. The research team used Highway Data 

Management (HDM) software to program the sensors prior to field data collection—the internal 

clock was set to record vehicle speeds for up to 12 to 16 h, including both daytime and nighttime 

periods, depending on the time of day and traffic volumes present at the study locations. The 

research team also used HDM software to download the data from the sensors into Microsoft®

Excel spreadsheets. 

The research team placed the sensors at three different points at each study site to collect speed 

data at the treatment and comparison sites: 1) approximately 300 ft prior before the beginning of 

the horizontal curve,

1 2) at the beginning of the horizontal curve (PC), and 3) at the midpoint of 

the horizontal curve. Figure 18 shows the data-collection locations along a study site. HISTAR® sensors are capable of adding time stamp information to each vehicle collected at a 

particular location so vehicles can be tracked. A sensor was also placed in the opposing travel 

lane, near the midpoint of the horizontal curve, to determine whether a vehicle was present at the 

same time that a vehicle was present in the analysis direction. 

The traffic volumes at the study locations were low, with daily traffic volumes ranging from 

approximately 700 to 1,600 vehicles per day. The probability of an opposing vehicle near to or 

on the horizontal curve at the same time as the subject vehicle was small. However, the analysis 

described below did consider the presence of a vehicle in the opposing travel lane.

 1The research team selected the point speed location before the curve to capture speeds that were unaffected by 

the HFST. The “upstream” location of 300 ft before the beginning of the treatment was based on 3.65 s of preview 

time at 55 mph (81 ft/s).

34

 
Figure 18. Diagram. Location of traffic sensors for treatment and control sites

(not to scale). 

Sample Size Determination

The research team used the equation shown in figure 19 to determine the sample size when 

estimating the mean speed from a population of speeds, while minimizing the tolerable error in 

field measurements.

(69)

Figure 19. Equation. Minimum number of measured speeds.

Where:

N = minimum number of measured speeds.

S = estimated sample standard deviation (SD), mph.

K = constant corresponding to the desired confidence level.

E = permitted error in the average speed estimate, mph.

To obtain a range of possible sample sizes, multiple values for the confidence level K were 

considered. The values correspond to confidence levels of 90, 95, and 99 percent. The permitted 

error in the average speed estimate E has been included as a conservative value of ±1 mph. The 

estimate of sample SD S is a function of area type and highway type. The input value of 5.3 is 

representative of a rural, two-lane highway.

(69)

Table 7 summarizes the resulting sample size 

estimates for the proposed confidence interval, permitted error, and SD estimates.

Hi-star Sensor

300 feet

Direction of 

Travel

Direction of 

Travel

PC

2 ( ) E

K N = S

35
Table 7. Sample size determination.

Confidence Level (percent) K N

90 1.64 76

95 1.96 108

99 2.58 187

As table 7 shows, the estimated sample size for the 95th percentile confidence level is 

approximately 110 free-flow passenger car speeds. It should be noted that collecting the 

minimum sample size depends on the traffic characteristics at each study site. The research team 

attempted to collect the minimum sample size during both daytime and nighttime periods, which 

covered one 12- to 16-h period per site (6−8 h of daytime and 6−8 h at night). 

When comparing the difference in means for two different data-collection periods, the expected 

effect size (i.e., difference in mean speeds) is an important consideration. In this case, the 

equation shown in figure 20 was used to estimate the sample size in an observational before-after

study:

Figure 20. Equation. Sum of the sample in before-after comparison groups.

Where:

N = sum of the sample in both comparison groups (before-after).

s = SD of the comparison groups (assumed equal) (mph).

zcritical = level of statistical significance assumed from the standard normal distribution.

zpower = desired statistical power from the standard normal distribution.

D = minimum expected difference between the sample means (mph).

Table 8 shows different sample size estimates, assuming that the SD in speed is 5.3 mph for 

varying levels of critical and power statistics and for different minimum expected differences in 

sample means. 

Table 8. Sample size estimates for comparative research studies.

Difference 

in Means 

(mph)

Level of Statistical Significance (zcritical)

90 percent (zcritical = 1.645) 95 percent (zcritical = 1.96)

Desired Statistical Power (zpower) Desired Statistical Power (zpower)

90 percent

(zpower = 1.282)

95 percent

(zpower = 1.645)

90 percent

(zpower = 1.282)

95 percent

(zpower = 1.645)

1.0 500 822 709 1,169

2.0 125 206 177 292

3.0 56 91 79 130

4.0 31 51 44 73

5.0 20 33 28 47

Because the treatments in the current study are original and little information exists to determine 

the expected difference in means between the before and after periods, the research team used

( ) 2

2 2 4

D

z z

N critical + power = σ

36
2.0 mph as a practical difference. In this case, 95-percent statistical significance and power 

required a minimum sample size of 292 free-flow passenger cars to be included in the combined 

before and after samples (i.e., 146 free-flow speeds per data-collection period). The 110 freeflow passenger car speeds recommended for each data-collection period based on the equation in 

Figure 19 would yield 95-percent statistical significance and more than 90-percent statistical 

power, if a 2.0 mph difference in means was computed between the before and after samples. As 

a result, the research team sought to measure at least 110 free-flow vehicle speeds during each 

12- to 16-h collection period; however, if additional free-flow vehicles were available for 

analysis, the entire sample was used to compare the before with after mean speeds. 

Data-Collection Periods and Durations 

Speed data were collected on weekdays only and during both daytime and nighttime periods. 

Only free-flow vehicles were included in the evaluation sample. The definition of a free-flow 

vehicle also meant no opposing vehicles were present that could influence the subject vehicle. 

The extent to which observations with opposing vehicles could be screened depended on the 

sample size and the estimated effect of the opposing vehicles as described above. Based on 

previous studies, free-flow vehicles were identified as those vehicles traveling with a minimum 

headway of 5 s. (70,71) Data were collected at each study site during favorable driving 

conditions—clear weather with normal visibility (no fog) and dry roadway conditions, without 

the presence of standing water from an earlier rain. These requirements increased the likelihood 

that drivers were selecting their operating speeds based solely on the physical roadway and 

roadside features at each site; during and after HFST implementation, any changes in operating 

speeds could then be associated with the HFST treatment. The data-collection session was long 

enough so that sufficient data were collected to satisfy the sample size requirements after the 

data were screened (i.e., after non-free-flow passenger cars were eliminated from the database).

The study methodology was an observational before-after study. The before data were collected 

before implementing the HFST on horizontal curves. All before data collection occurred during 

summer 2012. Two after data collection periods were included in the evaluation. The first after

period occurred approximately 1 month after implementing the HFST to minimize the novelty 

effects associated with the treatment—these data were also collected during summer 2012. A 

second after period occurred approximately 1 year after implementing the HFST, during summer 

2013. The research team chose a 1-year interval between the after periods to minimize seasonal 

effects and to assess long-term novelty effects of the treatment. It was anticipated that the skidresistant qualities of the HFST would decrease after 1 year because of vehicle tire abrasion and 

likely winter maintenance on roadways in West Virginia. 

Statistical Analysis

Before beginning the data analysis, all raw data from the treatment and control sites were

screened to exclude all vehicles that were not passenger cars and that were not considered freeflow vehicles, as described previously. It was anticipated that vehicles present in the opposing 

travel lane would influence the speed of free-flow vehicles in the subject travel lane; therefore, 

the research team added an indicator variable to the data files to identify free-flow vehicles in the 

subject travel lane that were measured in the presence of an opposing vehicle. The research team 

excluded missing data values from the analysis. The research team carefully evaluated data 

37
points considered outliers to determine whether to exclude them in the analysis. Examples of 

outliers include vehicles traveling at very low speeds or entering or exiting at nearby driveways.

The research team calculated after data screening and mean operating speeds at each sensor 

location for all treatment and control sites and all data-collection periods. The team then 

compared corresponding speed parameters at each site for each data-collection period by 

calculating the numerical differences in these speed parameters. The team applied the t-statistic 

for independent samples to determine whether the differences in mean speed were statistically 

significant. Statistically significant changes in mean operating speeds indicated that the observed 

speeds were different in the two time periods compared. The t-statistic is commonly used to test 

the hypothesis of differences in population parameters.(72) In this study, the null and alternative 

hypotheses for testing the differences in two population mean speed measures, 1 and 2, were

the following:

• Null Hypothesis (H0): There has not been a change in mean speeds as a result of 

HFST implementation, or H0: 1 – 2 = 0.

• Alternative Hypothesis (Ha): There has been a decrease in mean speeds as a result of 

HFST implementation, or Ha: 1 – 2 > 0.

At each study site, a t-statistic is calculated for each sensor location and between data-collection 

periods. Independent two-sample t-statistics is applied to test for the difference between two 

sample means at each study site. The t-statistic for large samples with known variables is 

calculated using the equation shown in figure 21: (73)

Figure 21. Equation. t-statistic to test for the difference between two sample means at each 

study site.

Where:

= mean speed for the before and after periods.

sB, sA = SD of speed for the before and after periods.

nB, nA = sample size in before and after periods.

In figure 21, both the first and second after periods were compared with the before period and to 

each other, using data from the treatment and comparison sites. 

The degrees of freedom (df) for the independent samples t-statistic is nA + nB - 2. The critical 

value when = 0.05 for a one-tail test is 1.645. The null hypothesis is rejected when the 

computed t-test exceeds the critical value, thus concluding that the mean speeds being compared 

differ between the two collection periods being considered. An alternative method to determine 

the statistical significance of HFST on mean speed is the p-value associated with the t-statistic. A 

μ μ

μ μ

μ μ

A

A

B

B

B A

n

s

n

s

X X

t

2 2

( )

+

− =

X B , X A

α

38
low p-value (i.e., less than or equal to 0.05) indicates a high probability that implementing the 

HFST influenced mean speeds between two data-collection periods. The team computed

t-statistic and p-value for each pair of collection periods at each study site. It was anticipated that 

the difference in mean speeds at the control sites would not be statistically significant. However, 

if there is a statistically significant difference in mean speeds between any of the data-collection 

periods, the magnitude of this difference would need to be taken into account. In this case, the 

research team added or subtracted, depending on whether the difference is positive or negative, 

to the numerator in figure 21. As such, the mean speed difference computed at the treatment sites 

was adjusted to account for statistically significant mean speed differences at the treatment sites.

The research team also used the t-test for independent samples to compare the before and after

mean difference in vehicle speeds between the PC and the curve midpoint. The comparison of 

mean delta v, where delta v is the curve PC speed minus the curve midpoint speed, was made in 

the same way as the mean speed comparisons. 

In addition to the t-test, the percentage of vehicles exceeding the PSL and the advisory speed at 

the treatment and control sites was calculated and compared between data-collection periods. 

The percentage of speeding vehicles, PS, was computed using the equation shown in figure 22.

Figure 22. Equation. Percentage of speeding vehicles.

Where:

x = number of vehicles exceeding the PSL.

n = the total number of vehicles in the sample.

By comparing the number of vehicles exceeding the PSL in two data-collection periods, it can be 

determined whether the HFST is associated with reducing the proportion of PSL violations. The 

percent reduction in speeding vehicles %RS from period 1 to period 2, at the treatment and 

control locations, is computed using the equation shown in figure 23.

Figure 23. Equation. Percent reduction of speeding vehicles.

Where:

PSB = the proportion of vehicles speeding during the before data-collection period.

PSA = the proportion of vehicles speeding during the after data-collection period. (Note that there 

will be two after periods for each location.)

= ×100

n

x PS

% ×100 − =

SB

SB SA

S P

P P

R

39
To determine whether the proportion of vehicles exceeding the PSL at the treatment and control 

locations changed between data-collection periods, a Z-test for independent samples was

computed. The null and alternative hypotheses for the test are the following:

• Null Hypothesis (H0): There is no difference between the two sample proportions, or

H0: PSB – PSA = 0.

• Alternative Hypothesis (Ha): There is a difference between the two sample 

proportions, Ha: PSB – PSA ≠ 0.

The Z-statistic used to determine the statistical difference between the two proportions is

computed using the equation shown in figure 24.

(73)

Figure 24. Equation. Z-statistic to determine the speed difference between a pair of before

and after periods.

Where PSB and PSA are the sample proportions from figure 23, n1 and n2 are sample sizes for the 

corresponding proportions being considered, and P is the combined proportion in both samples, 

computed using the equation shown in figure 25.

Figure 25. Equation. Combined proportion of vehicles speeding during the before and after 

data-collection periods.

Similar to the t-statistic, the Z-statistic is associated with a p-value. A p-value of 0.05 or less 

rejects the null hypothesis and concludes that the HFST is effective in reducing the number of 

vehicles exceeding the speed limit at the 95-percent confidence level.

The final speed performance metric considered in the present study is speed variance. A twosided F-test is used to compare the variances of vehicle operating speed in the before and after

periods. The F-test is computed using the equation shown in figure 26.

Figure 26. Equation. F-test to compare the speed variance in the before and after periods.

This equation has an F-distribution with (nB – 1) numerator degrees of freedom and (nA – 1) 

denominator degrees of freedom. When the computed F-test exceeds the critical value, the null 















 − +

− =

1 2

1 1 (1 )

n n

P P

P P

Z SB SA

B A

B A

n n

x x P

+

+ =

2

2

A

B

s

s

F =

40
hypothesis is rejected, and the conclusion is that the speed variance differs between the before

and after periods.

HFST ENCROACHMENT EVALUATION METHODOLOGY

The purpose of the encroachment evaluation was to determine whether the HFST changes the 

proportion of vehicles that cross either the edge line or centerline on two-lane rural highways in 

West Virginia. Because the HFST increases the coefficient of road adhesion, it was hypothesized 

that the proportion of lane-line encroachments would decrease. The following sections describe

the encroachment evaluation data collection and analysis.

Data-Collection Locations and Periods

Data collection took place at the same locations described above in the speed evaluation section. 

To identify lane-line encroachments, the research team deployed digital video recorders at all 

treatment and comparison site locations. A single recorder was positioned on the approach 

tangent, near the PC location, to record vehicles traversing the first half of the horizontal curve 

(PC to midpoint). Video data were recorded during daylight hours only in the before period (2 to 

4 h per collection period at each site), and during two after treatment periods. The first after

period occurred within the first month after applying the HFST to a horizontal curve, and the 

second after period occurred approximately 1 year after installing the HFST treatment. Data 

collection at the comparison sites occurred on the same days as the treatment site data collection. 

Analysis Methods

The research team collected the video data and reviewed it on a computer. The research team

then tabulated the total number of vehicles observed and the number of vehicles that crossed the 

edge line and the centerline of the roadway within the limits of the PC and midpoint of the 

horizontal curve. The proportion of vehicles encroaching on the edge line or centerline was then

computed using the equation shown in figure 27.

Figure 27. Equation Proportion of vehicles encroaching on the edge line or centerline.

Where:

Pe = proportion of vehicles encroaching on the edge line or centerline.

x = number of vehicles encroaching on the edge line or centerline.

n = number of vehicles observed during data-collection period.

To determine whether the proportion of vehicles encroaching on a lane line at the treatment and 

control locations changed between the before and after data-collection periods, the team 

computed a Z-test for independent samples. The null and alternative hypotheses for the test are

the following:

= ×100

n

x Pe

41
• Null Hypothesis (H0): There is no difference between the two sample proportions, or

H0: Pe(before) – Pe(after) = 0 

• Alternative Hypothesis (Ha): There is a difference between the two sample 

proportions, Ha: Pe(before) – Pe(after) ≠ 0.

The Z-statistic used to determine the statistical difference between the two proportions is shown 

in figure 28.

Figure 28. Equation. Z-statistic to determine the proportion of vehicles encroaching on a 

lane line during the before and after data-collection periods.

Where Pe(before) and Pe(after) are the sample proportions from figure 23, n1 and n2 are sample sizes 

for the corresponding proportions being considered, and P is the combined proportion in both 

samples, computed using the equation in figure 29.

Figure 29. Equation. Combined proportion of vehicles encroaching on a lane line between 

the before and after data-collection periods.

Similar to the t-statistic, the Z-statistic is associated with a p-value. A p-value of 0.05 or less 

rejected the null hypothesis and concluded that the HFST is effective in reducing the number of 

vehicles exceeding the speed limit at the 95-percent confidence level.

FRICTION EVALUATION METHODOLOGY

The research team also measured roadway surface friction before and after implementing HFST. 

The following is a discussion of the friction testing methods.

The research team used a dynamic friction (DF) tester to evaluate the skid resistance of the 

HFST and comparison site locations. All testing was performed in accordance with ASTM 

E1911-09a, Standard Test Method for Measuring Pavement Surface Frictional Properties Using 

the Dynamic Friction Tester. The DF tester measures the necessary torque to turn three small 

rubber pads in a circular path on the measured surface at different speeds. The apparatus consists 

of a horizontal spinning disk fitted with three spring-loaded rubber sliders that contact the paved 

surface as the disk rotational speed decreases because of the friction supplied between the sliders 

and the paved surface. A water supply unit delivers water to the paved surface being tested. The 

torque generated by the slider forces, measured during the spin down, is then used to calculate 

the friction supply as a function of speed. Typical test speeds range from 55 mph down to 3 mph. 

The device uses an electric motor to spin the measuring disc at the desired speed and an 

electromagnetic device to lower the spinning disk to the ground at the highest speed revolution. 















 − +

− =

1 2

( ) ( )

1 1 (1 )

n n

P P

P P

Z e before e after

before after

before after

n n

x x

P

+

+ =

42
The device is equipped with a rotational speed measurement device together with a rotational 

torque and a downward load measurement sensor. Figure 30 shows the DF tester.

Source: Pennsylvania State University

Figure 30. Photo. Dynamic friction tester.

The device is portable and was manually placed on the pavement surface where the test took

place. The research team used a laptop computer to control the test and record the data. Once the 

test was initiated, the electronic motor first accelerated the disk to the standard spinning speed of 

55 mph. The electromagnetic release mechanism then dropped the spinning disk to the ground, at 

which time automated data acquisition began. The test was completed when the disk came to a 

complete stop. The raw data were then filtered—the friction supply at the pavement-rubber disk 

interface was calculated from the measured and filtered torque and loading forces based on an 

internal algorithm within the testing apparatus. 

The team used a circular texture (CT) meter along with the DF tester to measure road surface 

texture characteristics. The meter is designed to measure surface texture on the same circular 

track as the DF tester. The CT meter calculates and reports the mean profile depth (MPD) of the 

road surface and the International Friction Index (IFI). 

The following describes the data-collection protocol with the number of measurements and the 

placement of measurements.

Data-Collection Protocol

The research team used the DF tester and CT meter to measure all treatment and control sites 

included in the speed study. A single before period, and two after periods were included in the 

data-collection process. These periods corresponded with the time periods described previously 

for the speed and encroachment data collection. The research team used the following testing 

protocol:

43
1. Each test section was divided into two segments as follows:

o The first segment was the last 300 ft (if available) of the approach tangent 

before the beginning of a horizontal curve. 

o The second segment was the entire length of the treated horizontal curve.

2. The first segment was divided into three equal 100-ft sectors. The research team used 

the DF tester and CT meter devices to measure the beginning and end point of these 

sectors. This yielded four total friction supply measurements on the approach tangent 

before the horizontal curve. It was assumed that this segment is where deceleration was 

most likely to occur and thus the texture and friction supply of the pavement surface 

was likely to vary on the approach tangent. The proposed measurements enabled the 

research team to determine this variability in friction supply. All friction supply 

measurements on the approach tangent were taken in the left wheel path. 

3. The second segment (i.e., horizontal curve) was similarly divided into three equal 

length sectors yielding four physical measurement locations. The intent of measuring 

friction supply at four locations within the horizontal curve was to provide information 

about the variability in friction supply within the limits of the curve. 

4. Each measurement location within a sector was defined as a 6-ft-long straight line. The 

research team again used the CT meter and DF tester devices to measure the beginning

and end points of the 6-ft-long line, producing two individual measurement points for 

each location. The research team computed the average of these measurements, which

served as the measured data for the locations.

5. Within each horizontal curve segment, the friction supply measurement locations were

determined as follows:

o On curves to the right, all measurements were recorded in the left wheel path 

because this location experiences more polishing and therefore supplies less 

friction than the right wheel path.

o On curves to the left, friction supply was measured in the right wheel path.

Analysis

The research team derived a representative friction supply curve for each test segment. The 

curves were plotted to illustrate the difference in friction supply before and after application of 

the HFST. Figure 31 shows a sample illustration of road friction curves produced using the 

measurement protocol described above. The research team used this analysis to determine the 

absolute change in friction supply at various locations approaching and along the horizontal 

curve at the treatment and control sites. 

44
Figure 31. Graph. Road friction curves (for illustrative purposes only).

In addition to the friction curves, the research team used the speed data collected during the 

speed study to compute the difference in friction supply and the friction demanded by vehicles 

traversing horizontal curves at the treatment and control locations. The friction demand was

computed using the point-mass model, using the equation shown in figure 32.

Figure 32. Equation. Side friction demand.

Where:

f = side friction demand.

V = vehicle operating speed (mph).

R = radius of horizontal curve (ft);

e = rate of superelevation (percent).

During the friction testing, the research team used a digital slope meter to measure the 

superelevation at the midpoint of each horizontal curve. The team then computed the descriptive 

statistics from the distributions of friction demand (e.g., mean, SD, 95th percentile) at each 

treatment and control curve location to the friction supply distribution. The margin of safety, 

ff = VV2

15RR − ee100

45
based on the difference between the distributions of friction supply and demand, was computed 

for each treatment and control location. 

BEFORE-PERIOD DATA SUMMARY

Speed, friction, and encroachment data were collected before implementing the HFST 

application at seven sites near Elkins, WV. Data were collected at four treatment sites and three 

comparison sites. One comparison site was located between two treatment sites on U.S. Route 

219, and was therefore used as a basis to compare the before and after operational performance 

at the two adjacent treatment sites. This section of the report describes the specific characteristics 

of each data-collection site, as well as the speed and other operational data-collection protocols 

employed at each site in the before period. This section of the report also provides results of the 

before analysis. 

West Virginia Route 32 Treatment Site (T1 in Table 6)

The direction of travel for speed data collection was from south to north (bottom left to top right 

in figure 33). There was a cut slope on the inside of the curve, which limited horizontal sight 

distance along the curve. The radius of curve and the curve length, calculated using Google 

EarthTM, were found to be 680.43 ft and 1,080 ft, respectively. The superelevation for this curve 

was 8.0 percent and the vertical grade was -0.5 percent, based on manual field measurements 

with a digital slope meter. The PSL was 55 mph. As figure 33 shows, there was a curve-to-theright warning sign (W1-2) with a 40-mph advisory speed plaque (W13-1P). The travel lanes 

were 10 ft wide, and there was a 4-ft paved shoulder on both sides

46
Figure 33. Diagram. Geometric layout of WV Route 32 treatment site (not to scale).

At this site, the research team collected data 300 ft before the PC, at the PC, and at the midpoint 

of the horizontal curve. A sensor was placed at the midcurve location in the opposing direction 

of travel to determine whether an opposing vehicle was present during data collection in the 

northbound travel lane. A camera was placed approximately at the PC to collect braking and 

encroachment data for 2 h during daylight. Braking data were only collected for the northbound 

traffic, while encroachment data were collected in both directions of travel. An intersection (WV 

Route 32/4) was located approximately 200 ft before the first sensor in the northbound direction 

of travel. Figure 33 shows a graphical layout of the horizontal curve along with the speed datacollection locations at the WV Route 32 treatment site.

47
Table 9 shows the speed data collected during the before period. The data are presented 

separately for passenger cars and heavy trucks, daytime and nighttime speeds for passenger cars, 

opposed (a vehicle present in the opposing lane) versus unopposed passenger cars, and free-flow 

versus non-free-flow passenger cars. All of these metrics are presented for the approach, PC, and 

midpoint of the horizontal curve locations. An independent sample t-test was performed to 

compare the mean speed and speed deviation for the disaggregate data comparisons shown in 

table 9. At the WV Route 32 treatment site, there was a statistically significant difference in 

mean speeds at the PC for passenger cars versus heavy vehicles and for opposed versus 

unopposed vehicles. As table 9 shows, there were only 9 heavy vehicles versus 289 passenger 

cars. There were 44 opposed vehicles versus 245 unopposed vehicles in the data-collection 

period. All other statistical comparisons were not statistically significant at the 95th percentile 

level (α = 0.05). This includes the comparison of daytime versus nighttime free-flow vehicle 

speeds and the comparison of free-flow versus non-free-flow vehicle speeds. The latter finding 

was expected because the traffic volumes were low at this treatment site. 

Table 9. WV Route 32 treatment site before data.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid

Speed

Mid 

SD N

Passenger cars 54.796 6.698 53.052 6.174 47.803 5.493 289

Heavy trucks 55.111 3.983 51.111 4.781 47.556 5.175 9

Daytime passenger cars 54.897 6.809 53.231 6.209 47.872 5.474 234

Nighttime passenger cars 54.364 6.246 52.291 6.021 47.509 5.614 55

Opposed passenger cars 53.886 5.735 50.614 6.300 47.455 5.214 44

Unopposed passenger cars 54.959 6.854 53.490 6.061 47.865 5.550 245

Free-flow passenger cars 54.976 6.955 53.172 6.316 47.948 5.557 250

Non-free-flow passenger cars 53.641 4.637 52.282 5.176 46.872 5.027 39

Bold indicates statistical significance at the 95-percent confidence level (α=0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 34 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along the WV Route 32 treatment section during the before period. As the figure 

shows, the truck and passenger car mean speeds are similar across the study section, but the 

heavy trucks appear to have a more constant deceleration from the approach to the midpoint of 

the curve. Passenger cars appear to maintain speed from the approach to the PC and then 

decelerate once into the curve. The mean acceleration rate from the PC to the midpoint of the 

curve was -1.15 ft/s (with a SD of 1.256) for passenger cars and -0.609 ft/s (0.833) for heavy 

trucks. A negative value indicates deceleration. 

48
Figure 34. Graph. Graphical representation of speeds at the WV Route 32 treatment site.

Friction data were collected at eight locations at this study site, as described in the Friction 

Evaluation Methodology section. Table 10 shows the data-collection locations and the 

measurements that were taken for pavement macro-texture and pavement micro-texture. The 

pavement macro-texture was measured using the CT meter in accordance with ASTM E2517 to 

establish the MPD in millimeters. The frictional micro-texture characteristic of the sample 

surfaces was measured with the DF tester device according to the ASTM E1911 standard. The 

two complementary devices allowed the research team to calculate the IFI friction indices and 

subsequently translate the IFI numbers into predicted locked wheel friction numbers (Skid 

Number (SN) 65). Table 10 shows the SN 65 values based on the macro- and micro-texture 

measurements.

Table 10. WV Route 32 treatment site friction data.

Location PC +300 PC + 200 PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 0.750 0.790 0.943 0.977 0.930 0.987 0.940 0.980

DFT 20 0.530 0.595 0.495 0.490 0.395 0.480 0.385 0.400

SN 65 0.410 0.460 0.400 0.390 0.320 0.380 0.310 0.320

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

As table 10 shows, the skid number at 40 mph is lower within the curve than before the curve, 

which was expected as a result of greater friction demand in the lateral direction when cornering. 

30

35

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

49
The research team collected encroachment data for 127 vehicles in the northbound direction and 

132 vehicles in the southbound direction. Seventeen vehicles encroached onto the shoulder, and 

no vehicles crossed the centerline of the road in the northbound direction. Twelve vehicles 

crossed the centerline and 6 vehicles encroached onto the shoulder in the southbound direction. 

Braking maneuvers were also observed for the northbound vehicles. Because the camera was 

located at the PC, only vehicles braking within the curve were observed. At this site, 35 of the 

127 vehicles were observed to brake within the curve for the northbound direction.

West Virginia Route 32 Comparison Site (C1 in Table 6)

Data were also collected at a comparison site approximately 1 mi south of the treatment site on 

WV Route 32 at the same time of the same day as the treatment site. The direction of travel was 

also south to north on a similar horizontal curve to the right. The radius of curve and the curve 

length, calculated using Google EarthTM, were found to be 1,073.3 ft and 1,213.6 ft, respectively. 

The superelevation for this curve was 7.0 percent, and the vertical grade was -3.5 percent, based 

on manual field measurements with a digital slope meter. There was a small slope on the inside 

of the curve that limited horizontal sight distance along the curve, and there was a driveway 

inside the curve, approximately at the quarter-point between the PC and the PT. The PSL was 

55 mph. As shown in figure 35, there was a reverse curve warning sign (W1-4) with a 50-mph

advisory speed plaque (W13-1P). The travel lanes were 10 ft wide, and there was a 4-ft shoulder 

on both sides.

Speed data were collected 300 ft before the PC, at the PC, and at the midpoint of the curve. The 

research team placed the sensor in the opposing direction of travel at the midpoint of the curve to 

determine whether vehicles were present in the opposing lane. The camera was placed upstream 

of the PC (approximately 100 ft) to observe braking before and into the curve for northbound 

vehicles. Figure 35 shows a graphical layout of the horizontal curve along with the speed datacollection locations.

50
Figure 35. Diagram. Geometric layout of the WV Route 32 comparison site (not to scale).

Table 11 shows the speed data for the before period. A simple t-test was computed to compare 

the operating speeds at each data-collection location. For this comparison site, there were no 

statistically significant differences in speed measures. 

51
Table 11. WV Route 32 comparison site before data.

Speed Metric Approach 

Speed

Approach 

SD

PC 

Speed PC SD Mid Speed Mid SD N

Passenger cars 57.530 6.357 54.793 6.293 52.345 7.148 232

Heavy trucks 56.917 2.644 52.75 4.515 50.000 4.880 12

Daytime passenger cars 57.926 6.068 54.886 5.912 52.737 7.301 175

Nighttime passenger cars 56.917 7.114 54.446 7.444 51.107 6.627 56

Opposed passenger cars 58.581 5.870 54.774 5.812 52.452 7.348 31

Unopposed passenger cars 57.368 6.427 54.796 6.378 52.328 7.135 201

Free-flow passenger cars 57.623 6.381 54.912 6.387 52.265 7.402 204

Non free-flow passenger cars 56.857 6.246 53.929 5.591 52.929 4.981 28

Bold indicates significance at the 95-percent confidence level (α=0.05)

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 36 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along the WV Route 32 comparison section during the before period. As shown, 

the truck and passenger car mean speeds are similar across the section, but the heavy truck mean 

speed is consistently about 2 mph less than the passenger car mean speed. The deceleration rates 

appear to be very similar. The dispersion of speed at the midpoint of the curve is much greater 

for passenger cars than at the other locations, which leads to the 85th percentile being relatively 

stable from the approach to the midpoint of the curve. The mean acceleration rate from the PC to 

the midpoint of the curve was -0.434 ft/s (1.38) for passenger cars and -0.615 ft/s (0.700) for 

heavy trucks.

Figure 36. Graph. Graphical representation of speeds at the WV Route 32 comparison site.

The research team also collected friction data at eight locations within the comparison site. 

Table 12 presents the macro-texture, micro-texture, and SNs at the horizontal curve and 

approach locations. SNs within the curve were lower those on the approach tangent, which was 

expected because of the lateral friction demand by drivers traversing horizontal curves. 

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

52
Table 12. WV Route 32 comparison site friction data.

Location PC +300 PC + 200 PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 0.727 0.830 0.790 0.980 0.873 0.870 1.560 1.037

DFT 20 0.480 0.515 0.500 0.450 0.445 0.450 0.395 0.525

SN 65 0.380 0.410 0.400 0.360 0.360 0.360 0.280 0.420

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

The research team collected encroachment data for 110 vehicles in the northbound direction and 

129 vehicles in the southbound direction. Two vehicles encroached onto the shoulder, and no 

vehicles crossed the centerline in the northbound direction. Six vehicles crossed the centerline,

and no vehicles encroached onto the shoulder in the southbound direction. Braking maneuvers 

were also observed for the northbound vehicles. Because the camera was located before the PC, 

vehicles braking before and within the curve were observed. At this site, 15 of the 110 vehicles 

were observed to brake before the curve and 10 of the 110 were observed to brake within the 

curve.

U.S. Route 33 Treatment Site (T2 in Table 6)

The second treatment site was located on U.S. Route 33 east of Harman, WV. The direction of 

travel for the data collection was in the eastbound direction. The radius of curve and the curve 

length, calculated using Google EarthTM, were 209.97 ft and 539.22 ft, respectively. The 

superelevation for this curve was 6.0 percent, and the vertical grade was -8.0 percent. There was 

a substantial slope on the inside of the curve, which limited horizontal sight distance along the 

curve. The PSL was 55 mph. As figure 37 shows, there is a reverse turn warning sign (W1-3)

with a 25 mph advisory speed plaque (W13-1P). The travel lanes were 11 ft wide, and there was 

a 4-ft shoulder on both sides.

Speed data were collected 300 ft before the PC, at the PC, and at the midpoint of the curve. The 

sensor was placed in the opposing direction of travel at the midpoint of the curve to determine 

whether vehicles were present in the opposing lane. In this case, there were two travel lanes in 

the westbound direction, and the sensor was placed in the left lane. The camera was placed 

upstream of the PC (approximately 200 ft) to allow for observation of braking before and into the 

curve for eastbound vehicles. Figure 37 shows the horizontal curve along with the speed datacollection locations. 

53
Figure 37. Diagram. Geometric layout of the U.S. Route 33 treatment site (not to scale).

Table 13 shows the speed data for the before period. The research team performed a simple t-test 

for each of these comparisons at each of the curve locations. Evaluation at this site showed

statistically significant differences between passenger car and heavy truck speeds at all three 

locations. The difference was approximately 13 mph at the approach and 3.5 mph at the midpoint 

of the curve. Daytime speeds exceeded nighttime speeds for all locations, but the difference was 

only statistically significant at the PC. The relationship between free-flow speeds and non-freeflow speeds was inconsistent, and the difference was statistically significant at the PC.

54
Table 13. U.S. Route 33 treatment site before data.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Passenger cars 47.413 6.675 39.120 5.855 31.982 4.705 276

Heavy trucks 34.265 8.497 32.118 5.536 28.441 7.153 34

Daytime passenger cars 47.715 6.725 39.729 5.647 32.113 4.383 221

Nighttime passenger cars 46.200 6.384 36.673 6.086 31.455 5.843 55

Opposed passenger cars 47.970 7.760 38.788 6.637 31.982 4.705 33

Unopposed passenger cars 47.337 6.528 39.165 5.754 28.441 7.153 243

Free-flow passenger cars 47.332 6.747 38.817 5.656 32.127 4.709 229

Non-free-flow passenger cars 47.809 6.368 40.596 6.609 31.277 4.675 47

Bold indicates significance at the 95-percent confidence level (α=0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 38 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along the U.S. Route 33 treatment section during the before period. As shown, 

the passenger car speeds decelerate substantially from the approach to the middle of the curve. 

The heavy truck mean speeds are more aligned with the 15th percentile passenger car speed, but 

there is less deceleration for heavy vehicles than passenger cars at this site. The truck speeds are 

consistent with the advisory speed of 25 mph at the midpoint of the curve. The mean acceleration 

rate from the PC to the midpoint of the curve was found to be -1.58 ft/s (0.817) for passenger 

cars and -1.075 ft/s (0.887) for heavy trucks.

Figure 38. Graph. Graphical representation of speeds at the U.S. Route 33 treatment site.

Table 14 shows the macro-texture, micro-texture, and SNs for the U.S. Route 33 treatment site 

across the eight data-collection locations. The data show no discernible pattern because the 

friction and texture levels are fairly constant throughout the site.

20

25

30

35

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

55
Table 14. U.S. Route 33 treatment site friction data.

Location PC +300 PC + 200 PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 0.703 1.137 0.937 0.877 0.910 0.717 1.060 0.703

DFT 20 0.415 0.435 0.425 0.505 0.405 0.390 0.405 0.460

SN 65 0.330 0.340 0.340 0.400 0.330 0.320 0.320 0.360

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

Encroachment data were collected for 122 vehicles in the eastbound direction and 130 vehicles 

in the westbound direction. Six vehicles encroached onto the shoulder, and 15 vehicles crossed 

the centerline in the eastbound direction. Two vehicles crossed the centerline, and one vehicle 

encroached onto the shoulder in the westbound direction. Because there were two travel lanes in 

the westbound direction, it was observed that 48 vehicles crossed or straddled the broken line

between the two lanes in the same direction. Braking maneuvers were also observed for the 

eastbound vehicles. Because the camera was located before the PC, vehicles braking before and 

within the curve were observed. At this site, 115 of the 122 vehicles were observed to brake 

before the curve, and 3 of the 122 vehicles were observed to brake within the curve.

U.S. Route 33 Comparison Site (C2 in Table 6)

Data for the U.S. Route 33 comparison were collected approximately 2 mi east of the treatment 

site. The direction of travel for the data collection was eastbound. The radius of curve and the 

curve length, calculated using Google EarthTM, were 264.83 ft and 693.60 ft, respectively. The 

superelevation for this curve was 8.5 percent, and the vertical grade was -7.5 percent. There was 

a substantial cut-slope on the inside of the curve that limited horizontal sight distance along the 

curve. The PSL was 55 mph. As figure 39 shows, there was a reverse turn warning sign (W1-3) 

with a 25-mph advisory speed plaque (W13-1P). The travel lanes were 11 ft wide, and there was 

a 4-ft shoulder on both sides.

Speed data were collected 100 ft before the PC (because of the proximity of an adjacent 

horizontal curve), at the PC, and at the midpoint of the curve. The sensor in the opposing 

direction of travel was placed at the midpoint of the curve to whether vehicles were present in 

the opposing lane. The camera was placed upstream of the PC (approximately 200 ft) to allow 

observation of braking before and into the curve for eastbound vehicles. Figure 39 shows the 

horizontal curve along with the speed data-collection locations. 

56
Figure 39. Diagram. Geometric layout of the U.S. Route 33 comparison site (not to scale).

Table 15 shows the speed data for the before period. The research team performed a simple t-test 

for each of the comparative measures at each of the curve locations. For this site, a statistically 

significant difference was found between passenger car and heavy truck speeds at all three 

locations. The difference was approximately 5.5 mph at the approach and PC locations, and 

2.5 mph at the midpoint of the curve. The daytime speeds were greater than the nighttime speeds 

at all three locations, but the difference was only statistically significant at the PC. The free-flow 

speeds were greater than the non-free-flow speeds at all locations, but the difference was not 

statistically significant at the midpoint of the curve.

57
Table 15. U.S. Route 33 comparison site before data.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Passenger cars 43.027 5.966 38.608 6.566 35.814 6.528 263

Heavy trucks 37.564 8.012 32.974 7.354 33.128 5.908 39

Daytime passenger cars 43.376 5.804 39.168 6.362 36.056 6.633 197

Nighttime passenger cars 41.985 6.360 36.939 6.926 35.091 6.196 66

Opposed passenger cars 43.377 6.404 38.434 7.680 35.547 6.444 53

Unopposed passenger cars 42.938 5.864 38.652 6.274 35.881 6.562 210

Free-flow passenger cars 43.404 5.866 39.207 6.289 35.914 6.528 208

Non-free-flow passenger cars 41.600 6.181 36.345 7.142 35.436 6.786 55

Bold indicates significance at the 95-percent confidence level (α=0.05).

SD = Standard Deviation

PC = Point of Curve

N = Number of Observations

Figure 40 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along the U.S. Route 33 comparison section during the before period. As was the 

case at the treatment site, the mean speed for passenger cars decreased across the study section at 

a greater rate than the heavy trucks. However, the mean heavy truck speed stabilized at about 

33 mph, which is 8 mph greater than the advisory speed. The 85th percentile speed for passenger 

cars was approximately the PSL (55 mph) at the approach and decreased to about 49 mph at the 

midpoint of the curve. The 15th percentile speed was approximately the advisory speed of 

25 mph at the midpoint of the curve. There does not appear to be a relationship between 

passenger car speeds and heavy truck speeds at this site. The mean acceleration rate from the PC 

to the midpoint of the curve was found to be -0.679 ft/s (1.664) for passenger cars and -0.262 ft/s 

(1.468) for heavy trucks.

Figure 40. Graph. Graphical representation of speeds at the U.S. Route 33 comparison site.

20

25

30

35

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

58
Table 16 shows the macro-texture, micro-texture, and SNs for the U.S. Route 33 comparison site

across the seven data-collection locations. It is clear from the data that both the macro-texture 

and micro-texture are very low at this site. This leads to a range of SNs from a low of 0.26 at the 

three-quarter point of the curve to a high of 0.34 at the PC. Similar to the treatment site, the 

comparison site is located on a very steep grade (approximately 8 percent). The steep grade 

creates the need for braking throughout the entire treatment and comparison sites, which is likely 

the reason that the pavement texture is consistent, but low, throughout the study site.

Table 16. U.S. Route 33 comparison site friction data.

Location PC + 200 PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 0.463 0.530 0.547 0.420 0.350 0.327 0.430

DFT 20 0.355 0.400 0.450 0.360 0.400 0.365 0.380

SN 65 0.28 0.31 0.34 0.28 0.28 0.26 0.29

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

The research team collected encroachment data for 89 vehicles in the eastbound direction and 92 

vehicles in the westbound direction. Four vehicles encroached onto the shoulder, and 10 vehicles 

crossed the centerline in the eastbound direction. Five vehicles crossed the centerline, and 12 

vehicles encroached onto the shoulder in the westbound direction. Braking maneuvers were also 

observed for the eastbound vehicles. Because the camera was located before the PC, vehicles 

braking before and within the curve were observed. At this site, 85 of the 89 vehicles were 

observed to brake before the curve, and 2 of the 89 vehicles were observed to brake within the 

curve.

U.S. Route 219 Treatment Site A—Mile Marker 6.32 (T3 in Table 6)

Data at treatment site A on U.S. Route 219 were collected in the northbound direction of travel. 

The radius of curve and the curve length, calculated using Google EarthTM, were 605.08 ft and 

753.82 ft, respectively. The superelevation for this curve was 11 percent, and the vertical grade 

was -2.0 percent. There was a roadside slope on the inside of the curve that limited horizontal 

sight distance along the curve. The PSL was 55 mph. As figure 41 shows, there was a warning 

sign (W1-2) of a curve to the right with a 30 mph advisory speed plaque (W13-1P). The travel 

lanes were 10 ft wide, and there was a 1-ft paved shoulder on both sides. 

Speed data were collected 300 ft before the PC, at the PC, and at the midpoint of the curve. The 

sensor in the opposing direction of travel was placed at the midpoint of the curve to determine 

whether vehicles were present in the opposing lane. The camera was placed upstream of the PC 

(approximately 200 ft) to allow observation of braking before and into the curve for northbound 

vehicles. Figure 41 shows a graphical layout of the horizontal curve along with the speed datacollection locations.

59
Figure 41. Diagram. Geometric layout of the U.S. Route 219 treatment A site (not to scale).

60
Table 17 presents the speed data for the before period. The research team completed a simple 

t-test for each of the speed measures at each of the curve locations. For this site, passenger car 

speeds were greater than the heavy truck speeds at all three locations. The difference was 

statistically significant at the approach location only. Daytime and nighttime speeds were 

statistically significant at the approach; however, there were only 14 vehicles observed in the 

nighttime period. At the approach and PC, the nighttime speeds were greater than the daytime 

speeds. The daytime speeds were greater (although insignificantly) that nighttime speeds at the 

midpoint of the curve. 

Table 17. U.S. Route 219 treatment A site before data.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Passenger cars 48.125 6.058 46.397 6.062 36.294 7.532 136

Heavy trucks 43.944 5.826 45.222 5.287 34.389 4.629 18

Daytime passenger cars 47.893 6.172 46.336 6.191 36.434 7.356 122

Nighttime passenger cars 50.143 4.655 46.929 4.953 35.071 9.144 14

Opposed passenger cars 46.889 6.615 46.167 6.947 37.667 9.172 18

Unopposed passenger cars 48.314 5.977 46.432 5.948 36.085 7.273 118

Free-flow passenger cars 48.383 6.059 46.600 6.039 36.565 7.542 115

Non-free-flow passenger cars 46.714 6.282 45.286 6.214 34.810 7.481 21

Bold indicates significance at the 95-percent confidence level (α=0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 42 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along U.S. Route 219 treatment site A during the before period. The figure shows 

that mean speeds for both heavy trucks and passenger cars remain relatively stable from the 

approach to the PC, but decrease substantially from the PC to the midpoint of the curve. At this 

site, it is clear that the mean speeds for both passenger cars and heavy trucks are similar across 

the study segment. The mean speeds are approximately 5 mph greater than the advisory speed of 

30 mph at the midpoint of the curve. It is also clear that the dispersion of speed decreases 

substantially within the horizontal curve. The mean acceleration rate from the PC to the midpoint 

of the horizontal curve was -3.178 ft/s (2.959) for passenger cars and -3.042 ft/s (2.811) for 

heavy trucks.

61
Figure 42. Graph. Graphical representation of speeds at the U.S. Route 219 treatment A 

site.

Table 18 shows the macro-texture, micro-texture, and SNs for the U.S. 219 treatment A site 

across the eight data-collection locations. From the table, it is clear that the mean profile depth is 

much greater across the entire site than the other data-collection sites. Greater mean-profile depth 

is associated with a lower SN. Conversely, the micro-texture friction is higher than most sites. 

The SN appears to be fairly constant from the approach throughout the horizontal curve. 

Table 18. U.S. Route 219 treatment A site friction data.

Location PC +300 PC + 200 PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 1.407 1.417 1.407 1.277 0.890 0.950 1.093 1.140

DFT 20 0.500 0.490 0.525 0.530 0.505 0.465 0.585 0.545

SN 65 0.380 0.370 0.360 0.400 0.360 0.380 0.370 0.400

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

Encroachment data were collected for 77 vehicles in the northbound direction and 92 vehicles in 

the southbound direction. Two vehicles encroached onto the shoulder, and no vehicles crossed 

the centerline in the northbound direction. Six vehicles crossed the centerline, and three vehicles 

encroached onto the shoulder in the southbound direction. Braking maneuvers were also 

observed for the northbound vehicles. Because the camera was located before the PC, vehicles 

braking before and within the curve were observed. At this site, 56 of the 77 vehicles were 

20

25

30

35

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

62
observed braking before the curve, and 12 of the 77 vehicles were observed braking within the 

curve.

U.S. Route 219 Treatment Site B―Mile Marker 5.81 (T4 in Table 6)

The research team also collected at a second treatment site along U.S. Route 219. The direction 

of travel for the data collection was northbound. The radius of curve and the curve length, 

calculated using Google EarthTM, were 272.85 ft and 673.42 ft, respectively. The superelevation 

for this curve was 12 percent, and the vertical grade was -3.0 percent. There was a roadside slope 

on the inside of the curve that limited horizontal sight distance along the curve. The travel lanes 

were 10.5 ft wide, and there was a 1-ft paved shoulder on both sides. The PSL is 55 mph. As 

Figure 44 shows, there was a warning sign (W1-2) of a curve to the right with a 25-mph advisory 

speed plaque (W13-1P).

Speed data were collected 300 ft before the PC, at the PC, and at the midpoint of the curve. The 

sensor in the opposing direction of travel was placed at the midpoint of the curve to determine 

whether vehicles were present in the opposing lane. The camera was placed upstream of the PC 

(approximately 200 ft) to observe braking before and into the curve for northbound vehicles.

Figure 43 shows the layout of the horizontal curve along with the speed data-collection locations.

63
Figure 43. Diagram. Geometric layout of the U.S. Route 219 treatment B site (not to scale).

64
Table 19 presents speed data for the before period. A simple t-test was computed for each of 

these comparisons at each of the curve locations. For this site, passenger car speeds were greater 

than the heavy truck speeds at all three locations. The difference was statistically significant at 

the PC only. The unopposed passenger car speeds were greater than the opposed passenger car 

speeds at all three locations. Free-flow speeds were statistically different than non-free-flow 

speeds at the PC only.

Table 19. U.S. Route 219 treatment B site before data.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Passenger cars 48.661 8.304 44.724 6.720 34.622 6.285 127

Heavy trucks 46.684 7.616 39.263 6.145 33.474 4.823 19

Daytime passenger cars 48.848 8.082 44.857 6.881 34.464 6.373 112

Nighttime passenger cars 47.267 10.018 43.733 5.457 35.800 5.647 15

Opposed passenger cars 46.769 5.085 44.615 4.445 33.154 4.616 13

Unopposed passenger cars 48.877 8.584 44.737 6.946 34.789 6.443 127

Free-flow passenger cars 48.413 8.647 45.298 6.914 34.712 6.406 104

Non-free-flow passenger cars 49.783 6.578 42.130 5.120 34.217 5.823 23

Bold indicates significance at the 95-percent confidence level (α=0.05).

SD = Standard Deviation

PC = Point of Curve

N = Number of Observations

Figure 44 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along U.S. Route 219 treatment site B during the before period. The figure shows 

that passenger cars decelerate at a much greater rate within the horizontal curve compared with

the approach to the horizontal curve. Heavy trucks appear to have a more constant deceleration 

from the approach to the midpoint of the horizontal curve, which explains the significant 

difference at the PC location. Mean speeds are about 7 mph less than the PSL at the approach 

and about 10 mph greater than the advisory speed at the midpoint of the horizontal curve. The 

15th percentile speed is approximately equal to the advisory speed at the midpoint of the 

horizontal curve. The mean acceleration rate from the PC to the midpoint of the curve was -

2.603 ft/s (2.064) for passenger cars and -1.645 ft/s (1.53) for heavy vehicles.

65
Figure 44. Graph. Graphical representation of speeds at the U.S. Route 219 treatment B 

site.

Table 20 shows the macro-texture, micro-texture, and SNs for the U.S. Route 219 treatment B 

site across the eight data-collection locations. Again, there is no discernible pattern of the SN

from the approach to the end of the site, but the SN is pretty high compared with many of the 

other sites. The mean-profile depth is small (ranging from 0.493 to 0.823), and the micro-texture 

friction is high (ranging from 0.465 to 0.585). 

Table 20. U.S. Route 219 treatment B site friction data.

Location PC +300 PC + 200 PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 0.493 0.493 0.647 0.680 0.823 0.570 0.643 0.573

DFT 20 0.535 0.560 0.525 0.530 0.505 0.465 0.585 0.545

SN 65 0.380 0.400 0.400 0.410 0.400 0.350 0.440 0.400

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

The research team collected encroachment data for 61 vehicles in the northbound direction and 

61 vehicles in the southbound direction. Ten vehicles encroached onto the shoulder, and 

10 vehicles crossed the centerline in the northbound direction. Twelve vehicles crossed the 

centerline, and 2 vehicles encroached onto the shoulder in the southbound direction. Braking 

maneuvers were also observed for the northbound vehicles. Because the camera was located 

before the PC, vehicles braking before and within the curve were observed. At this site, 31 of the 

61 vehicles were observed braking before the curve, and 20 of the 61 vehicles were observed 

braking within the curve.

20

25

30

35

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

66
U.S. Route 219 Comparison Site (C3/C4 in Table 6)

The U.S. Route 219 comparison site was located approximately 5 mi north of the two treatment 

sites on the same route. The direction of travel for the data collection was northbound. The curve 

radius and the curve length, calculated using Google EarthTM, were 544.57 ft and 826.91 ft, 

respectively. The superelevation for this curve was 12 percent, and the vertical grade was 

-6.5 percent. The PSL was 55 mph. As figure 45 shows, there was a reverse curve warning sign

(W1-4) with a 30-mph advisory speed plaque (W13-1P). The travel lanes were 11 ft wide, and 

there was no paved shoulder. 

Speed data were collected 100 ft before the PC (because of an adjacent horizontal curve), at the 

PC, and at the midpoint of the curve. The research team placed the sensor in the opposing 

direction of travel at the midpoint of the curve to determine whether vehicles were present in the 

opposing lane. The camera was placed at the PC to observe braking into the curve for 

northbound vehicles. Figure 45 shows a layout of the horizontal curve along with the speed datacollection locations.

Figure 45. Diagram. Geometric layout of the U.S. Route 219 comparison site (not to scale).

67
Table 21 presents the speed data for the before period. The research team computed a simple 

t-test for each of the speed measures at each of the curve locations. The passenger car speeds 

were greater than the heavy truck speeds at all three locations. This difference was statistically 

significant at all three locations, even with only 79 and 13 passenger car and truck speed 

observations, respectively. The daytime speeds were greater than the nighttime speeds at all three 

sites. This difference was not statistically significant at any site, likely owing to the small sample 

size. The opposed passenger car speeds were greater than the unopposed passenger car speeds at 

every site, and were statistically significant at the approach. The free-flow speeds were greater 

than the non-free-flow speeds at every site, but not statistically significant at any location.

Table 21. U.S. Route 219 comparison site before data.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Passenger cars 44.506 6.961 42.025 6.653 41.152 5.371 79

Heavy trucks 39.154 7.186 38.154 5.886 36.000 6.506 13

Daytime passenger cars 44.647 6.083 42.176 5.122 41.426 4.566 68

Nighttime passenger cars 43.634 11.360 41.091 12.973 39.455 9.038 11

Opposed passenger cars 46.000 4.219 43.273 5.442 42.909 5.594 11

Unopposed passenger cars 43.444 7.482 41.235 6.799 40.086 5.771 81

Free-flow passenger cars 44.714 7.051 42.100 6.740 41.157 5.468 70

Non free-flow passenger cars 42.889 6.353 41.444 6.267 41.111 4.833 9

Bold indicates significance at the 95-percent confidence level ( =0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 46 graphically shows the PSL, advisory speed limit, and the mean speeds for passenger 

cars and trucks along the U.S. Route 219 comparison site during the before period. The 

passenger car and heavy truck speeds remain fairly constant from the approach to the midpoint 

of the horizontal curve. This is likely because this horizontal curve is in the middle of several 

horizontal curves with no long tangent sections between. The mean passenger car speed was 

approximately 12 mph greater than the advisory speed, and the heavy truck speed was 

approximately 10 mph greater. The 85th percentile operating speed was approximately equal to 

the PSL (55 mph). The mean acceleration rate from the PC to the midpoint of the curve was 

-0.213 ft/s (1.201) for passenger cars and -0.157 ft/s (1.627) for heavy trucks.

α

68
Figure 46. Graph. Graphical representation of speeds at the U.S. Route 219 comparison 

site.

Table 22 shows the macro-texture, micro-texture, and SNs for the U.S. Route 219 comparison 

site across the six data-collection locations. As the table shows, the SN is quite low across the 

site and is somewhat uniform from the approach to the end of the horizontal curve. Again, the 

site is on a fairly substantial grade (about 6.5 percent downhill), which may contribute to 

increased longitudinal friction as a result of braking.

Table 22. U.S. Route 219 comparison site friction data.

Location PC + 100 PC 1/4 Mid 3/4 PT

CTM MPD 0.650 0.760 0.457 0.520 0.610 0.683

DFT 20 0.390 0.395 0.385 0.390 0.410 0.390

SN 65 0.310 0.320 0.290 0.300 0.330 0.320

CTM = Circular Texture Meter

MPD = Mean Profile Depth

DFT = Dynamic Friction Meter

SN = Skid Number

PC = Point of Curvature

PT = Point of Tangent

Encroachment data were collected for 49 vehicles in the northbound direction and 60 vehicles in 

the southbound direction. Eight vehicles encroached onto the shoulder, and no vehicles crossed 

the centerline in the northbound direction. Twenty vehicles crossed the centerline, and 3 vehicles 

encroached onto the shoulder in the southbound direction. Braking maneuvers were also 

observed for the northbound vehicles. Because the camera was located at the PC, vehicles 

braking maneuvers within the curve were observed. At this site, 47 of the 49 vehicles were 

observed to brake within the curve. 

20

25

30

35

40

45

50

55

60

Approach PC Midpoint

Speed (mph)

Location on Curve

Passenger Car Mean

Heavy Truck Mean

Speed Limit

Advisory Speed

69
COMPARISON OF BEFORE AND AFTER PERIOD DATA

The HFST was applied to the four treatment site locations in June 2012, and the research team 

observed speed, encroachment, and braking maneuvers in August 2012. The second after period 

data-collection effort was completed in June 2013, and included speed, encroachment, and 

braking maneuver field measurements and observation. This section of the report describes the 

differences found between the before and after conditions at the treatment sites, as well as the 

comparison sites. If significant differences were found from the before to after condition at the 

comparison sites, then those differences were considered in the analysis of the treatment sites. 

As described in the data collection and analysis methods section above, the research team 

excluded all vehicles that were not passenger cars and that were not considered free-flow 

vehicles from the analysis database. The data analysis files also included indicators for when 

vehicles were present opposite to the travel lane where the operational evaluation was being 

conducted. The mean speed, change in mean speed between the PC and midpoint of the curve, 

percentage of vehicles exceeding the PSL, encroachment, and friction analysis results are all 

included in this section of the report. 

Mean Operating Speed Results

West Virginia Route 32 (Treatment and Comparison Site)

Table 23 shows the before and after mean speeds and speed deviations for the treatment and 

comparison sites on WV Route 32. The table shows the values for both passenger cars and heavy 

trucks at the approach, PC, and curve midpoint. The mean and SDs are given for free-flow 

vehicles with no opposing vehicles in the opposite direction because very few vehicles were 

present in the opposing lane during the analysis period (see before data period data summary 

above) and because these mean speeds were seldom statistically different in the before period 

data analysis. Only daytime speeds were reported for comparison in the before and after periods

because too few nighttime observations were available or because passenger car and truck speeds

seldom varied in the before period analysis. As table 23 shows, there was no statistically 

significant change in speed measures for the comparison site from the before to the first after

period. However, significant reductions in speed were found at the PC and curve midpoints for 

passenger cars at the treatment site. In both cases, the reduction was approximately 1.5 mph. The 

midpoint speed was found to be significantly lower for heavy trucks, by approximately 8 mph, in 

the first after period when compared with the before period, but this was likely the result of the 

very small number of trucks included in the sample. When comparing the second after period to 

the first after period, the mean truck speeds increased to levels similar to the before period. 

There was a significant reduction in speed for passenger cars at the approach point in the second 

after period, when compared with the before period, at the treatment site. However, there was 

also a significant reduction at the approach point for the comparison site. When taking this 

reduction into account, the reduction in speed for the treatment site was no longer statistically 

significant. The mean speed of passenger cars at the PC and curve midpoint increased slightly in

the second after period, but they were still less than the before period. There was a 4.2-mph

reduction in truck speed at the approach of the treatment site, but this reduction did not continue 

through the curve. There was also a statistically significant increase in truck speeds at the curve 

midpoint in the second after period compared with the first. The increase was approximately 

70
6.9 mph, but the speed was still 1.3 mph lower than the before period. The truck speed at the 

midpoint during the first after period was low when compared with the before and second after

period, but there were 12 or fewer trucks in each observation period.

Table 23. Operating speeds at WV Route 32 sites before and after treatment.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Treatment PCs before 55.216 7.3 53.743 6.283 48.054 5.639 167

Treatment PCs 1st after 54.166 7.959 52.337 7.343 46.554 5.126 175

Treatment PCs 2nd after 53.111 8.447 52.849 6.645 47.633 7.212 199

Treatment trucks before 56.50 3.987 51.50 5.089 49.833 4.622 6

Treatment trucks after 55.125 3.227 50.50 5.855 41.625 4.658 8

Treatment trucks 2nd after 52.333 6.443 51.417 5.384 48.50 3.477 12

Comparison PCs before 57.839 6.04 55.04 6.046 52.758 7.617 124

Comparison PCs 1st after 57.443 5.317 54.584 5.057 52.227 5.587 185

Comparison PCs 2nd after 56.504 6.315 55.417 6.923 52.483 6.06 240

Comparison trucks before 56.429 2.992 53.857 2.734 49.429 3.823 7

Comparison trucks 1st after 57.889 8.023 52.556 5.94 50.667 5.148 9

Comparison trucks 2nd after 54.375 6.811 51.938 6.708 49.25 3.474 16

Bold indicates significance at the 95-percent confidence level ( =0.05) when comparing either after period to 

the before period. 

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods. 

Underline indicates that, when accounting for the speed change at the comparison site, the change in the speed at 

the treatment site was not statistically significant at the 95-percent confidence level ( = 0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 47 and figure 48 show graphical representations of the speed profiles for the WV 

Route 32 treatment and comparison sites, respectively. The general shape of the speed profiles 

for the three collection periods remained relatively similar. 

α

α

α

71
Figure 47. Graph. WV Route 32 treatment site operating speeds (PSL = 55 mph).

Figure 48. Graph. WV Route 32 comparison site operating speeds (PSL = 55 mph).

46

48

50

52

54

56

58

60

62

64

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

46

48

50

52

54

56

58

60

62

64

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

72
U.S. Route 33 (Treatment and Comparison Site)

Table 24 shows the before and after mean operating speeds for the treatment and comparison 

sites on U.S. Route 33. Again, there was no statistically significant change in mean speeds for 

both passenger cars and heavy trucks at the comparison from the before period to the first after

period. The difference in mean speed for passenger cars between the before treatment application 

and first after treatment application were statistically significant at all three data-collection 

points. This difference shows reduced speed from the before to the after period at the treatment 

location. The change was approximately 1.3 mph at the approach and PC locations, and 1.7 mph

at the midpoint of the curve. Passenger car speeds decreased by only 0.4 mph at the midpoint 

after considering passenger cars entered the curve by approximately 1.3 mph slower in the first 

after period. For heavy trucks, there was a statistically significant reduction in speed of 3.5 mph 

in the first after period at the PC. 

Table 24 shows that mean speed for passenger cars significantly increased at the approach point 

by approximately 2.5 mph in the second after period compared with the first after period at the 

treatment site. Although not significant, the speed increase was approximately 1.2 mph at the 

approach point from the before period to the second after period. The significant increase in 

speed in the second after period continued through the PC location, where the increase was 

approximately 1.8 mph relative to the before period and 3.1 mph relative to the first after period. 

Passenger car speeds were significantly reduced in the second after period when compared with

the before period at the comparison site, at the approach point and the PC, by approximately 

1.3 mph and 1.4 mph, respectively. This reduction in speeds at the comparison site increases the 

significance of the increase in speeds at the approach point and PC at the treatment site. 

Passenger car mean speeds were significantly lower at the curve midpoint by approximately 

2.2 mph, in the second after period, not taking into account the speed reduction at the 

comparison site. However, speeds were also significantly reduced at the midpoint of the 

comparison site by approximately 1.7 mph. When taking this reduction into account, the speed 

reduction at the curve midpoint of the treatment site was no longer statistically significant. As 

with the WV Route 32 site, the high-friction surface had no long-term effect on passenger car 

mean operating speeds at the curve midpoint of the U.S. Route 33 treatment site. However, there 

was a statistically significant speed reduction at both the PC and midpoint for trucks in the 

second after period.

73
Table 24. Operating speeds at U.S. Route 33 before and after treatment.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N

Treatment PCs before 47.608 6.538 39.544 5.346 32.367 4.571 158

Treatment PCs 1st after 46.301 7.512 38.245 5.771 30.614 3.791 163

Treatment PCs 2nd after 48.769 7.723 41.336 7.199 30.154 5.024 143

Treatment trucks before 34.158 7.762 32.368 3.7 27.263 4.188 19

Treatment trucks 1st after 33.50 11.329 28.833 8.855 27.167 4.967 24

Treatment trucks 2nd after 30.905 9.049 27.476 7.593 24.048 5.661 21

Comparison PCs before 43.661 5.812 39.347 6.318 36.169 6.786 118

Comparison PCs 1st after 42.865 5.372 38.361 5.055 35.459 6.086 133

Comparison PCs 2nd after 42.366 6.462 37.93 5.812 34.443 5.445 142

Comparison trucks before 39.214 5.409 35.286 5.045 32.00 5.698 14

Comparison trucks 1st after 36.621 8.918 32.897 8.461 31.517 7.41 29

Comparison trucks 2nd after 36.80 5.569 34.70 4.921 32.55 5.781 20

Bold indicates significance at the 95-percent confidence level ( =0.05) when comparing either after period to 

the before period. 

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after

periods. 

Underline indicates that, when accounting for the speed change at the comparison site, the change in the 

speed at the treatment site was not statistically significant at the 95 percent confidence level ( = 0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations

Figure 49 and figure 50 show graphical representations of the speed profiles for the U.S. 

Route 33 treatment and comparison sites, respectively. The general shape of the speed profiles 

for the three collection periods remained relatively similar. 

α

α

α

74
Figure 49. Graph. U.S. Route 33 treatment site operating speeds (PSL = 55 mph).

Figure 50. Graph. U.S. Route 33 comparison site operating speeds (PSL = 55 mph).

30

32

34

36

38

40

42

44

46

48

50

52

54

56

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

30

32

34

36

38

40

42

44

46

48

50

52

54

56

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

75
U.S. Route 219 (Treatment and Comparison Site)

Table 25 shows the mean speeds for passenger cars and heavy trucks for the treatment and 

comparison sites on U.S. Route 219. For these sites, there was a statistically significant increase 

in mean speed from the before period to the first after period at all three data-collection locations 

at the comparison site. This result was expected because the roadway was slightly damp in the 

before period. The data at the comparison site showed that approach and PC mean speeds 

increased by about 2.2 mph in the first after period relative to the before period. At the midcurve 

location, the mean speed increased by 2.7 mph when comparing the first after period with the 

before period. Without accounting for this change, the PC mean speed was significantly lower in 

the first after period relative to the before period at the MM 6.32 location, while the midpoint 

curve mean speed is significantly higher in the first after period relative to the before period. 

However, when taking the increase in speed at the comparison site into account, the speed 

increase at the curve midpoint of the first treatment site (MM 6.32) is no longer statistically 

significant. However, when accounting for the statistically significant reduction in the mean 

speed at the PC location, the PC mean speed reduction for passenger cars at the treatment site 

was approximately 4.8 mph, which was statistically significant. Passenger car speeds also 

increased, between the before period and first after period, at the second treatment site 

(MM 5.81), at the approach point and the midpoint of the curve. The speed increase was 

approximately 2.3 mph at both data-collection points. However, neither of these mean speed 

increases was statistically significant when considering the speed increases at the comparison 

site. 

There were statistically significant changes at all three data-collection points at the comparison 

site in the second after period for passenger cars. There was a statistically significant increase in 

mean speed at the approach point between the before and second after periods, which was 

approximately 3.7 mph. There was also a statistically significant reduction in speed at the PC 

when comparing the second after period with the before period. There was no significant 

difference in speed at the midpoint of the curve between the second after and before periods. 

However, there was a statistically significant reduction in speed at the PC and curve midpoint 

between the first and second after periods. The speed reductions were approximately 4.6 mph at 

the PC and 2.7 mph at the curve midpoint.

Table 25 shows a significant speed reduction at the PC of the first treatment site (MM 6.32) in 

the second after period. This significant reduction was approximately 4 mph when compared 

with the before period and 1.4 mph when compared with the first after period. There was also a 

statistically significant speed increase at the curve midpoint of approximately 5.7 mph when 

compared with the before period, and 1.6 mph when compared with the first after period. 

Passenger cars maintained their speed from the PC to the curve midpoint at the first treatment 

site (MM 6.32), which suggests drivers may realize they have more available friction in the 

curve and do not decelerate as much throughout the curve. This is the only treatment site where 

speeds significantly increased in the curve, after taking into account speed changes at the 

comparison site, but this change was large, at approximately 5.7 mph. There also was a 

significant speed reduction at the approach point of the second treatment site (MM 5.81). This 

significant reduction was approximately 4 mph when compared with the first after period, but 

this speed reduction was not statistically significant when compared with the before period. 

There was a statistically significant speed reduction at the curve midpoint of approximately 

76
3.4 mph when compared with the first after period, but again, this speed reduction was not 

significant when compared with the before period. This speed reduction was no longer 

statistically significant after accounting for the speed reduction at the comparison site.

There was no significant difference for heavy trucks from the before to first after period at the 

comparison site. There was a statistically significant increase in speed at the first treatment site 

(MM 6.32) at the curve midpoint of approximately 3.4 mph. However, the speed at the midpoint 

of the curve decreased in the second after period, and there was no significant change between 

the before period and second after period. The only significant change in truck speeds at this site 

in the second after period was at the PC, where there was a reduction of approximately 8.9 mph. 

Trucks then increased their mean speed by 0.6 mph to the curve midpoint, although this increase 

was not statistically significant. However, there were only five trucks in the second after period, 

which likely contributed to the large change in mean speed at the PC location. Of note, truck 

mean speeds at the comparison site in the second after period were significantly greater when 

compared with the before and first after periods. There was approximately a 12.6-mph increase 

at the approach, a 12.4-mph increase at the PC, and approximately a 13.2-mph increase at the 

curve midpoint. Trucks maintained relatively similar speeds throughout the three data-collection 

points in all three time periods at the comparison site, but the speeds were much greater in the 

second after periods. All three truck speeds (approach, PC, and curve midpoint) in the second 

after period were greater than passenger vehicles at the comparison site.

The only change in the second treatment site (MM 5.81) mean truck speed was between the first 

and second after periods, at the approach data-collection location. However, this reduction was 

not statistically significant when compared with the before period.

77
Table 25. Operating speeds at U.S. Route 219 before and after treatment.

Speed Metric

Approach 

Speed

Approach 

SD

PC 

Speed PC SD

Mid 

Speed

Mid 

SD N

Treatment 6.32 PCs before 48.221 6.282 46.465 6.135 36.291 7.221 86

Treatment 6.32 PCs 1st after 47.773 6.219 43.876 5.251 40.34 5.433 97

Treatment 6.32 PCs 2nd after 47.756 7.204 42.511 5.637 41.967 4.72 90

Treatment 6.32 trucks before 44.364 5.971 44.455 6.44 34.545 4.698 11

Treatment 6.32 trucks 1st after 45.063 5.118 40.75 6.017 37.938 5.092 16

Treatment 6.32 trucks 2nd after 42.00 7.517 35.6 5.413 36.20 4.919 5

Treatment 5.81 PCs before 48.696 8.825 45.544 7.412 34.797 6.728 79

Treatment 5.81 PCs 1st after 51.078 5.788 45.553 5.489 37.136 6.463 103

Treatment 5.81 PCs 2nd after 47.042 7.617 47.099 7.484 33.718 5.197 71

Treatment 5.81 trucks before 46.923 8.19 39.308 5.964 32.308 3.728 13

Treatment 5.81 trucks 1st after 50.566 3.395 40.667 4.444 32.778 4.466 9

Treatment 5.81 trucks 2nd after 46.00 2.828 44.5 7.778 31.50 4.95 2

Comparison PCs before 44.66 6.317 42.06 4.867 41.16 4.354 50

Comparison PCs 1st after 46.831 5.967 44.282 6.388 43.859 5.354 71

Comparison PCs 2nd after 48.363 7.915 39.682 11.257 41.122 5.802 11/41a

Comparison trucks before 41.429 8.08 40.286 5.908 39.857 4.1 7

Comparison trucks 1st after 39.143 10.04 38.143 8.591 37.857 7.925 7

Comparison trucks 2nd after 54.00 8.164 52.636 6.439 53.091 3.33 4/11b

a

Eleven observations at the approach point and 41 observations at the PC and midcurve. b

Four observations at the approach point and 11 observations at the PC and midcurve.

Bold indicates significance at the 95-percent confidence level ( =0.05) when comparing either after period 

with the before period. 

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods. 

Underline indicates that, when accounting for the speed change at the comparison site, the change in the speed 

at the treatment site was not statistically significant at the 95-percent confidence level ( =0.05).

SD = Standard Deviation

PC = Point of Curvature

N = Number of Observations 

Figure 51 through figure 53 show speed profiles for the U.S. Route 219 treatment and 

comparison sites. At the comparison site, the speed profiles show vehicles behaved in the same 

manner during the before and first after period, but in the second after period, vehicles had 

higher speeds at the approach point and then decelerated more aggressively to the PC, compared 

with the before and first after period. In the second after period, vehicles actually accelerated 

slightly from the PC to the curve midpoint, at the comparison site. At the first treatment site 

(MM 6.32), passenger cars had higher speeds at the approach point and PC, when compared with

both after periods, but then they decelerated more aggressively from the PC to the curve 

midpoint and had a significantly lower speed at the curve midpoint compared with the after 

periods. Vehicles behaved relatively similarly between the two after periods, except the 85th

percentile speed at the PC in the second after period was 2 mph less than in the first after period 

and 3 mph less than in the before period. At the second treatment site (MM 5.81), passenger cars 

behaved relatively similarly in the before and first after period. However, in the second after

period, vehicles had slower speeds at the approach point and then slightly higher speeds at the 

PC; then they decelerated more aggressively to the curve midpoint and were traveling a at slower 

speed at the curve midpoint. This suggests drivers may be misjudging the curve, causing them to 

α

α

α

78
enter the curve at an excessive speed, and as they realized the tight geometry, causing them to 

brake harder in the curve.

Figure 51. Graph. U.S. Route 219 treatment site A (MM 6.32) operating speeds

(PSL = 55 mph).

Figure 52. Graph. U.S. Route 219 treatment site B (MM 5.81) operating speeds

(PSL=55 mph).

33

35

37

39

41

43

45

47

49

51

53

55

57

59

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

33

35

37

39

41

43

45

47

49

51

53

55

57

59

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

79
Figure 53. Graph. U.S. Route 219 comparison site operating speeds (PSL = 55 mph).

Mean Operating Speed Summary

In summary, the research team compared the mean operating speed for passenger cars and trucks 

before and at two different time periods after installing the HFST at four treatment and three

comparison sites in West Virginia. The mean speeds were compared during the three datacollection time periods at a location on the approach tangent, curve PC location, and the 

midpoint of the horizontal curve. The analysis included only daytime and unopposed free-flow 

vehicle mean speeds. 

The results of the mean speed analysis indicate that the HFST did not significantly affect vehicle 

mean operating speeds in a consistent manner across all four treatment sites. Few of the 

independent sample t-tests showed that the mean passenger car and heavy truck operating speeds 

differed between the before and first or second after periods at the treatment sites. A multifactor

analysis of variance (ANOVA) found that the data collection-time period–treatment site 

interaction was not statistically significant (F2, 4160 = 0.49, p > 0.05) at the approach speed 

location, when including observations of free-flow vehicles only and controlling for the presence 

of vehicles in the opposing lane, time of day, and vehicle type. Similar results were found at the 

PC (F2,4160 = 1.51, p > 0.05) and midcurve locations (F2, 4160 = 0.56, p > 0.05).

Change in Mean Operating Speed 

The next measure considered in the analysis was the change in speed from the PC to the 

midpoint of the horizontal curve (hereafter referred to as delta speed). This measure was 

observed in the before and both after periods at each of the treatment and comparison sites. As 

discussed previously, researchers used a t-test for independent samples to compare the two after 

periods with the before period and to compare the two after periods with one another. Table 26

39

41

43

45

47

49

51

53

55

57

59

Approach PC Midcurve

Speed (mph)

Location on Curve

Passenger Car Operating Speeds

Before Period Mean

First After Period Mean

Speed

Second After Period

Mean Speed

Before Period 85th

Percentile Speed

First After Period 85th

Percentile Speed

Second After Period 85th

Percentile Speed

80
shows the change in speed (delta speed) from the entry of the curve to the midpoint of the curve. 

The positive value of delta speed indicates that a mean decrease in speed occurred from the PC 

to the midpoint of the curve. A negative value represents a mean increase in speed between the 

two locations. As expected, few locations demonstrated a mean increase in speed from the PC to 

midcurve location.

81
Table 26. Change in speed from PC to curve midpoint.

Speed Metric Delta Speed Standard Deviation N

U.S. Route 219 Treatment 6.32 PCs before 10.174 8.896 86

U.S. Route 219 Treatment 6.32 PCs 1st after 3.536 5.629 97

U.S. Route 219 Treatment 6.32 PCs 2nd after 0.544 4.913 90

U.S. Route 219 Treatment 6.32 trucks before 9.909 9.016 11

U.S. Route 219 Treatment 6.32 trucks 1st after 2.813 4.004 16

U.S. Route 219 Treatment 6.32 trucks 2nd after -0.6 3.715 5

U.S. Route 219 Treatment 5.81 PCs before 10.747 7.923 79

U.S. Route 219 Treatment 5.81 PCs 1st after 8.417 7.239 103

U.S. Route 219 Treatment 5.81 PCs 2nd after 13.38 6.779 71

U.S. Route 219 Treatment 5.81 trucks before 7 7.165 13

U.S. Route 219 Treatment 5.81 trucks 1st after 7.889 1.691 9

U.S. Route 219 Treatment 5.81 trucks 2nd after 13 2.828 2

U.S. Route 219 Comparison PCs before 0.9 4.586 50

U.S. Route 219 Comparison PCs 1st after 0.423 5.008 71

U.S. Route 219 Comparison PCs 2nd after -1.439 9.859 41

U.S. Route 219 Comparison trucks before 0.429 7.231 7

U.S. Route 219 Comparison trucks 1st after 0.286 1.976 7

U.S. Route 219 Comparison trucks 2nd after -0.455 8.067 11

U.S. Route 33 Treatment PCs before 7.177 5.367 158

U.S. Route 33 Treatment PCs 1st after 7.632 4.953 163

U.S. Route 33 Treatment PCs 2nd after 11.182 7.653 143

U.S. Route 33 Treatment trucks before 5.105 3.71 19

U.S. Route 33 Treatment trucks 1st after 1.667 6.391 24

U.S. Route 33 Treatment trucks 2nd after 3.429 6.25 21

U.S. Route 33 Comparison PCs before 3.178 8.494 118

U.S. Route 33 Comparison PCs 1st after 2.902 6.393 133

U.S. Route 33 Comparison PCs 2nd after 3.486 5.312 142

U.S. Route 33 Comparison trucks before 3.286 8.09 14

U.S. Route 33 Comparison trucks 1st after 1.379 5.551 29

U.S. Route 33 Comparison trucks 2nd after 2.15 2.925 20

WV Route 32 Treatment PCs before 5.689 5.856 167

WV Route 32 Treatment PCs 1st after 5.783 7.091 175

WV Route 32 Treatment PCs 2nd after 5.216 7.072 199

WV Route 32 Treatment trucks before 1.667 4.179 6

WV Route 32 Treatment trucks 1st after 8.875 3.758 8

WV Route 32 Treatment trucks 2nd after 2.917 6.007 12

WV Route 32 Comparison PCs before 2.282 7.139 124

WV Route 32 Comparison PCs 1st after 2.357 4.548 185

WV Route 32 Comparison PCs 2nd after 2.933 4.97 240

WV Route 32 Comparison trucks before 4.429 4.117 7

WV Route 32 Comparison trucks 1st after 1.889 4.197 9

WV Route 32 Comparison trucks 1st after 2.688 5.474 16

Bold indicates significance at 95 percent confidence level ( =0.05) when comparing either after period with

the before period. 

Italics indicates significance at 95-percent confidence level ( =0.05) between the 1st and 2nd after periods.

N = Number of Observations

α

α

82
As table 26 shows, there was no statistically significant change in delta speed at any of the 

comparison locations for either passenger cars or heavy trucks. The only changes that occurred 

for passenger cars in the first after period were at the U.S. Route 219 treatment sites. In both 

cases, the delta speed was reduced (more constant speeds from the approach to the midpoint of 

the curve). Speeds became even more constant between the PC and midcurve in the second after 

treatment period at the first treatment site (MM 6.32) of U.S. Route 219, with less than a 1-mph 

change between the PC and curve midpoint. There was also a change at the second treatment site 

(MM 5.81) in the second after period; however, this change was an increase in delta speed of 

approximately 2.6 mph from the before period. This increase in delta speed is probably 

associated with passenger vehicles entering the curve at a higher speed in the second after period 

relative to the before period, and then realizing they are travelling too fast for the curve. There 

was also an increase in delta speed at the U.S. 33 treatment site in the second after period. The 

change was approximately 4 mph relative to the before period. 

A statistically significant change was found for heavy trucks at three out of the four treatment 

sites in the first after period. The delta speed was significantly reduced at two sites (by 7.1 mph 

and 3.5 mph). One treatment site showed a significant increase in delta speed (7.2 mph) from the 

before to the first after period; however, it is noted that there were only six heavy vehicles in the 

before period and eight heavy vehicles in the after period. The very low SD in both cases for this 

site shows that outliers are not driving these results. However, delta speed was reduced by 6 mph 

from the first after period to the second after period, and was 1.3 mph greater than in the before 

period. The site with the 7.1 mph reduction in delta speed in the first after period also had a 

3.4 mph reduction from the first after period to the second after period. Delta speed actually 

became slightly negative at this site, representing an increase in speed from the PC to the curve 

midpoint.

There is no consistent trend in the difference between passenger car speeds at the PC and curve 

midpoint from the before to the second after period as a result of the HFST. There was a 

significant increase in the difference at two treatment sites, but there was also a very significant 

decrease in the difference at another treatment site. The site (U.S. Route 219 Treatment 6.32) 

with the decrease in delta speed for passenger cars also had a statistically significant decrease in 

delta speed for trucks. A multifactor ANOVA found that the treatment site-time period 

interaction was not statistically significant (F2, 4160 = 0.51, p > 0.05) when including observations 

of free-flow vehicles only and controlling for the presence of vehicles in the opposing lane, time 

of day, and vehicle type. This suggests that the HFST did not affect the change in vehicle speeds 

between the PC and midcurve locations in the current study.

Vehicles Exceeding Posted Speed Limit

Finally, in addition to the t-test, the percentage of vehicles exceeding the PSL and the advisory 

speed at the treatment and control sites was calculated and compared between data-collection 

periods. The following describes the results of the data analysis. 

Table 27 shows the number of passenger cars and heavy trucks observed to exceed the speed 

limit at each location of every site in the before and both after periods. A test of proportions was 

used to determine whether the proportion of speeding vehicles changed at each location of every 

site from the before to after treatment application. From table 27, there were no visible trends 

83
from the before period to after treatment application. In the first after period, there was only a 

significant change in the number of passenger vehicles exceeding the speed limit at the first 

treatment site of U.S. Route 219 (MM 6.32), where the proportion of vehicles exceeding the 

speed limit at the PC was lower relative to the before period. Four vehicles exceeded the speed 

limit in the before period, and no vehicles exceeded the speed limit in the first and second after 

periods. This change was also significant in the second after period. There was one additional 

site in the second after period that had a significant reduction in the number of vehicles 

exceeding the speed limit. At the WV Route 32 treatment site, the proportion was reduced from 

0.50 to 0.39 at the approach point. There were also a few locations where there was a significant 

difference between the two after periods, but not the before period, which resulted from a slight 

reduction in the first after period that was not statistically significant. The only statistically 

significant change at the curve midpoint was at the WV Route 32 comparison site, where the 

proportion of trucks exceeding the speed limit significantly increased in the first after period, but 

then the proportion decreased in the second after period and was no longer significant. This 

result is noteworthy, however, because the U.S. Route 219 and U.S. Route 33 sites had such 

restrictive geometry that few vehicles traveled in excess of the PSL.

84
Table 27. Number of vehicles exceeding the PSL by site.

Data-Collection 

Location and Time 

Period

Speed Observation Site

U.S. Route 219 U.S. Route 33 WV Route 32

Treat. A

(MM

6.32)

Treat. B 

(MM

5.81) Comp. Treat. Comp. Treat. Comp.

Approach 

passenger 

cars

Before 6 (7%) 15 (19%) 3 (6%) 15 (9%) 1 (1%) 83 (50%) 82 (66%)

1st After 10 (10%) 23 (22%) 5 (7%) 12 (7%) 3 (2%) 75 (43%) 121 (65%)

2nd After 12 (13%) 8 (11%) 1 (9%) 21 (15%) 3 (2%) 77 (39%) 143 (60%)

Approach 

trucks

Before 1 (9%) 2 (15%) 1 (14%) 0 (0%) 0 (0%) 4 (67%) 5 (71%)

1st After 1 (6%) 1 (11%) 0 (0%) 0 (0%) 0 (0%) 5 (63%) 5 (56%)

2nd After 0 (0%) 0 (0%) 2 (50%) 0 (0%) 0 (0%) 4 (33%) 5 31%)

PC 

passenger 

cars

Before 4 (5%) 5 (6%) 0 (0%) 0 (0%) 1 (1%) 63 (38%) 60 (48%)

1st After 0 (0%) 2 (2%) 3 (4%) 3 (2%) 0 (0%) 52 (30%) 81 (44%)

2nd After 0 (0%) 8 (11%) 3 (7%) 2 (1%) 0 (0%) 62 (31%) 125 (52%)

PC trucks

Before 1 (9%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 2 (33%) 1 (14%)

1st After 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 2 (25%) 3 (33%)

2nd After 0 (0%) 0 (0%) 4 (36%) 0 (0%) 0 (0%) 3 (25%) 5 (31%)

Midcurve 

passenger 

cars

Before 1 (1%) 1 (1%) 0 (0%) 0 (0%) 2 (2%) 12 (7%) 45 (36%)

1st After 1 (1%) 2 (2%) 0 (0%) 0 (0%) 0 (0%) 5 (3%) 48 (26%)

2nd After 1 (1%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 18 (9%) 74 (31%)

Midcurve 

trucks

Before 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)

1st After 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 3 (33%)

2nd After 0 (0%) 0 (0%) 2 (18%) 0 (0%) 0 (0%) 0 (0%) 1 (6%)

Number 

of 

passenger 

cars

Before 86 79 50 158 118 167 124

1st After 97 103 71 163 133 175 185

2nd After 90 71 11/41a 143 142 199 240

Number 

of trucks

Before 11 13 7 19 14 6 7

1st After 16 9 7 24 29 8 9

2nd After 5 2 4/11b 21 20 12 16 a

Eleven observations at the approach point and 41 observations at the PC and midcurve. b

Four observations at the approach point and 11 observations at the PC and midcurve. 

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period.

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods.

Treat. = Treatment

MM = Mile Marker

Comp. = Comparison

PC = Point of Curvature

Table 28 shows the number of vehicles exceeding the advisory speed at the midpoint of the curve 

for each study site. The research team considered only the midpoint location because the 

advisory speed is for the horizontal curve, and the approach and PC locations are not within the 

curve. No significant changes were observed at the comparison sites from the before to the first 

after period. The proportion of passenger cars exceeding the advisory speed was significantly 

higher at the U.S. Route 219 treatment A (MM 6.32) site, but there was no change at any other 

site in the first after period. This increase continued into the second after period, where all but 

one vehicle exceeded the advisory speed. The proportion of heavy trucks exceeding the advisory 

speed was significantly lower at the WV Route 32 site in the first after period, but there was no 

change at any other site. This reduction did not continue into the second after period and the 

α

α

85
proportion of trucks exceeding the advisory speed was 100 percent, which is the same as in the 

before period. In the second after period at the U.S. Route 219 treatment B (MM 5.81) site, there 

was a significant decrease in the proportion of vehicles exceeding the advisory speed when 

compared with the before and first after periods. At this same site, the proportion of trucks 

exceeding the advisory speed was also significantly reduced when compared with the before and 

first after periods. There was also a significant reduction at the U.S. Route 219 comparison site 

between the first after period and second after period. This reduction was less significant than at 

the treatment B site. The proportion of vehicles decreased by 0.08 compared with the before 

period at the comparison site and 0.19 at the treatment site B. The proportion of passenger cars 

exceeding the advisory speed increased at one treatment site, decreased at another treatment site, 

and remained the same at the other two. These results indicate there might be a slight reduction 

in the number of trucks exceeding the advisory speed, but there does not appear to be a strong 

effect on the number of passenger vehicles exceeding the advisory speed at the HFST locations.

Table 28. Number of vehicles exceeding the advisory speed by site.

Data-Collection 

Location and Time 

Period

Speed Observation Site

U.S. Route 219 U.S. Route 33 WV Route 32

Treat. A

(MM

6.32)

Treat. B 

(MM

5.81) Comp. Treat. Comp. Treat. Comp.

Midcurve 

passenger

cars

Before 74 (86%) 75 (95%) 49 (98%) 148 (94%) 111 (94%) 154 (92%) 80 (65%)

1st After 94 (97%) 100 (97%) 70 (99%) 148 (91%) 124 (93%) 159 (91%) 112 (61%)

2nd After 89 (99%) 54 (76%) 37 (90%) 129 (90%) 134 (94%) 177 (89%) 155 (65%)

Midcurve 

trucks

Before 8 (73%) 13 (100%) 7 (100%) 13 (68%) 12 (86%) 6 (100%) 3 (43%)

1st After 15 (94%) 9 (100%) 5 (71%) 16 (67%) 22 (76%) 4 (50%) 4 (44%)

2nd After 4 (80%) 1 (50%) 11 (100%) 9 (43%) 19 (95%) 12 (100%) 6 (38%)

Number 

of 

passenger 

cars

Before 86 79 50 158 118 167 124

1st After 97 103 71 163 133 175 185

2nd After 90 71 41 143 142 199 240

Number 

of trucks

Before 11 13 7 19 14 6 7

1st After 16 9 7 24 29 8 9

2nd After 5 2 11 21 20 12 16

Bold indicates significance at the 95-percent confidence level (α=0.05) between the 1st or 2nd after periods and the 

before period.

Italics indicates significance at 95 percent confidence level (α=0.05) between the 1st and 2nd after periods.

Treat. = Treatment

MM = Mile Marker

Comp. = Comparison

PC = Point of Curvature

Speed Variance Analysis

Speed variance was the final speed performance metric considered in the current study. A twosided F-test was used to compare the variance of vehicle operating speed in the before and after

periods for passenger cars and heavy trucks.

Table 29 shows that the only change that occurred for the U.S. Route 219 comparison site in the 

first after period was at the PC for passenger cars. There was an approximate 1.5-mph increase in 

speed deviation at this location. Taking this change into account, the speed deviation was found 

86
to decrease at the PC locations for both treatment sites. There was also a significant decrease at 

the approach location for treatment site B for both passenger cars and heavy trucks, as well as at 

the midpoint of the curve at treatment site A for passenger cars. For the U.S. Route 219 

comparison site, there was an increase in speed deviation at the PC and curve midpoint in the 

second after period compared with the before period. There was an approximate 6.4-mph

increase in speed deviation at the PC and an approximate 1.5-mph increase at the curve 

midpoint. Taking these changes into account, there was a decrease in speed deviation at the PC 

and curve midpoint for both treatment sites. There was only a significant decrease between the 

first and second after period for trucks at the midpoint of the curve of the comparison site. 

However, there was no change between the before and second after period. There was also no 

change in speed deviation at any data-collection point for trucks at the two treatment sites.

When comparing the first after period with the before period for U.S. Route 33 comparison site, 

the speed deviation decreased by 1.3 mph at the PC for passenger cars and increased by 

approximately 3.5 mph at the approach and PC for heavy trucks. Taking these trends into 

account, a significant increase in speed deviation occurred at the approach and PC for passenger 

cars, while a significant decrease occurred at the midpoint of the horizontal curve. For heavy 

trucks, a significant increase occurred only at the PC (approximately 2.7 mph). At the 

comparison site, the speed deviation decreased by approximately 1.3 mph at the curve midpoint 

for passenger cars. There was also a statistically significant increase at the approach for 

passenger cars, but this was only between the first and second after periods. Taking these trends

into account, a significant increase in speed deviation occurred at the curve midpoint for 

passenger cars in the second after period. At the comparison site, there was no statistically 

significant change in speed deviation between the before and second after period for trucks. 

There was a statistically significant decrease at the approach and PC location for trucks between 

the first and second after periods. The speed deviation increased by approximately 3.9 mph at the 

PC for trucks from the before to second after period at the treatment site. 

For WV Route 32, there were statistically significant decreases at the PC and the midpoint of the 

curve for passenger cars and significant increases at the approach and PC for heavy trucks at the 

comparison site in the first after period. Taking these differences into account resulted in 

statistically significant increases in speed deviation at the PC and midpoint for passenger cars, 

and significant decreases for heavy trucks at the approach and PC for heavy trucks at the 

treatment site. In the second after period, there was a significant increase in speed deviation at 

the PC and a significant decrease at the curve midpoint for the comparison site for passenger 

cars. Taking these differences into account, there was a significant increase in speed deviation at 

the approach and curve midpoint of the treatment site for passenger cars in the second after

period. There was also a significant increase in speed deviation at the approach and PC for trucks 

at the comparison site. Taking these differences into account, there was a significant decrease in 

speed deviation at the approach and PC for the treatment site for trucks in the second after

period.

There was no consistent trend in the effects of the HFST on the speed deviation of passenger 

cars. The effects of the HFST on the speed deviation were considered for the PC and curve 

midpoint locations because the surface was applied starting at the PC, or just before it, and it was

assumed that the surface would have no effect on the speed deviation at the approach datacollection location. In the first after period, the speed deviation increased at the PC for two sites, 

87
but the speed deviation also decreased at two other sites. In the second after period, the speed 

deviation decreased at the PC for two sites. In the first after period, the speed deviation increased 

at the curve midpoint at one site, but the speed deviation decreased at another site. In the second 

after period, the speed deviation increased at the curve midpoint for two sites, but the speed 

deviation also decreased at two sites. For trucks, the speed deviation decreased at the PC at one 

site in both after periods, and it also decreased at one site in both after periods. There was no 

change in speed deviation at the curve midpoint for trucks at any site. 

Table 29. Change in standard deviation of speed.

Speed Metric Approach SD PC SD Mid SD N

U.S. Route 219 Treatment 6.32 PCs before 6.282 6.135 7.221 86

U.S. Route 219 Treatment 6.32 PCs 1st after 6.219 5.251 5.433 97

U.S. Route 219 Treatment 6.32 PCs 2nd after 7.204 5.637 4.72 90

U.S. Route 219 Treatment 6.32 trucks before 5.971 6.44 4.698 11

U.S. Route 219 Treatment 6.32 trucks 1st after 5.118 6.017 5.092 16

U.S. Route 219 Treatment 6.32 trucks 2nd after 7.517 5.413 4.919 5

U.S. Route 219 Treatment 5.81 PCs before 8.825 7.412 6.728 79

U.S. Route 219 Treatment 5.81 PCs 1st after 5.788 5.489 6.463 103

U.S. Route 219 Treatment 5.81 PCs 2nd after 7.617 7.484 5.197 71

U.S. Route 219 Treatment 5.81 trucks before 8.19 5.964 3.728 13

U.S. Route 219 Treatment 5.81 trucks 1st after 3.395 4.444 4.466 9

U.S. Route 219 Treatment 5.81 trucks 2nd after 2.828 7.778 4.95 2

U.S. Route 219 Comparison PCs before 6.317 4.867 4.354 50

U.S. Route 219 Comparison PCs 1st after 5.967 6.388 5.354 71

U.S. Route 219 Comparison PCs 2nd after 7.915 11.257 5.802 11/41a

U.S. Route 219 Comparison trucks before 8.08 5.908 4.10 7

U.S. Route 219 Comparison trucks 1st after 10.04 8.591 7.925 7

U.S. Route 219 Comparison trucks 2nd after 8.164 6.439 3.33 4/11b

U.S. Route 33 Treatment PCs before 6.538 5.346 4.571 158

U.S. Route 33 Treatment PCs 1st after 7.512 5.771 3.791 163

U.S. Route 33 Treatment PCs 2nd after 7.723 7.199 5.024 143

U.S. Route 33 Treatment trucks before 7.762 3.7 4.188 19

U.S. Route 33 Treatment trucks 1st after 11.329 8.855 4.967 24

U.S. Route 33 Treatment trucks 2nd after 9.049 7.593 5.661 21

U.S. Route 33 Comparison PCs before 5.812 6.318 6.786 118

U.S. Route 33 Comparison PCs 1st after 5.372 5.055 6.086 133

U.S. Route 33 Comparison PCs 2nd after 6.462 5.812 5.445 142

U.S. Route 33 Comparison trucks before 5.409 5.045 5.698 14

U.S. Route 33 Comparison trucks 1st after 8.918 8.461 7.41 29

U.S. Route 33 Comparison trucks 2nd after 5.569 4.921 5.781 20

WV Route 32 Treatment PCs before 7.3 6.283 5.639 167

WV Route 32 Treatment PCs 1st after 7.959 7.343 5.126 175

WV Route 32 Treatment PCs 2nd after 8.447 6.645 7.212 199

WV Route 32 Treatment trucks before 3.987 5.089 4.622 6

WV Route 32 Treatment trucks 1st after 3.227 5.855 4.658 8

WV Route 32 Treatment trucks 2nd after 6.443 5.384 3.477 12

88
Speed Metric Approach SD PC SD Mid SD N

WV Route 32 Comparison PCs before 6.04 6.046 7.617 124

WV Route 32 Comparison PCs 1st after 5.317 5.057 5.587 185

WV Route 32 Comparison PCs 2nd after 6.315 6.923 6.06 240

WV Route 32 Comparison trucks before 2.992 2.734 3.823 7

WV Route 32 Comparison trucks 1st after 8.023 5.94 5.148 9

WV Route 32 Comparison trucks 2nd after 6.811 6.708 3.373 16 a

Eleven observations at the approach point and 41 observations at the PC and midcurve. b

Four observations at the approach point and 11 observations at the PC and midcurve. 

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after

periods relative to the before period. 

Italics indicates significance at 95-percent confidence level ( =0.05) between the 1st and 2nd after

periods. 

SD = Standard Deviation

PC = Point of Curvature

N= Number of Observations

Encroachment Data

Along with speed metrics, the research team observed encroachment and braking vehicles;

table 30 shows these data. The data collection and analysis methods were described earlier in this 

report.

Table 30 shows the braking and encroachment data for the comparison and treatment sites. There 

was no statistically significant change in the before or first after period—for any braking or 

encroachment measure—at treatment site A along U.S. Route 219. At treatment site B along

U.S. Route 219, there was a statistically significant reduction in the proportion of vehicles 

entering the curve that encroached onto the shoulder and those vehicles entering the curve that 

encroached over the centerline, when comparing the before with the first after period. However, 

these reductions did not continue into the second after period, and there were no statistically 

significant change in the second after period relative to the before period. At the U.S. Route 219 

comparison site, there was a reduction in the proportion of vehicles entering the curve that 

encroached onto the shoulder in the second after period. There was also a reduction in the 

proportion of vehicles entering the curve that braked inside the curve and a reduction in the 

proportion of vehicles exiting the curve that encroached beyond centerline, when comparing the 

before with the first after period. However, these reductions did not continue into the second 

after period, and there were no reductions in the second after period relative to the before period. 

There was a reduction in the proportion of vehicles entering the curve that encroached on the 

centerline in the first after period at the U.S. Route 33 treatment site, but there was no reduction 

in the second after period. At both the U.S. Route 33 treatment and comparison sites, there was a 

reduction in the proportion of vehicles entering the curve that braked before the curve in the first 

after period, but there was no reduction in the second after period, relative to the before period. 

At the treatment site, there was a statistically significant increase in the proportion of vehicles 

exiting the curve that encroached onto the shoulder, in both after periods. There was also a 

significant reduction in the proportion of vehicles exiting the curve that crossed the centerline

between the two lanes in the first after period, but once again, this reduction did not continue into 

the second after period.

α

α

89
At the WV Route 32 treatment site, there was an increase in the proportion of vehicles entering 

the curve that braked inside the curve in the first after period, but there was no change in the 

second after period relative to the before period. At the WV Route 32 treatment site, the camera 

was placed so it could see before the curve in the second after period, where it could not in the 

before and first after period. As a result, a statistical analysis of the braking before/within the 

curve for this site was not conducted in the second after period. There was also a reduction in the 

proportion of vehicles entering the curve that encroached onto the shoulder in the second after

period at the treatment site. This significant reduction becomes more significant after accounting 

for the comparison site because there was an increase in the proportion of vehicles entering the 

curve that encroached onto the shoulder. Finally, at the WV Route 32 comparison site, there was 

a reduction in the proportion of vehicles entering the curve that braked before the curve in the 

first after period, but there was an increase in the second after period. 

There was no significant change in the braking and encroachment data that lasted throughout the 

treatment period except for an increase in the proportion of vehicles exiting the curve that 

encroached onto the shoulder at the U.S. Route 33 treatment site and also a decrease in the 

proportion of vehicles entering the curve that encroached onto the shoulder at the WV Route 32 

treatment site. These results show the HFST does not have a consistent effect on the braking and 

encroachment behavior of vehicles.

90
Table 30. Number of encroachments and braking vehicles by site.

Data-Collection 

Location and Time 

Period

Observation Site

U.S. Route 219 U.S. Route 33 WV Route 32

Treat.

A (MM

6.32)

Treat.

B (MM

5.81)

Comp. Treat. Comp. Treat. Comp.

Total 

entering 

Before 77 61 49 122 89 127 110

1st after 91 74 111 104 80 102 122

2nd after 89 77 39 103 81 74 68

Entering 

shoulder

Before 2 (3%) 10

(16%) 8 (16%) 6 (5%) 4 (4%) 17 (13%) 2 (2%)

1st after 3 (3%) 0 (0%) 12 (11%) 4 (4%) 4 (5%) 11 (11%) 3 (2%)

2nd after 8 (9%) 5 (6%) 1 (3%) 11 (11%) 7 (9%) 1 (1%) 8 (12%)

Entering 

centerline

Before 0 (0%) 10

(16%) 0 (0%) 15 (12%) 10 (11%) 0 (0%) 0 (0%)

1st after 1 (1%) 4 (5%) 0 (0%) 5 (5%) 8 (10%) 1 (1%) 0 (0%)

2nd after 3 10 0 (0%) 8 (8%) 4 (5%) 3 (4%) 0 (0%)

Entering 

brake 

before

Before 56

(73%)

31

(51%) 115 (94%) 85 (96%) 15 (14%)

1st after 75

(82%)

43

(58%) N/A 87 (84%) 62

(78%) N/A 6 (5%)

2nd after 70

(79%)

50

(65%) N/A 96 (93%) 79 (98%) 16 (22%) 18 (26%)

Entering 

brake 

inside

Before 12

(16%)

20

(33%) 47 (96%) 3 (2%) 2 (2%) 35 (28%) 10 (9%)

1st after 6 (7%) 27

(36%)

83

(75%) 4 (4%) 10(13%) 53 (52%) 17 (14%)

2nd after 7 (8%) 23

(30%) 38 (97%) 5 (5%) 1 (1%) 23 (31%) 6 (9%)

Total 

exiting

Before 92 61 60 130 92 132 129

1st after 69 62 78 124 93 96 97

2nd after 90 71 33 94 100 88 76

Exiting 

shoulder

Before 3 (3%) 2 (3%) 3 (5%) 1 (1%) 12 (13%) 6 (5%) 0 (0%)

1st after 3 (4%) 1 (2%) 1 (1%) 9 (7%) 5 (5%) 5 (5%) 0 (0%)

2nd after 2 (2%) 2 (3%) 0 (0%) 18 (19%) 9 (9%) 2 (2%) 1 (1%)

Exiting 

centerline

Before 6 (7%) 12

(20%) 20 (33%) 2 (2%) [48] (37%) 5 (5%) 12 (9%) 6 (5%)

1st after 3 (4%) 5 (8%) 11

(14%)

0 (0%) 

[20](16%) 3 (3%) 7 (7%) 4 (4%)

2nd after 10

(11%)

16

(23%) 12 (36%) 0 (0%) [24] 

(26%) 4 (4%) 7 (8%) 3 (4%)

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period.

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods. 

Brackets indicate encroachment on broken line for U.S. 33 treatment site in uphill (exiting) direction

Treat. = Treatment

MM = Mile Marker

Comp. = Comparison

α

α

91
Friction Data

The research team used the DF tester and CT meter to evaluate the skid resistance of the 

treatment and comparison site locations. The data collection and analysis methods were 

described earlier in this report. Table 31 through table 33 show the before, first after, and second 

after period friction data, respectively. The values reported in each table correspond to the SN at 

40 mph. As table 31 shows, the minimum friction value observed in the before period was 0.26,

and the maximum friction value was 0.46. As noted above, the research team observed friction 

values across the curve approach to determine whether a trend existed. As the data show, there 

was no discernible trend across the approaches (where deceleration occurs). The data do show 

that there is not a consistent level of friction across each approach, but each location varies with

respect to its adjacent location differently at each site. As for the horizontal curve, there is a 

large amount of variability in pavement friction within each horizontal curve in the before

period. At the WV Route 32 and U.S. Route 33 sites, the minimum friction level occurred at the 

three-quarter point of the horizontal curve; however, this was not the case at the U.S. Route 219 

sites. At the U.S. Route 219 sites, the minimum friction level occurred at the one-quarter point or

the midpoint of the horizontal curve. Otherwise, there are no apparent patterns within the 

horizontal curves with regard to friction supply. 

Table 31. SN65 friction data from the before period.

Site 300 ft 200 ft 100 ft PC 1/4 Midcurve 3/4 PT

WV Route 32 Treatment 0.41 0.46 0.40 0.39 0.32 0.38 0.31 0.32

WV Route 32 Comparison 0.38 0.41 0.40 0.36 0.36 0.36 0.28 0.42

U.S. Route 33 Treatment 0.33 0.34 0.34 0.40 0.33 0.32 0.32 0.36

U.S. Route 33 Comparison N/A N/A 0.31 0.34 0.28 0.28 0.26 0.29

U.S. Route 219 Treatment

MM 6.32

0.38 0.37 0.36 0.40 0.36 0.38 0.37 0.40

U.S. Route 219 Treatment

MM 5.81

0.38 0.40 0.40 0.41 0.40 0.35 0.44 0.40

U.S. Route 219 Comparison N/A N/A 0.31 0.32 0.29 0.30 0.33 0.32

MM = Mile Marker

PT = Point of Tangent

N/A = Not Applicable

Table 32 presents the friction data from the immediate after-application period. The HFST was 

only applied within the horizontal curves (from the PC to the PT) at each treatment site. This 

means that the approach data at every site and all data at the comparison sites should be 

comparable. The treatment surface was applied from the PC to the PT for each of the treatment 

curves. For the WV Route 32 treatment site, it is readily apparent that the treatment application 

was not uniform—the observed friction decreased from the PC to the PT. At the other three sites, 

the application appeared to provide the greatest observed friction at the PC and PT; the friction 

across the middle of the curve was lower than at the ends of the curve. 

92
Table 32. SN65 friction data from the immediate after period.

Site 300 ft 200 ft 100 ft PC 1/4 Midcurve 3/4 PT

WV Route 32 Treatment 0.31 0.42 0.43 0.72 0.67 0.66 0.62 0.57

WV Route 32 Comparison 0.32 0.32 0.37 0.35 0.33 0.33 0.35 0.38

U.S. Route 33 Treatment 0.36 0.32 0.38 0.62 0.60 0.51 0.56 0.58

U.S. Route 33 Comparison N/A N/A 0.25 0.27 0.26 0.29 0.26 0.30

U.S. Route 219 Treatment

MM 6.32

0.35 0.32 0.29 0.69 0.56 0.56 0.58 0.60

U.S. Route 219 Treatment

MM 5.81

0.37 0.38 0.34 0.65 0.61 0.62 0.60 0.66

U.S. Route 219 Comparison N/A N/A 0.30 0.31 0.26 0.29 0.27 0.34

MM = Mile Marker

PT = Point of Tangent

N/A = Not Applicable

Table 33 shows the friction data from the second after period. As mentioned in the immediate 

after period at WV Route 32, the observed friction decreased from the PC to PT, with the 

exception that the observed friction at the PT was almost as high as that at the PC location. The 

friction levels within the horizontal curve decreased between 0.12 and 0.15 at the WV Route 32 

treatment site from the immediate after period to the second after period, with the exception of 

the PT location, which increased by 0.1. As mentioned in the immediate after period discussion, 

it is apparent that the treatment was not uniform throughout the curve. The coefficient of friction 

decreased between 0.10 and 0.15 at the U.S. Route 33 treatment site from the immediate after

period to the second after period. The coefficient of friction values at the U.S. Route 219 

treatment sites did not change as much between the two after periods as they did at the U.S. 

Route 33 and WV Route 32 treatment sites.

Table 33. SN65 friction data from the second after period.

Site 300 ft 200 ft 100 ft PC 1/4 Midcurve 3/4 PT

WV Route 32 Treatment 0.36 0.38 0.36 0.59 0.55 0.51 0.50 0.58

WV Route 32 Comparison 0.43 0.36 0.35 0.37 0.29 0.28 0.30 0.35

U.S. Route 33 Treatment 0.32 0.34 0.34 0.51 0.46 0.38 0.46 0.43

U.S. Route 33 Comparison N/A N/A 0.34 0.29 0.29 0.29 0.29 0.30

U.S. Route 219 Treatment MM 6.32 0.33 0.36 0.34 0.59 0.58 0.59 0.61 0.61

U.S. Route 219 Treatment MM 5.81 0.39 0.40 0.43 0.61 0.55 0.51 0.59 0.59

U.S. Route 219 Comparison N/A N/A 0.33 0.37 0.29 0.32 0.36 0.36

MM = Mile Marker

PT = Point of Tangent

N/A = Not Applicable

Table 34 presents the before and after friction data for the treatment site approaches and curves, 

and also presents the data for the comparison sites. The research team conducted a t-test to 

compare the before and both after periods of friction data at each site. The test was statistically

significant (p-value < 0.05) at each of the four treatment curves in the first after period relative to 

the before period. The friction level increased significantly from the before to the after period at 

the treatment sites, ranging from an increase of 0.21 to 0.30 in the SN65 value. At all four 

treatment sites, the second after period produced friction levels that were statistically higher than 

the before period, indicating that the higher friction levels produced by the treatment were 

maintained for at least one year. 

93
Only two sites had friction values that were not significantly different from the before to the after

period. The first was the approach to the WV Route 32 treatment site and the second was the 

U.S. 219 comparison site. This means that for the rest of the treatment approaches and 

comparison sites (none of which were treated with a high-friction surface), the before and after

friction cannot be treated as the same value. The differences were marginal, as can be noted from 

table 34, but may indicate differences resulting from weather conditions or some other 

confounding factor from the before period (in May) to the after period (in August). Because of

these findings, the before and after friction data at the comparison and non-treatment sites were

considered independently in the margin of safety analysis.

Table 34. Before and after friction data for comparison.

Location Mean Standard Deviation N t-stat

WV Route 32 Treatment Approach before 0.424 0.032 6 N/A

WV Route 32 Treatment Approach 1st after 0.386 0.068 6 -1.24

WV Route 32 Treatment Approach 2nd after 0.365 0.015 6 -4.14

WV Route 32 Treatment Curve before 0.347 0.037 10 N/A

WV Route 32 Treatment Curve 1st after 0.646 0.057 10 13.90

WV Route 32 Treatment Curve 2nd after 0.543 0.040 10 11.35

WV Route 32 Comparison Site before 0.370 0.044 16 N/A

WV Route 32 Comparison Site 1st after 0.344 0.026 16 -2.04

WV Route 32 Comparison Site 2nd after 0.341 0.050 16 -1.76

U.S. Route 33 Treatment Approach before 0.340 0.012 6 N/A

U.S. Route 33 Treatment Approach 1st after 0.369 0.017 6 3.40

U.S. Route 33 Treatment Approach 2nd after 0.336 0.010 6 -0.56

U.S. Route 33 Treatment Curve before 0.347 0.037 10 N/A

U.S. Route 33 Treatment Curve 1st after 0.576 0.043 10 12.74

U.S. Route 33 Treatment Curve 2nd after 0.447 0.048 10 5.23

U.S. Route 33 Comparison Site before 0.293 0.027 12 N/A

U.S. Route 33 Comparison Site 1st after 0.276 0.020 12 -1.75

U.S. Route 33 Comparison Site 2nd after 0.301 0.020 12 0.86

U.S. Route 219 Treatment 6.32 Approach before 0.372 0.018 6 N/A

U.S. Route 219 Treatment 6.32 Approach 1st after 0.318 0.029 6 -3.87

U.S. Route 219 Treatment 6.32 Approach 2nd after 0.343 0.012 6 -3.34

U.S. Route 219 Treatment 6.32 Curve before 0.381 0.030 10 N/A

U.S. Route 219 Treatment 6.32 Curve 1st after 0.599 0.053 10 11.32

U.S. Route 219 Treatment 6.32 Curve 2nd after 0.596 0.013 10 21.12

U.S. Route 219 Treatment 5.81 Approach before 0.394 0.017 6 N/A

U.S. Route 219 Treatment 5.81 Approach 1st after 0.363 0.032 6 -2.09

U.S. Route 219 Treatment 5.81 Approach 2nd after 0.406 0.021 6 1.11

U.S. Route 219 Treatment 5.81 Curve before 0.402 0.030 10 N/A

U.S. Route 219 Treatment 5.81 Curve 1st after 0.631 0.028 10 17.62

U.S. Route 219 Treatment 5.81 Curve 2nd after 0.570 0.040 10 10.63

U.S. Route 219 Comparison Site before 0.312 0.013 12 N/A

U.S. Route 219 Comparison Site 1st after 0.296 0.030 12 -1.70

U.S. Route 219 Comparison Site 2nd after 0.338 0.031 12 2.70

Bold indicates that the difference between the after and before period was statistically significant with a 

95-percent confidence.

N = Number of Observations

N/A = Not Applicable

94
As table 34 shows, the friction levels decreased throughout the horizontal curves at three 

treatment sites and remained the same, from the first to second after period, at these same sites. 

The decreases ranged from 0.061 to 0.129. However, the coefficients of friction were all 

significantly higher in the second after period than in the before period. t-statistics ranged from 

5.23 to 21.12. Friction levels at the comparison sites actually increased slightly at two sites and 

remained the same at the other site.

The friction data shown in table 35, table 36, and table 37 are longitudinal friction values for the 

sites. For the margin of safety analysis, the research team estimated the available side (lateral) 

friction. Lamm et al. has shown that available side (lateral) friction is approximately 92.5 percent 

of the available longitudinal friction.

(74)

The authors showed that a multiplier of 0.925 can be 

used to determine available side (lateral) friction from available longitudinal friction. Table 35, 

table 36, and table 37show that using this scaling factor, the estimated available side friction (at 

40 mph) for the before and both after periods, respectively. 

Table 35. SN65 estimated available side friction before treatment application.

Site 300 ft 200 ft 100 ft PC 1/4 Midcurve 3/4 PT

WV Route 32 Treatment 0.38 0.43 0.37 0.36 0.30 0.35 0.29 0.30

WV Route 32 Comparison 0.35 0.38 0.37 0.33 0.33 0.33 0.26 0.39

U.S. Route 33 Treatment 0.31 0.31 0.31 0.37 0.31 0.30 0.30 0.33

U.S. Route 33 Comparison N/A N/A 0.29 0.31 0.26 0.26 0.24 0.27

U.S. Route 219 Treatment MM 6.32 0.35 0.34 0.33 0.37 0.33 0.35 0.34 0.37

U.S. Route 219 Treatment MM 5.81 0.35 0.37 0.37 0.38 0.37 0.32 0.41 0.37

U.S. Route 219 Comparison N/A N/A 0.29 0.30 0.27 0.28 0.31 0.30

MM = Mile Marker

PC = Point of Curve

PT = Point of Tangent

N/A = Not Applicable

Table 36. SN65 Estimated available side friction first after treatment application.

Site 300 ft 200 ft 100 ft PC 1/4 Midcurve 3/4 PT

WV Route 32 Treatment 0.29 0.39 0.40 0.67 0.62 0.61 0.57 0.53

WV Route 32 Comparison 0.30 0.30 0.34 0.32 0.31 0.31 0.32 0.35

U.S. Route 33 Treatment 0.33 0.30 0.35 0.57 0.56 0.47 0.52 0.54

U.S. Route 33 Comparison N/A N/A 0.23 0.25 0.24 0.27 0.24 0.28

U.S. Route 219 Treatment MM 6.32 0.32 0.30 0.27 0.64 0.52 0.52 0.54 0.56

U.S. Route 219 Treatment MM 5.81 0.34 0.35 0.31 0.60 0.56 0.57 0.56 0.61

U.S. Route 219 Comparison N/A N/A 0.28 0.29 0.24 0.27 0.25 0.31

MM = Mile Marker

PC = Point of Curve

PT = Point of Tangent

N/A = Not Applicable

95
Table 37. SN65 estimated available side friction second after treatment application.

Site 300 ft 200 ft 100 ft PC 1/4 Midcurve 3/4 PT

WV Route 32 Treatment 0.33 0.35 0.33 0.54 0.51 0.47 0.46 0.53

WV Route 32 Comparison 0.40 0.34 0.32 0.34 0.26 0.26 0.27 0.33

U.S. Route 33 Treatment 0.30 0.32 0.32 0.47 0.42 0.35 0.42 0.40

U.S. Route 33 Comparison N/A N/A 0.31 0.27 0.27 0.27 0.27 0.28

U.S. Route 219 Treatment MM 6.32 0.31 0.33 0.31 0.54 0.54 0.55 0.56 0.57

U.S. Route 219 Treatment MM 5.81 0.36 0.37 0.40 0.56 0.51 0.47 0.55 0.55

U.S. Route 219 Comparison N/A N/A 0.30 0.34 0.27 0.30 0.34 0.33

MM = Mile Marker

PC = Point of Curve

PT = Point of Tangent

N/A = Not Applicable

A representative friction supply curve was derived for each test segment. The curves were 

plotted to illustrate the difference in friction supply before and after application of the HFST. 

Figure 54 through figure 56 show the plots. The figures support the discussion related to table 35

through table 37. While the available side friction is inconsistent from before to after at some 

comparison locations, the change in available side friction at 40 mph is quite substantial at the 

treatment sites. In general, the application appears to be inconsistent throughout the treatment 

curves, as discussed above. The available side friction is always highest at the PC and in three 

cases, reaches a minimum at approximately the midpoint of the treatment curve. At the WV 

Route 32 site, the friction continues to decrease through the curve and reaches a minimum at the 

PT (in the direction of data collection). This same trend occurred in the second after period, with 

the exception that the side friction does not decrease at the PT and was the same as in the first 

after period. The side friction remained consistent throughout the curve of the U.S. Route 219 

Treatment MM 6.32.

Figure 54. Graph. Side friction supply before and after for WV Route 32 sites.

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

1 2 3 4 5 6 7 8

Coefficient of Friction

Location

WV 32 Treatment Before

WV 32 Treatment 1st After

WV 32 Treatment 2nd After

WV 32 Comparison Before

WV 32 Comparison 1st After

WV 32 Comparison 2nd

After

96
Figure 55. Graph. Side friction supply before and after for U.S. Route 33 sites.

Figure 56. Graph. Side friction supply before and after for U.S. Route 219 sites.

In addition to the friction curves, the research team used speed data collected during the speed 

study to compute the difference in friction supply and the friction demanded by vehicles 

traversing horizontal curves at the treatment and control locations. The friction demand was 

computed using the point-mass model, using the equation shown in figure 57.

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

1 2 3 4 5 6 7 8

Coefficient of Friction

Location

US 33 Treatment Before

US 33 Treatment 1st After

US 33 Treatment 2nd After

US 33 Comparison Before

US 33 Comparison 1st After

US 33 Comparison 2nd After

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

1 2 3 4 5 6 7 8

Coefficient of Friction

Location

US 219 Treatment MM 6.32

Before

US 219 Treatment MM 6.32 1st

After

US 219 Treatment MM 6.32 2nd

After

US 219 Treatment MM 5.81

Before

US 219 Treatment MM 5.81 1st

After

US 219 Treatment MM 5.81 2nd

After

US 219 Comparison Before

US 219 Comparison 1st After

97
Figure 57. Equation. Side friction demand.

Where:

f = side friction demand

V = vehicle operating speed (mph)

R = radius of horizontal curve (ft)

e = rate of superelevation (percent).

During the friction testing, the research team used a digital slope meter to measure the 

superelevation at the midpoint of each horizontal curve. The research team also compared 

descriptive statistics from the distributions of friction demand (e.g., mean, SD, 95th percentile) at 

each treatment and control curve location with the friction supply distribution. Table 38 shows 

the descriptive statistics for each horizontal curve observed. 

15 100

2

e

R

V f = −

98
Table 38. Descriptive statistics for passenger cars for margin of safety analysis.

Site R e

Passenger Car Speed Side Friction Supply

Mean SD Min Max Mean SD Min Max

WV Route 32 Treatment before 680 8 48.05 5.64 27 67 0.32 0.03 0.29 0.36

WV Route 32 Treatment 1st after 680 8 46.54 5.13 23 58 0.60 0.05 0.53 0.67

WV Route 32 Treatment 2nd 

after 680 8 47.63 7.21 17 69 0.50 0.04 0.46 0.54

WV Route 32 Comparison 

before 1,073 7 52.76 7.62 30 72 0.33 0.05 0.26 0.39

WV Route 32 Comparison 1st 

after 1,073 7 52.23 5.59 32 69 0.32 0.02 0.31 0.35

WV Route 32 Comparison 2nd 

after 1,073 7 52.48 6.06 24 75 0.32 0.05 0.26 0.40

U.S. Route 33 Treatment before 210 6 32.37 4.57 18 54 0.32 0.03 0.30 0.37

U.S. Route 33 Treatment 1st 

after 210 6 30.61 3.79 15 42 0.53 0.04 0.47 0.57

U.S. Route 33 Treatment 2nd 

after 210 6 30.15 5.02 15 54 0.41 0.04 0.35 0.47

U.S. Route 33 Comparison 

before 265 8.5 36.17 6.79 13 58 0.27 0.03 0.24 0.31

U.S. Route 33 Comparison 1st 

after 265 8.5 35.46 6.09 12 48 0.26 0.01 0.24 0.28

U.S. Route 33 Comparison 2nd 

after 265 8.5 34.44 5.45 11 48 0.28 0.02 0.27 0.31

U.S. Route 219 Treatment MM 

6.32 before 605 11 36.29 7.22 12 62 0.35 0.03 0.33 0.37

U.S. Route 219 Treatment MM 

6.32 1st after 605 11 40.34 5.43 13 56 0.55 0.05 0.52 0.64

U.S. Route 219 Treatment MM 

6.32 2nd after 605 11 41.97 4.72 30 63 0.55 0.01 0.54 0.57

U.S. Route 219 Treatment MM 

5.81 before 273 12 34.80 6.73 21 66 0.37 0.03 0.32 0.41

U.S. Route 219 Treatment MM 

5.81 1st after 273 12 37.14 6.46 21 70 0.58 0.03 0.56 0.61

U.S. Route 219 Treatment MM 

5.81 2nd after 273 12 33.72 5.20 21 47 0.53 0.04 0.47 0.56

U.S. Route 219 Comparison 

before 545 12 41.16 4.35 29 53 0.29 0.01 0.27 0.31

U.S. Route 219 Comparison 1st 

after 545 12 43.86 5.35 26 54 0.27 0.03 0.24 0.31

U.S. Route 219 Comparison 2nd 

after 545 12 41.12 5.80 27 48 0.31 0.03 0.27 0.34

MM = Mile Marker

SD = Standard Deviation

Max = Maximum

Min = Minimum

The margin of safety, based on the difference between the distributions of friction supply and 

demand, was computed for each treatment and control location, as table 39 shows. The mean 

friction demand at all sites, for all time periods, is lower than the mean side friction supply. The 

85th percentile friction demand at all treatment sites, for all time periods, except the before time 

period of the U.S. 33 treatment site, is lower than the mean side friction supply. The 85th

percentile friction demand for all time periods of the U.S. 33 comparison site is greater than the 

99
side friction supply. The 95th percentile friction demand at all treatment sites, for all time 

periods except the before time period of the U.S. Route 33 treatment site, is lower than the mean 

side friction supply. The 95th percentile friction demand for all time periods of the U.S. Route 33 

comparison site is greater than the side friction supply. The only additional site where the friction 

demand at the 95th percentile exceeded the friction supply was at the U.S. Route 219 treatment 

MM 5.81 site in the before period.

Table 39. Friction demand and supply comparison.

Site

Side Friction Demand Side Friction Supply

Mean

85th

Percentile

95th

Percentile Mean SD Min Max

WV Route 32 Treatment before 0.146 0.205 0.242 0.321 0.034 0.290 0.360

WV Route 32 Treatment 1st after 0.132 0.183 0.216 0.598 0.053 0.530 0.670

WV Route 32 Treatment 2nd after 0.142 0.218 0.267 0.502 0.037 0.459 0.542

WV Route 32 Comparison before 0.103 0.159 0.195 0.329 0.045 0.260 0.390

WV Route 32 Comparison 1st after 0.099 0.139 0.164 0.322 0.022 0.310 0.350

WV Route 32 Comparison 2nd after 0.101 0.144 0.172 0.315 0.046 0.261 0.395

U.S. Route 33 Treatment before 0.273 0.377 0.445 0.321 0.033 0.300 0.370

U.S. Route 33 Treatment 1st after 0.238 0.319 0.371 0.533 0.040 0.470 0.570

U.S. Route 33 Treatment 2nd after 0.229 0.337 0.409 0.414 0.045 0.350 0.473

U.S. Route 33 Comparison before 0.244 0.385 0.479 0.268 0.026 0.240 0.310

U.S. Route 33 Comparison 1st after 0.232 0.354 0.435 0.257 0.014 0.240 0.280

U.S. Route 33 Comparison 2nd after 0.214 0.320 0.389 0.279 0.018 0.265 0.314

U.S. Route 219 Treatment MM 6.32 before 0.035 0.101 0.146 0.352 0.027 0.330 0.370

U.S. Route 219 Treatment MM 6.32 1st 

after 0.069 0.123 0.158 0.554 0.049 0.520 0.640

U.S. Route 219 Treatment MM 6.32 2nd 

after 0.084 0.132 0.162 0.552 0.012 0.540 0.569

U.S. Route 219 Treatment MM 5.81 before 0.176 0.306 0.394 0.372 0.028 0.320 0.410

U.S. Route 219 Treatment MM 5.81 1st 

after 0.217 0.349 0.438 0.583 0.026 0.560 0.610

U.S. Route 219 Treatment MM 5.81 2nd 

after 0.158 0.254 0.317 0.527 0.037 0.472 0.563

U.S. Route 219 Comparison before 0.087 0.135 0.166 0.288 0.013 0.270 0.310

U.S. Route 219 Comparison 1st after 0.115 0.179 0.220 0.272 0.030 0.240 0.310

U.S. Route 219 Comparison 2nd after 0.087 0.152 0.194 0.313 0.028 0.267 0.342

Bold indicates 85th percentile friction demand exceeded mean side friction supply.

Italics indicates 95th percentile friction demand exceeded mean side friction supply.

SD = Standard Deviation

Max = Maximum

Min = Minimum

SUMMARY OF HFST EVALUATION FINDINGS

The research team performed operational, driver behavior, and friction evaluations on four 

treatment and three corresponding comparison sites in West Virginia. The operational and driver 

behavior analyses generally found no consistent differences at the treatment sites between the 

before and after time periods from the data. The friction analysis, however, clearly demonstrated 

that the friction increased considerably at the four horizontal curve treatment locations in West 

Virginia. The friction generally remained high for 1 year after the treatment was applied. A 

safety analysis being completed under a separate FHWA contract will reveal further information 

about the safety effects of the high-friction surface treatment.

100
5. SPEED EFFECTS OF OPTICAL SPEED BARS ON RURAL 

AND SUBURBAN ROADS

This section describes the OSB site selection criteria, design, site characteristics, and data 

collection and analysis methods used for evaluation.

OVERVIEW 

OSBs are 18-inch-long and 12-inch-wide white transverse markings placed on both sides of the 

lane perpendicular to the centerline, edge line, or lane line in a pattern of progressively reduced 

spacing. The pattern gives drivers the impression that their speed is increasing. The intended 

outcome of the treatment is to reduce vehicle-operating speeds. 

The initial and final spacing between the OSBs depends on the initial speed (approach speed) 

and desired speed in the curve (advisory speed). The length of roadway treated with the OSBs 

depends on the speed difference between the initial and final speed. FHWA recommends that 

drivers be in the OSB segment for at least 4 s. 

OSBs can be painted on the roadway or a thermoplastic material is used to improve durability 

and increase longevity of the markings. OSBs are typically installed in school zones, at 

horizontal curve locations, or on tangent roadway segments. This project analyzed the effects of 

OSBs on vehicle operating speeds on horizontal curves using an observational before-after study. 

Figure 58 shows an example of an OSB treatment.

Source: KLS Engineering, LLC

Figure 58. Photo. OSB example.

101
SITE SELECTION 

The research team used extensive outreach with several State and local transportation agencies to 

identify potential locations for installing OSB treatment on two-lane rural/suburban horizontal 

curves. The research team contacted more than 40 agencies to determine their willingness to 

install the treatment, 3 of which came forward to install or assist in installing the treatment for 

the study purposes. The three agencies are Massachusetts Southeastern Regional Planning and

Economic Development District (SRPEDD), Mohave County (Arizona), and the Alabama 

Department of Transportation (ALDOT). 

SRPEDD conducted road safety audits (RSA) in 2009 on eight roadways in suburban/rural areas 

of southeastern Massachusetts. The roadways were selected based on the number of lanedeparture crashes resulting in injury or death. OSBs were one of the treatments recommended in 

the RSA, especially on the approaches to the many dangerous curves. Initially, the research team 

selected 11 curved segments on 6 different two-lane roadways for OSB consideration. Based on 

further discussions with SRPEDD and the counties, the initial list of 11 was narrowed to 

8 locations on 4 roadways. During site visit, one location was found not to have an edge line and 

was thus eliminated, bringing the total number of sites in Massachusetts to seven. Table 40

shows the Massachusetts OSB treatment site(s) characteristics and location details.

Mohave County previously experimented with OSB at one location (Stockton Hill Road between 

MM 21 and 20) in July 2007, and was familiar with the OSB considerations. Mohave County 

examined speed and crash data maintained for its regional highway network and recommended 

four two-lane rural roadways as candidates. The locations had been the sites of a significant 

number of crashes, 85th percentile speeds significantly above posted, or both. Table 40 shows 

the Arizona OSB treatment site(s) characteristics and location details.

ALDOT provided 10 two-way rural roadways for OSB consideration. The roadways were 

selected based on crash data, at least three crashes on average per year over the last 10 years, on 

the approach, within, or immediately following a horizontal curve. Five roadways were deemed 

inappropriate for study purposes (residential streets, vicinity of major intersection, etc.). Eight 

curve segments on five different roadways were selected for OSB installation. Table 40 shows 

the Alabama OSB treatment site(s) characteristics. The identifying location information (e.g., 

route, milepost, county name) is not listed at the counties’ request.

To summarize, a total of 19 treatment sites (7 in Massachusetts, 4 in Arizona, and 8 in Alabama) 

were selected for field evaluations. 

TREATMENT DESIGN 

The research team used two different types of OSB designs, as discussed in the following 

sections. 

Design for Massachusetts and Arizona Sites 

This layout was based on an experimental design by Mohave County Public Works (MCPW), 

which yielded positive results. The MCPW optical speed zone contained three speed-bar 

patterns―downstream, transition, and upstream―designed to convey to road users a sensory 

102
perception of increased speed while traveling through the zone. The MCPW design used a driver 

perception time of .75 s. The MCPW design layout involved computing the downstream barpattern spacing by multiplying the site-measured 85th percentile speed by 1 s and upstream bar 

spacing by 1.5 s (targeting a 50-percent increase in spacing from downstream to upstream). The 

transition pattern provided an incremental reduction in bar spacing, from upstream to 

downstream pattern spacing distance, between successive bars to disguise the physical change in 

bar spacing from the passing road user. The design used a fixed set of five bars in the upstream 

and downstream patterns while the transition set contained four bars. 

To normalize the effects of differing PSLs, the research team slightly modified the MCPW 

design as follows:

• Used four bars each in the downstream pattern and upstream pattern and three bars in 

the transition zone.

• The upstream set bar spacing was established at 1-s headway. 

• The downstream set bar spacing was established at 0.6-s headway.

• The transition set consisted of four sequential bars spaced at 0.9-, 0.8-, 0.7-, and 0.6-s 

headway. 

• All spacing calculations were rounded to the next 5 ft. 

This approach is demonstrated below using an example 40 mph, 85th percentile speed:

• Upstream set spacing at 1-s headway = (40*5280/3600)*1 ≈ 60 ft.

• Total upstream set spacing for four bars = 4*60 = 240 ft.

• Transition Set.

o First bar spaced at 0.9-s headway ≈ 54 ft.

o Second bar spaced at 0.8-s headway ≈ 48 ft.

o Third bar spaced at 0.7-s headway ≈ 42 ft.

• Total transition set spacing = 54 ft +48 ft +42 ft = 144 ft.

• Total downstream set spacing at 0.6-s headway = 4*36 = 144 ft.

• Total treatment length = 240 ft + 144 ft + 144 ft = 528 ft.

Design for Alabama Sites 

The design principle adopted for the Alabama sites was the same design used in studies by Katz 

and Arnold et al.(56,75) This design methodology considered an initial speed and a desired ending 

103
speed at each location. Based on these speeds, the length of OSB treatment is determined based 

on deceleration from the initial to the ending speed, and the bars are spaced such that a driver 

decelerating at a constant rate from the initial speed to the ending speed crosses four bars per 

second. The equation shown in figure 59 is used to determine the required length of the OSB

treatment, and the equation shown in figure 60, developed by Katz, is used to find the spacing of 

the optical speed bar throughout the treatment.(76) A frequency of four bars per second was 

adopted for OSB design.

Figure 59. Equation. Length of OSB treatment.

Where: 

D = distance traveled in slowing from vv0 to vv1.

= deceleration rate.

0 = initial speed at the beginning of the treatment.

1 = final speed.

Figure 60. Equation. Individual placement of the OSBs.

Where:

= placement of the optical speed bars.

xx0 = initial placement of the first bar. The value of xx0 is set to zero when a first bar is placed at 

the beginning of the treatment.

= number of the optical speed bar for which the placement is determined.

f = required frequency of the bars, which is the number of OSBs seen in a second by motorists 

travelling through the treatment.

The dimensions of the OSB installed were in accordance with the 2009 Manual on Uniform 

Traffic Control Devices (MUTCD) (Part 3B.22) recommended guidelines. The markings were 

12 inches wide by 18 inches long, installed on both sides of the lane perpendicular to the center 

line and edge line. 

α

vv

vv

xx

nn

104
SITE CHARACTERISTICS

The range of features of the 19 study sites was quite broad. The characteristics of the study sites 

included the following:

• A minimum radius of 236 ft and maximum radius of 1,865 ft.

• Curves to the left and to the right.

• Speed limits of 25 to 55 mph.

• Advisory speeds of 20 to 35 mph.

Table 40 summarizes the site characteristics of the 19 treatment sites. The Before Period Data 

Summary section describes specific characteristics of each treatment site.

105
Table 40. OSB treatment location site characteristics.

City/County

Route Name/

Number

Curve 

Direction/

Grade AADT

PSL 

(mph)

Lane 

Widt

h (ft)

Lc

(ft)

Approx.

Radius 

(ft)

1 Dolan Springs/ 

Mohave County, AZ

Pierce Ferry 

Road 

(northbound)

Left/Uphill 750 55/50a 12 993 497

2 Golden Valley/ 

Mohave County, AZ

Shinarump 

Road 

(southbound)

Left/Level 450 45 12 887 1,865

3 Meadview/Mohave 

County, AZ

Diamond Bar 

Road 

(southbound)

Right/Level 470 45 12 875 1,067

4 Golden Shores/ 

Mohave County, AZ

County Route 1 

(southbound) Right/Uphill 850 35 13 332 1,095

5 Alabama location #1 N/A Right/Level 1,050 55 10 666 673

6 Alabama location #2 N/A Right/Level 1,065 55 11 303 273

7 Alabama location #3 N/A Right/Level 2,770 55 12 546 635

8 Alabama location #4 N/A Right/Uphill 1,570 35 10 278 236

9 Alabama location #5 N/A Right/ 

Downhill 380 40 10 1060 710

10 Alabama location #6 N/A Right/Level 390 40 10 885 710

11 Alabama location #7 N/A Right/Level 1,275 35 10 457 602

12 Alabama location #8 N/A Right/ 

Downhill 1,370 35 11 223 486

13 Dartmouth/Bristol 

County, MA

Tucker Road 

(southbound) Right/Level 2,900 30 13 817 1,099

14 Dartmouth/Bristol 

County, MA

Tucker Road 

(northbound) Left/Level 3,950 35 12 293 569

15 Dartmouth/Bristol 

County, MA

Reed Road 

(southbound) Left/Level 5,450 25 12 459 683

16 Fairhaven/Bristol 

County, MA

New Boston 

Road 

(southbound)

Left/Level 750 35 11 226 596

17 Fairhaven/Bristol 

County, MA

New Boston 

Road 

(northbound)

Right/Level 750 35 11 186 471

18 Rochester /Plymouth 

County, MA

Braley Hill 

Road 

(southbound)

Right/Level 1,150 30 11 673 695

19 Rochester/Plymouth 

County, MA

Braley Hill 

Road 

(northbound)

Right/Level 1,050 40 10 662 2,097

a

-50 mph is nighttime PSL

AADT = Annual Average Daily Traffic

PSL = Posted Speed Limit

Lc = Length of Curve

Approx. = Approximate

106
INSTALLATION

In all three States, thermoplastic tape, applied with heat, was used to install the OSBs. Glass 

beads were added while the tape was being placed to increase visibility. Spacing of the bars was 

measured prior to their installation.

Installation at the four sites in Mohave County, AZ, occurred between October 25 and 30, 2012. 

Installation at the seven Massachusetts sites occurred between November 19 and 23, 2012. Each 

county installed the OSBs in their areas. The eight Alabama locations were installed between 

September 25 and October 1, 2013, and contractors performed the installation for ALDOT.

OPERATING SPEED EVALUATION METHODOLOGY

Data-Collection Procedures

The OSB treatments started on the tangent approaching the horizontal curves and ended near the 

beginning of the curve (PC station). An observational before-after study was employed to 

evaluate the OSB treatment. Speed data were collected before and after OSBs were applied to 

four sites in Arizona, eight sites in Alabama, and seven sites in Massachusetts. The before period 

data were collected prior to applying the OSBs. Two after-period data collection efforts were 

undertaken. The first after-period data were collected approximately 1 month after the OSBs

were installed in Alabama, Arizona, and Massachusetts. The second after-period data were 

collected approximately 6 months after the first after period in Arizona and 3 months after the 

first after period in Alabama. There was no second after-period data collected at the 

Massachusetts sites. The second after period was performed to assess long-term novelty effects 

of the OSBs and to determine whether they became less effective in reducing vehicle operating 

speeds over time.

The research team used a control point on the same roadway to determine whether vehicle 

operating speeds remained constant at a location that was not treated to ensure that another factor 

was not influencing vehicle speeds. The control point locations for the OSB evaluation were 

points located between 0.2 and 0.8 mi upstream of the treatment site location, on a tangent 

segment. The control point location was far enough upstream of the treatment so drivers were 

unable to see the treatment from that location. 

Data were collected using on-pavement traffic sensors. A total of six sensors, four in the OSB 

travel direction and two in the opposing lane, were placed to allow vehicles to be tracked 

throughout the study site, thus enabling the determination of speed changes for individual 

vehicles. The first sensor in the travel direction was placed at the control point. The second 

sensor in the travel direction was placed at the first transverse marking that delineated the OSBs, 

which was located on the curve approach. The third sensor in the travel direction was placed at 

the last transverse marking that delineated the OSBs, which was near the PC. The fourth sensor 

was placed at the curve midpoint to determine whether any speed reduction was maintained 

throughout the curve. Two sensors were placed in the opposing lane to determine whether the 

presence of a vehicle travelling in the opposite direction influenced driver speed choice.

Figure 61 shows the layout of the speed data-collection equipment in relation to the OSB 

treatment.

107
Figure 61. Diagram. OSB data-collection setup (not to scale).

Speed data were collected during both daytime and nighttime periods at each site. At each study 

site, the research team collected data during favorable driving conditions: clear weather with 

normal visibility (no fog) and dry roadway conditions, without the presence of standing water 

from an earlier rain. The data were screened to include only free-flow vehicles, defined as those 

vehicles traveling with a minimum headway of 5 s.

(70,71) The analysis included only passenger 

vehicles, which were defined as vehicles having a length less than 24 ft. 

The research team attempted to obtain the recommended 110 free-flow passenger car speeds for 

both the daytime and nighttime periods at each data-collection site in accordance with the sample 

size requirement described in table 7 and table 8. The 110 free-flow passenger car speeds 

recommended for each data-collection period based on the equation in figure 20 would yield 

95-percent statistical significance and more than 90-percent statistical power, if a 2.0-mph

difference in means was computed among the before and after samples. At sites where data were 

collected over 2 days/nights, and 1 day/night did not provide the recommended sample of freeflow passenger cars, a two-sample t-test was performed to compare the mean speeds between the 

2 days/nights. If there was no statistically significant difference between the 2 days/nights, then 

they were combined to provide more free-flow speed observations for analysis.

An important data-collection condition to note relates to possible measurement error from the 

on-road sensors at several data-collection sites in the OSB evaluation. Outliers in the speed data 

were identified using the following process:

1. Speeds remained relatively consistent from the control point to approach at most sites, 

as would be expected, so it was assumed the speeds at these two points were precise.

108
2. At some sites, the speeds at the PC appeared to be unrealistically high, while at other 

sites, the speeds at the curve midpoint appeared to be unrealistically high. Many 

observations had acceleration rates exceeding 10 ft/s

2

, which was nearly equivalent to 

deceleration rates assumed in stopping sight distance geometric design criteria. It was 

expected that vehicles either maintain their speed throughout the curve or decelerate, 

but not accelerate from the PC to curve midpoint. Previous research by Hu and Donnell 

found the maximum deceleration rate of vehicles entering a curve was 4.4 ft/s2

.

(77) 

Using this previous study, any observation with an acceleration rate less than -4.5 ft/s 

or greater than 1.0 ft/s (to be conservative) from the approach to PC or from the 

approach to curve midpoint, was eliminated from the database. 

3. While each vehicle speed was tracked from the control point location through the 

midpoint of the horizontal curve, in accordance with the data-collection setup shown in 

figure 61, the acceleration/deceleration rates between the approach point, PC location, 

and midcurve location were compared. When a point speed at the locations produced 

rates of acceleration/deceleration outside the limits identified in item 2 above, the 

research team excluded this individual point speed from the analysis. 

Performance Measures and Analysis Methods

The performance measures used to assess the speed effects of the OSB treatment included the 

mean speed, difference in speeds between the beginning and end OSB speed measurement 

locations (delta v as described in the HFST Statistical Analysis section), speed variance, and 

proportion of vehicles exceeding the PSL. Details of the statistical analysis methods are the same 

as for HFST. The mean speed will be evaluated using the equation in figure 21. The proportion 

of vehicles exceeding the PSL will be assessed using the equations shown in figure 22 through 

figure 25, and the speed variance will be appraised using the equation shown in figure 26.

BEFORE PERIOD DATA SUMMARY

This section of the report describes the before period speeds at each data-collection location. 

Arizona 

This section describes the characteristics of the four treatment sites in Arizona.

Northbound Pierce Ferry Road, AZ

The research team collected data on Pierce Ferry Road in Meadview, AZ. The direction of travel 

for the data collection was northbound, and the curve direction was to the left. The radius of 

curve and the curve length, calculated using Google EarthTM, were 497.40 ft and 992.78 ft, 

respectively. There was a substantial cut-slope on the inside of the curve, which limits horizontal 

sight distance along the curve. The daytime PSL was 55 mph, and nighttime PSL was 50 mph. 

As figure 62 shows, there was a curve warning sign (W1-2) with an advisory speed plaque of 

35 mph (W13-1P) located prior to the PC. The travel lanes were 12 ft wide, and there were no 

paved shoulders on either side of the road. However, there was a gravel shoulder on both sides of 

the road approximately 5 ft wide.

109
The team collected speed data in the before period at the control point 0.4 mi before the curve 

approach, which was 800 ft before the PC. The research team also collected speed data at the PC 

and midpoint of the curve. One sensor in the opposing direction of travel was placed at the 

midpoint of the curve, and the other one was placed 660 ft downstream of the first sensor to 

determine whether vehicles were present in the opposing lane. Figure 62 shows the horizontal 

curve layout and the speed data-collection locations.

110
Figure 62. Diagram. Geometric layout of northbound Pierce Ferry Road (not to scale).

111
Table 41 shows the speed data collected in the before period. The data are shown as all 

observations, passenger car versus heavy trucks, daytime versus nighttime speeds for passenger 

cars, and opposed (a vehicle present in the opposing lane) versus unopposed passenger cars. All 

of the comparisons exclude vehicles with high accelerations. The research team performed a 

simple t-test for each of these comparisons at each of the curve locations. For this treatment site, 

there was a statistically significant difference in speeds at the control point, approach, PC, and 

curve midpoint for passenger cars versus heavy vehicles. There was also a statistically significant 

difference in speeds at the control point, approach, and PC for daytime passenger cars versus 

nighttime passenger cars. The nighttime speed was significantly lower at every data-collection 

point. 

Table 41. Northbound Pierce Ferry Road before data.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 48.532 7.764 46.165 8.162 46.432 6.817 38.056 6.841 218 176 214

Passenger 

cars

48.867 7.565 46.793 7.855 46.789 6.628 38.513 6.739 203 166 199

Heavy 

trucks 44.000 9.220 37.667 7.697 40.500 7.546 32.000 5.237 15 10 15

Daytime 

passenger 

cars

49.577 7.116 47.521 7.429 47.669 6.277 39.271 6.744 142 118 140

Nighttime 

passenger 

cars

47.213 8.347 45.098 8.594 44.625 7.028 36.712 6.430 61 48 59

Opposed 

passenger 

cars

47.806 6.122 46.444 8.833 47.621 7.683 38.029 6.671 36 29 35

Unopposed 

passenger 

cars

49.096 7.838 46.868 7.655 46.613 6.400 38.616 6.769 167 137 164

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 63 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 63 also shows the mean speed for trucks within 

the study section. The figure shows that mean speeds for both heavy trucks and passenger cars 

remain relatively stable from the approach to the PC, but decrease substantially from the PC to 

the midpoint of the curve. The heavy-truck mean speeds align more with the 15th percentile 

passenger car speeds. Both the passenger car and truck mean speeds are consistent with the 

advisory speed of 35 mph at the midpoint of the curve. The mean acceleration rate from the PC 

to the midpoint of the curve was -3.534 ft/s for passenger cars and -3.803 ft/s for trucks. A 

negative value indicates deceleration.

α

112
Figure 63. Graph. Graphical representation of speeds on northbound Pierce Ferry Road.

Southbound Shinarump Road, AZ

The research team collected data on Shinarump Road in Golden Valley, AZ. The direction of 

travel for the data collection was southbound, and the curve direction was to the left. The radius 

of curve and the curve length, calculated using Google EarthTM, were 1,865.05 ft and 887.35 ft, 

respectively. The PSL was 45 mph. The travel lanes were 12 ft wide, and there was no shoulder 

on either side of the road. 

The team collected speed data at the control point, 0.6 mi before the curve approach, which was 

800 ft before the PC. The research team also collected speed data at the PC and midpoint of the 

curve. One sensor was placed in the opposing direction of travel at the midpoint of the curve, and 

the other was placed 618 ft downstream of the first sensor to determine whether vehicles were 

present in the opposing lane. Figure 64 shows the horizontal curve layout, along with the speed 

collection locations.

Figure 64. Diagram. Geometric layout of southbound Shinarump Road (not to scale).

30

35

40

45

50

55

60

Control Pt Approach PC MidPt

Speed (mph)

Northbound Pierce Ferry Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

Advisory Speed

113
Table 42 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

curve location. For this treatment site, there was a statistically significant difference in speeds at 

the PC location for passenger cars versus heavy vehicles. There was also a statistically 

significant difference at the control point and PC for daytime versus nighttime passenger cars. 

There was a statistically significant difference at the approach and PC locations for opposed 

versus unopposed passenger cars. 

Table 42. Southbound Shinarump Road before data.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 47.317 6.928 51.099 8.603 47.299 6.864 51.100 8.042 303 288 209

Passenger 

cars

47.566 6.768 51.241 8.023 48.017 6.341 51.537 7.773 249 238 175

Heavy 

trucks 46.167 7.583 50.444 10.956 43.880 8.188 48.853 9.099 54 50 34

Daytime 

passenger 

cars

46.686 7.001 50.777 8.431 47.009 6.033 50.894 7.375 121 115 94

Nighttime 

passenger 

cars

48.398 6.458 51.680 7.624 48.959 6.500 52.284 8.193 128 123 81

Opposed 

passenger 

cars

45.967 6.646 48.200 5.580 45.933 4.982 50.875 6.556 30 30 24

Unopposed 

passenger 

cars

47.785 6.770 51.658 8.224 48.317 6.468 51.642 7.964 219 208 151

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 65 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 65 also shows the mean speed for trucks within 

the study section. As the figure shows, the patterns of the speed changes were similar for the 

passenger car speeds and the truck mean speeds on the approach to curve. The speeds for 

passenger cars and the truck mean speeds increased from the control point to the approach of the 

curve, decreased from the approach to the PC, and then increased again from the PC to the 

midpoint of the curve. The 85th percentile speeds and the mean speeds for passenger cars along 

the curve were higher than the PSL of 45 mph. The mean acceleration rate from the PC to the 

midpoint of the curve was 4 ft/s for passenger cars and 6 ft/s for trucks. 

α

114
Figure 65. Graph. Graphical representation of speeds on southbound Shinarump Road.

Southbound Diamond Bar Road, AZ

The research team collected data on Diamond Bar Road in Meadview, AZ. The direction of 

travel for the data collection was in the southbound direction, and the curve direction was to the 

right. The radius of curve and the curve length, calculated using Google EarthTM, were 1,067.25 

ft 875.32 ft, respectively. There were desert plants on the inside of the curve, which limited

horizontal sight distance along the curve. The PSL was 45 mph. As figure 66 shows, there was a 

curve warning sign (W1-2) located after the PC. The travel lanes were 12 ft wide, and there were 

5-ft paved shoulders on both sides of the road. 

The team collected speed data at the control point, 0.4 mi before the curve approach, which was 

800 ft before the PC. Speed data were also collected at the PC and midpoint of the curve. One 

sensor in the opposing direction of travel was placed at the midpoint of the curve, and the other 

one was placed 640 ft downstream of the first sensor to determine whether vehicles were present 

in the opposing lane. Figure 66 shows the horizontal curve layout, along with the speed 

collection locations. 

The OSBs were installed differently at this site compared with the other sites. The OSB 

treatment started 400 ft upstream of the curve start, compared with beginning at the curve start at 

the other Arizona, Massachusetts, and Alabama sites. Because the treatment was offset from the 

curve PC location, an additional sensor was placed at the end of the OSB treatment. Figure 67

shows the layout of the sensors in the after periods. 

30

35

40

45

50

55

60

Control Pt Approach PC MidPt

Speed (mph)

Southbound Shinarump Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

115
Figure 66. Diagram. Geometric layout of southbound Diamond Bar Road in the before

period (not to scale).

Figure 67. Diagram. Geometric layout of southbound Diamond Bar Road in the after

periods (not to scale).

116
Table 43 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team again performed a simple t-test for each of these comparisons at 

each of the curve locations. For this treatment site, there was a statistically significant difference 

in speeds at the control point, approach, PC, and curve midpoint for passenger cars versus heavy 

vehicles. The heavy vehicle speed was lower than the passenger car speed at all the datacollection points. There also was a significant difference at the PC for daytime versus nighttime 

passenger cars.

Table 43. Southbound Diamond Bar Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 53.421 8.312 49.171 6.730 50.299 7.116 50.435 7.621 292 214 209

Passenger cars 53.867 8.389 49.516 6.675 50.874 6.996 50.703 7.611 256 182 182

Heavy trucks 50.250 7.064 46.722 6.704 47.031 7.014 48.630 7.581 36 32 27

Daytime 

passenger cars

54.061 8.582 49.873 7.057 51.706 7.113 51.109 7.876 181 126 128

Nighttime 

passenger cars

53.400 7.939 48.653 5.598 49.000 6.399 49.741 6.918 75 56 54

Opposed 

passenger cars

53.472 9.376 50.057 6.320 51.000 8.218 50.057 8.359 53 35 35

Unopposed 

passenger cars

53.970 8.134 49.374 6.773 50.844 6.705 50.857 7.445 203 147 147

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 68 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 68 also shows the mean speed for trucks within 

the study section. As the figure shows, the passenger car speeds and the truck mean speeds were 

relatively stable along the curve. The speed changes between points were minor. The truck mean 

speeds were consistent from the control point to the PC; however, the speeds increased slightly 

from the PC to midpoint of the curve. The 85th percentile speeds and mean speeds for passenger 

cars are higher than the PSL of 45 mph. The mean acceleration rate from the PC to the midpoint 

of the curve was 1 ft/s for passenger cars and 2.835 ft/s for trucks. 

α

117
Figure 68. Graph. Graphical representation of speeds on southbound Diamond Bar Road.

Southbound County Route 1, AZ

The research team collected data on County Route 1 in Golden Shores, AZ. The direction of 

travel for the data collection was southbound, and the curve direction was to the right. The curve 

was located on a moderate upgrade. The radius of curve and the curve length, calculated using 

Google Earth, were 1,095.39 ft and 332.27 ft, respectively. The PSL was 35 mph. The travel 

lanes were 13 ft wide, and there was a 4- to 5-ft paved shoulder on both sides of the road.

The team collected speed data at the control point, 0.8 mi before the curve approach, which was 

800 ft before the PC. The research team also collected speed data at the PC and midpoint of the 

curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve, and 

the other one was placed 732 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 69 shows the horizontal curve layout, along with the 

speed collection locations. 

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Southbound Diamond Bar Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

118
Figure 69. Diagram. Geometric layout of southbound County Route 1 (not to scale).

119
Table 44 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

curve location. For this treatment site, there was a statistically significant difference in speeds at 

the approach, PC, and midpoint for daytime versus nighttime passenger cars. There was also a 

significant difference at the midpoint for opposed versus unopposed passenger cars.

Table 44. Southbound County Route 1 before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 53.471 8.882 47.731 5.559 44.021 5.211 43.919 7.259 342 329 307

Passenger cars 53.532 8.901 47.810 5.515 44.134 5.125 43.918 7.262 327 314 292

Heavy trucks 52.133 8.651 46.000 6.414 41.667 6.532 43.933 7.450 15 15 15

Daytime 

passenger cars

53.847 9.266 49.038 5.430 44.977 4.895 44.599 7.081 183 174 162

Nighttime 

passenger cars

53.132 8.428 46.250 5.238 43.086 5.228 43.069 7.421 144 140 130

Opposed 

passenger cars

53.479 9.299 47.125 5.354 44.111 4.900 41.091 7.844 48 45 44

Unopposed 

passenger cars

53.541 8.848 47.928 5.543 44.138 5.171 44.419 7.053 279 269 248

Bold indicates significance at 95 percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 70 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 70 also shows the mean speed for trucks within 

the study section. The figure shows the passenger car speeds decelerated substantially from the 

control point to the PC and then stabilized from the PC to the midpoint of the curve. The truck 

mean speeds decreased from the control point to the midpoint of the curve. The passenger car 

speeds and the truck mean speeds along the curve were higher than the PSL of 35 mph. The 

mean acceleration rate from the PC to the midpoint of the curve was 0.581 ft/s for passenger cars 

and 0.668 ft/s for trucks.

α

120
Figure 70. Graph. Graphical representation of speeds on southbound County Route 1.

Alabama

This section describes the characteristics of the eight treatment sites in Alabama. ALDOT had an 

agreement with the counties that route information would not be disclosed. Thus, in the 

discussion below all eight Alabama locations are referenced numerically (1 through 8).

Alabama Location #1

The direction of travel for the data collection was northbound, and the curve direction was to the 

right. The radius of curve and the curve length, calculated using Google EarthTM, were 672.84 ft 

and 665.84 ft, respectively. The PSL was 55 mph. As figure 71 shows, there was a winding road 

sign (W1-5) 365 ft before the curve approach. The travel lanes were 11 ft wide, and there were 

2-ft paved shoulders on both sides of the road. There were trees offset approximately 10 ft from 

the inside edge of pavement, which limited horizontal sight distance along the curve.

The research team collected speed data at the control point, 0.4 mi before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 515 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 71 shows the horizontal curve layout, along with the 

speed data-collection locations. 

30

35

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Southbound County Route 1

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

121
Figure 71. Diagram. Geometric layout of Alabama Location #1 (not to scale).

122
Table 45 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the midpoint for passenger cars versus heavy trucks. The only other statistically

significant difference in speeds was at the PC for opposed versus unopposed passenger cars.

Table 45. Alabama Location #1 before data.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 47.883 9.368 49.208 7.596 50.136 8.725 42.323 6.912 375 88 353

Passenger 

cars

47.917 9.380 49.218 7.540 50.429 8.700 42.516 6.892 362 84 341

Heavy 

trucks 46.923 9.332 48.923 9.394 44.000 7.789 36.833 5.132 13 4 12

Daytime 

passenger 

cars

47.638 9.418 48.805 7.641 50.795 8.551 42.288 6.764 174 39 160

Nighttime 

passenger 

cars

48.176 9.362 49.601 7.444 50.111 8.912 42.718 7.016 188 45 181

Opposed 

passenger 

cars

47.529 10.661 48.793 7.385 46.833 7.648 42.037 6.512 87 24 82

Unopposed 

passenger 

cars

48.040 8.955 49.353 7.596 51.867 8.736 42.668 7.014 275 60 259

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 72 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 72 also shows the mean speed for trucks within 

the study section. The figure shows the speeds for passenger cars increased slightly from the 

control point to the PC and decreased substantially from the PC to the midpoint of the curve. 

The truck mean speeds were relatively consistent from the control point the PC and dropped 

substantially from the PC to the midpoint of the curve. The 85th percentile speeds for passenger 

cars at the control point, the approach, and the PC were higher than the PSL of 55 mph. Only at 

the midpoint of the curve were the 85th percentile speeds for passenger cars lower than the PSL

of 55 mph. The mean speeds and 15th percentile speeds for passenger cars and the truck mean 

speeds along the curve were all lower than the PSL of 55 mph. The mean acceleration rate from 

the PC to the midpoint of the curve was -8.726 ft/s for passenger cars and -6.304 ft/s for trucks. 

A negative value indicates deceleration.

α

123
Figure 72. Graph. Graphical representation of speeds at Alabama Location #1.

Alabama Location #2

This curve was located approximately 0.4 mi upstream of the Alabama Location #1 curve. The 

direction of travel for the data collection was southbound, and the curve direction was to the 

right. The curve approach and curve were located on a downgrade. The radius of curve and the 

curve length, calculated using Google EarthTM, were 272.92 ft and 303.38 ft. respectively. There 

was a substantial cut slope with trees on the inside of the curve, which limited horizontal sight 

distance along the curve. The PSL was 55 mph. As figure 73 shows, there was a winding road

sign (W1-5) with an advisory speed plaque (W13-1P) of 30 mph 175 ft before the PC. The travel 

lanes were 11 ft wide, and there were 2-ft paved shoulders on both sides of the road. There was a 

drainage ditch located on the inside of the curve and guardrail on the outside of the curve with 

chevron markers. 

The research team collected speed data at the control point, 800 ft before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 440 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 73 shows the horizontal curve layout, along with the 

speed data-collection locations.

30

35

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Alabama Location #1

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

124
Figure 73. Diagram. Geometric layout of Alabama Location #2 (not to scale).

125
Table 46 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the control point and approach for passenger cars versus heavy vehicles. There was 

also a statistically significant difference in speeds at the control point, approach, and curve 

midpoint for unopposed passenger cars versus opposed passenger cars.

Table 46. Alabama Location #2 before data.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 49.269 7.604 44.291 5.822 42.472 5.747 38.337 7.101 398 290 359

Passenger 

cars

49.569 7.238 44.479 5.623 42.630 5.554 38.418 7.137 376 273 337

Heavy 

trucks 44.136 11.319 41.091 8.053 39.941 8.050 37.091 6.560 22 17 22

Daytime 

passenger 

cars

49.884 8.070 45.072 5.722 43.263 5.737 37.821 7.802 138 99 123

Nighttime 

passenger 

cars

49.387 6.721 44.134 5.548 42.270 5.432 38.762 6.720 238 174 214

Opposed 

passenger 

cars

47.809 7.949 43.022 6.312 41.721 5.057 36.378 7.241 89 61 82

Unopposed 

passenger 

cars

50.115 6.928 44.930 5.323 42.892 5.674 39.075 6.991 287 212 255

Bold indicates significance at 95 percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 74 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 74 also shows the mean speed for trucks within 

the study section. The figure shows the patterns of the speed changes were similar for the 

passenger car speeds and the truck mean speeds at this curve location. The speeds for passenger 

cars and the truck mean speeds decreased consistently from the control point to the midpoint of 

the curve. The speeds for passenger cars and the truck mean speeds along the curve were lower 

than the PSL of 55 mph but higher than the advisory speed of 30 mph. The mean acceleration 

rate from the PC to the midpoint of the curve was -2.128 ft/s for passenger cars and -2.211 ft/s 

for trucks. A negative value indicates deceleration.

α

126
Figure 74. Graph. Graphical representation of speeds at Alabama Location #2.

Alabama Location #3

The direction of travel for the data collection was southbound, and the curve direction was to the 

right. This curve to the right was part of a reverse curve, with a curve back to the left 

immediately after. The radius of curve and the curve length, calculated using Google EarthTM, 

were 635.15 ft and 545.62 ft, respectively. The PSL was 55 mph. As figure 75 shows, there was 

a winding road sign (W1-5) with an advisory speed plaque (W13-1P) of 35 mph positioned 

460 ft before the PC; there were also chevrons on the outside of the curve. The travel lanes were 

12 ft wide, and there were 2-ft paved shoulders on either side of the road.

The research team collected speed data at the control point, 0.2 mi before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 500 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 75 shows the horizontal curve layout, along with the 

speed data-collection locations. 

20

25

30

35

40

45

50

55

60

Control Pt Approach PC MidPt

Sped (mph)

Alabama Location #2

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

Advisory Speed

127
Figure 75. Diagram. Geometric layout of Alabama Location #3 (not to scale).

128
Table 47 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the approach, PC, and the curve midpoint for passenger cars versus heavy vehicles. 

There was also a statistically significant difference in speeds at the approach for daytime 

passenger cars versus nighttime passenger cars. 

Table 47. Alabama Location #3 before data.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 65.122 13.222 49.842 6.461 41.329 4.665 41.192 5.936 499 474 474

Passenger 

cars

65.372 13.359 50.011 6.519 41.652 4.653 41.691 5.714 441 417 417

Heavy 

trucks 63.224 12.070 48.552 5.891 38.965 4.066 37.544 6.299 58 57 57

Daytime 

passenger 

cars

66.174 13.109 50.566 6.965 41.960 4.681 41.609 6.025 265 248 253

Nighttime 

passenger 

cars

64.165 13.675 49.176 5.702 41.201 4.589 41.817 5.214 176 169 164

Opposed 

passenger 

cars

65.516 13.031 49.979 6.684 41.449 5.061 41.928 6.036 188 176 180

Unopposed 

passenger 

cars

65.265 13.622 50.036 6.408 41.801 4.336 41.511 5.463 253 241 237

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 76 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 76 also shows the mean speed for trucks within 

the study section. As the figure shows, the passenger car speeds and truck mean speeds 

decelerated substantially from the control point to the PC. Both passenger car speeds and the 

truck mean speeds then stabilized from the PC to midpoint of the curve. The passenger car 

speeds and the truck mean speeds along the curve were all higher than the advisory speed of 

35 mph. The mean acceleration rate from the PC to the midpoint of the curve was 0.321 ft/s for 

passenger cars. The truck acceleration rate remained the same from the PC to the midpoint.

α

129
Figure 76. Graph. Graphical representation of speeds at Alabama Location #3.

Alabama Location #4

The direction of travel for the data collection was southbound, and the curve direction was to the 

right. The radius of curve and the curve length, calculated using Google EarthTM, were 236.38 ft 

and 277.70 ft, respectively. There was a substantial cut slope on the inside of the curve, which 

limited horizontal sight distance along the curve. There was guardrail and also chevrons on the 

outside of the curve. The PSL was 35 mph. As Figure 77 shows, there was a turn warning sign 

(W1-1) with an advisory speed plaque (W13-1P) of 20 mph and flashing amber beacons above 

the sign located at the curve approach. The travel lanes were 10 ft wide, and there was no 

shoulder on either side of the road.

The research team collected speed data at the control point, 0.3 mi before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve.

The other one was placed 440 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 77 shows the horizontal curve layout, along with the 

speed data-collection locations. 

30

40

50

60

70

80

90

Control Pt Approach PC MidPt

Sped (mph)

Alabama Location #3

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

Advisory Speed

130
Figure 77. Diagram. Geometric layout of Alabama Location #4 (not to scale).

Table 48 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was only a statistically significant difference 

in speeds at the curve midpoint for passenger cars versus heavy trucks and daytime versus 

nighttime passenger cars.

131
Table 48. Alabama Location #4 before data.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 50.785 9.441 46.478 7.630 39.042 4.961 34.213 9.051 502 478 461

Passenger 

cars

50.660 9.345 46.506 7.597 39.100 4.908 34.038 9.068 480 459 443

Heavy trucks 53.500 11.237 45.864 8.481 37.632 6.103 38.500 7.649 22 19 18

Daytime 

passenger 

cars

50.656 8.996 46.149 8.725 39.462 4.987 32.726 10.008 195 182 179

Nighttime 

passenger 

cars

50.663 9.592 46.751 6.723 38.863 4.849 34.928 8.273 285 277 264

Opposed 

passenger 

cars

51.007 9.307 46.188 9.237 39.053 5.305 33.523 9.955 144 132 128

Unopposed 

passenger 

cars

50.512 9.371 46.643 6.786 39.119 4.746 34.248 8.690 336 327 315

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 78 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 78 also shows the mean speed for passenger cars 

and trucks within the study section. The figure shows the passenger car speeds and truck speeds 

decelerated substantially from the approach to the midpoint of the curve. The passenger car 

speeds and the truck mean speeds along the curve were closer to the 35 mph PSL than the 

advisory speed of 20 mph. The mean acceleration rate from the PC to the midpoint of the curve 

was -0.931 ft/s for passenger cars and -0.183 ft/s for trucks. A negative value indicates 

deceleration. 

α

132
Figure 78. Graph. Graphical representation of speeds at Alabama Location #4.

Alabama Location #5

The direction of travel for the data collection was southbound, and the curve direction was to the 

right. The curve approach and curve were located on a downgrade. This curve to the right was 

part of a reverse curve, with the site for Alabama Location #6 located immediately downstream. 

The radius of curve and the curve length, calculated using Google EarthTM, were 709.81 ft and 

1,059.71 ft, respectively. The PSL was 40 mph. The travel lanes were 9 ft wide, and there was no 

shoulder on either side of the road. 

The research team collected speed data at the control point, 1,000 ft before the curve approach, 

which was 250 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 455 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 79 shows the horizontal curve layout, along with the 

speed data-collection locations. 

10

20

30

40

50

60

70

Control Pt Approach PC MidPt

Speed (mph)

Alabama Location #4

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

Advisory Speed

133
Figure 79. Diagram. Geometric layout of Alabama Location #5 (not to scale).

Table 49 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the control point, approach, and the curve midpoint for daytime versus nighttime 

passenger cars. There was also a statistically significant difference in speeds at the PC and 

midpoint of the curve for opposed versus unopposed passenger cars. 

134
Table 49. Alabama Location #5 before data.

Speed Metric

Control 

Point 

Speed

Control 

Point SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 41.944 7.212 43.742 8.327 45.781 7.524 39.810 6.842 233 64 221

Passenger 

cars

42.299 7.094 44.054 8.250 45.794 7.584 40.028 6.782 224 63 212

Heavy trucks 33.111 3.822 36.000 6.614 45.000 N/A 34.667 6.557 9 1 9

Daytime 

passenger 

cars

41.947 6.887 44.405 7.941 45.619 7.450 39.787 6.772 131 42 122

Nighttime 

passenger 

cars

42.796 7.383 43.559 8.686 46.143 8.021 40.356 6.821 93 21 90

Opposed 

passenger 

cars

40.235 7.242 41.353 11.045 38.833 7.333 34.933 7.045 17 6 15

Unopposed 

passenger 

cars

42.469 7.072 44.275 7.972 46.526 7.290 40.416 6.621 207 57 197

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

N/A = Not Applicable

Figure 80 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 80 also shows the mean speed for trucks within 

the study section. As the figure shows, the speeds for passenger cars and the truck mean speeds 

gradually increased from the control point to the PC of the curve and decreased from the PC to 

the midpoint of the curve. The 85th percentile speeds of passenger cars along the curve were 

higher than the PSL of 40 mph. The mean acceleration rate from the PC to the midpoint of the 

curve was -7.817 ft/s for passenger cars and -0.369 ft/s for trucks. A negative value indicates 

deceleration.

α

135
Figure 80. Graph. Graphical representation of speeds at Alabama Location #5.

Alabama Location #6

This curve to the right was part of a reverse curve associated with the site for Alabama Location 

#5 located immediately upstream. The direction of travel for the data collection was northbound,

and the curve direction was to the right. The radius of curve and the curve length, calculated 

using Google EarthTM, were 710.84 ft and 885.08 ft, respectively. At the midpoint of the curve,

the curve starts to go upgrade with a driveway located on the outside of the curve. The PSL was

40 mph. The travel lanes were approximately 9 ft wide, and there was no shoulder on either side 

of the road.

The research team collected speed data at the control point, 750 ft before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 490 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 81 shows the horizontal curve layout, along with the 

speed data-collection locations.

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Alabama Location #5

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

136
Figure 81. Diagram. Geometric layout of Alabama Location #6 (not to scale).

Table 50 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

curve location. For this treatment site, there was a statistically significant difference in speeds at 

the approach for passenger cars versus heavy trucks. There was also a statistically significant 

difference at the PC for opposed versus unopposed passenger cars.

137
Table 50. Alabama Location #6 before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 43.386 9.196 45.081 7.189 46.442 6.431 45.031 8.436 197 86 98

Passenger 

cars

43.370 9.277 45.402 6.928 46.447 6.469 45.128 8.568 189 85 94

Heavy trucks 43.750 7.498 37.500 9.457 46.000 N/A 42.750 4.272 8 1 4

Daytime 

passenger 

cars

43.462 9.112 45.400 6.716 46.586 6.489 44.317 9.561 130 58 63

Nighttime 

passenger 

cars

43.169 9.708 45.407 7.433 46.148 6.538 46.774 5.869 59 27 31

Opposed 

passenger 

cars

41.056 7.565 42.944 10.067 43.400 4.881 46.750 4.070 18 10 12

Unopposed 

passenger 

cars

43.614 9.425 45.661 6.499 46.853 6.571 44.890 9.032 171 75 82

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint

N/A = Not Applicable

Figure 82 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 82 also shows the mean speed for trucks within 

the study section. The figure shows that the 85th percentile and the mean speeds for passenger 

cars remain relatively stable from the control point to the midpoint of the curve. The 15th

percentile speeds for passenger cars increased substantially from the control point to the 

approach of the curve and stabilized from the approach to the midpoint of the curve. The truck 

mean speeds were not consistent; the speeds decreased from the control point to the approach of 

the curve and increased from the approach to the PC and then decreased from the PC to the 

midpoint of the curve. The 85th percentile speeds and the mean speeds for passenger and the 

truck mean speeds along the curve were all higher than the PSL of 40 mph. The mean 

acceleration rate from the PC to the midpoint of the curve was 0.627 ft/s for passenger cars and -

1.038 ft/s for trucks. A negative value indicates deceleration.

α

138
Figure 82. Graph. Graphical representation of speeds at Alabama Location #6.

Alabama Location #7

This curve to the right was part of a reverse curve, with a curve back to the left immediately 

after. The direction of travel for the data collection was southbound, and the curve direction was 

to the right. The white edge lines and yellow centerline were severely faded on the tangent and 

throughout the curve. The radius of curve and the curve length, calculated using Google EarthTM, 

were 601.93 ft and 456.89 ft, respectively. The PSL was 35 mph. The travel lanes were 10 ft 

wide, and there was no shoulder on either side of the road. There was a driveway located on the 

right side of the road approximately 100 ft before the PC. As figure 83 shows, there was a 

SCHOOL BUS STOP AHEAD sign (S3-1), with a REDUCED SPEED AHEAD sign (R2-5)

above it, located on the curve approach. There was also a winding road sign (W1-5) with a speed 

limit sign (R2-1) of 35 mph 250 ft before the PC.

The research team collected speed data at the control point, 0.3 mi before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 450 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 83 shows the horizontal curve layout, along with the 

speed data-collection locations.

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Alabama Location #6

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

139
Figure 83. Diagram. Geometric layout of Alabama Location #7 (not to scale).

Table 51 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team also conducted simple t-tests for each of these comparisons at 

each curve location. For this treatment site, there was a statistically significant difference in 

speeds at the control point for passenger cars versus heavy vehicles. There was also a statistically 

significant difference in speeds at the approach and PC for daytime versus nighttime passenger 

cars. 

140
Table 51. Alabama Location #7 before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 52.977 9.890 43.666 5.396 36.953 4.288 38.806 5.266 431 423 422

Passenger cars 52.850 9.896 43.653 5.388 36.973 4.305 38.755 5.239 421 413 412

Heavy trucks 58.300 8.433 44.200 6.033 36.100 3.604 40.900 6.208 10 10 10

Daytime 

passenger cars

53.000 9.668 44.420 5.224 37.647 4.536 39.188 5.310 193 190 191

Nighttime 

passenger cars

52.724 10.104 43.004 5.450 36.399 4.020 38.380 5.160 228 223 221

Opposed 

passenger cars

52.148 8.668 43.241 5.701 36.657 4.310 38.355 4.989 108 105 107

Unopposed 

passenger cars

53.093 10.287 43.796 5.277 37.081 4.306 38.895 5.325 313 308 305

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 84 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 84 also shows the mean speed for trucks within 

the study section. As the figure shows, the passenger car speeds and the truck mean speeds 

decelerated substantially from the control point to the PC of the curve. Passenger car speeds and 

the truck mean speeds remained relatively constant from the PC through the curve, averaging 

between 35 and 40 mph. The 85th percentile speeds and mean speeds of passenger cars and the 

truck mean speeds along the curve were higher than the PSL of 35 mph. The mean acceleration 

rate from the PC to the midpoint of the curve was 0.885 ft/s for passenger cars and 0.713 ft/s for 

trucks.

α

141
Figure 84. Graph. Graphical representation of speeds at Alabama Location #7.

Alabama Location #8

This curve was located approximately 1,000 ft downstream of Alabama Location #7 in the 

opposite direction. The direction of travel for the data collection was northbound, and the curve 

direction was to the right. There was a cut slope on the inside of the curve, which partially 

restricted horizontal sight distance entering the curve. The white edge lines and yellow centerline 

were severely faded on the tangent and throughout the curve. The radius of curve and the curve 

length, calculated using Google Earth, were 486.26 ft and 222.95 ft, respectively. The PSL was

35 mph. The travel lanes were 10 ft wide and there was no shoulder on either side of the road. 

There was a driveway on the outside of the curve at the midpoint. As figure 85 shows, there was 

a winding road sign (W1-5) with a speed limit sign (R2-1) of 35 mph located 700 ft before the 

curve approach. The end of a 280 ft concrete bridge crossing a ravine ended approximately 

180 ft before the PC.

The research team collected speed data at the control point, 1,500 ft before the curve approach, 

which was 500 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

The other one was placed 415 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 85 shows the horizontal curve layout, along with the 

speed data-collection locations. 

30

35

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Alabama Location #7

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

142
Figure 85. Diagram. Geometric layout of Alabama Location #8 (not to scale).

143
Table 52 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team again performed a simple t-test for each of these comparisons at 

each curve location. For this treatment site, there was a statistically significant difference in 

speeds at the PC and curve midpoint for passenger cars versus heavy vehicles. There was also a 

statistically significant difference in speeds at the control point for daytime versus nighttime 

passenger cars. There was also a statistically significant difference in speeds at the approach for 

opposed versus unopposed passenger cars.

Table 52. Alabama Location #8 before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 41.540 6.029 44.644 8.437 40.661 5.324 42.266 6.329 376 342 312

Passenger cars 41.566 6.053 44.672 8.317 40.754 5.326 42.375 6.337 366 334 304

Heavy trucks 40.600 5.254 43.600 12.624 36.750 3.655 38.125 4.612 10 8 8

Daytime 

passenger cars

43.145 5.833 44.612 8.251 40.842 4.928 42.401 5.908 165 146 137

Nighttime 

passenger cars

40.269 5.934 44.721 8.391 40.686 5.628 42.353 6.686 201 188 167

Opposed 

passenger cars

41.750 6.708 42.841 7.546 40.823 6.354 42.000 7.255 88 79 71

Unopposed 

passenger cars

41.507 5.842 45.252 8.477 40.733 4.979 42.489 6.042 278 255 233

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 86 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 86 also shows the mean speed for trucks within 

the study section. As the figure shows, the patterns of the speed changes were similar for the 

passenger car speeds and the truck mean speeds at this curve location. The speeds for passenger 

cars and the truck mean speeds increased from the control point to the approach of the curve,

decreased from the approach to the PC of the curve, and then increased again from the PC to the 

midpoint of the curve. The speeds of passenger cars and the truck mean speeds along the curve 

were both higher than the PSL of 35 mph. The mean acceleration rate from the PC to the 

midpoint of the curve was 1.94 ft/s for passenger cars and -0.153 ft/s for trucks. A negative value 

indicates deceleration.

α

144
Figure 86. Graph. Graphical representation of speeds at Alabama Location #8.

Massachusetts

This section describes the characteristics of the seven treatment sites in Massachusetts.

Southbound Tucker Road, MA

The research team collected data on Tucker Road in Dartmouth, MA. The direction of travel for 

the data collection was southbound, and the curve direction was to the right. The radius of curve 

and the curve length, calculated using Google EarthTM, were 1,098.66 ft and 816.67 ft, 

respectively. The PSL was 30 mph. The travel lanes were 13 ft wide, and there was no shoulder 

on either side of the road. 

The team collected speed data at the control point, 0.2 mi before the curve approach, which was 

319 ft before the PC. The research team also collected speed data at the PC and midpoint of the 

curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve, and 

the other one was placed 347 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 87 shows the horizontal curve layout, along with the 

speed data-collection locations. 

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Alabama Location #8

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

145
Figure 87. Diagram. Geometric layout of southbound Tucker Road (not to scale).

146
Table 53 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the control point and PC for passenger cars versus heavy trucks. There also was a 

statistically significant difference in speeds at the control point for daytime versus nighttime 

passenger cars, and also at the approach for opposed versus unopposed passenger cars.

Table 53. Southbound Tucker Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 44.458 7.485 36.492 5.228 35.223 4.467 35.329 5.014 577 539 514

Passenger cars 44.466 7.510 36.506 5.236 35.241 4.475 35.334 5.022 573 535 512

Heavy trucks 43.250 0.957 34.500 3.873 32.750 2.500 34.000 1.414 4 4 2

Daytime 

passenger cars

45.136 6.983 36.782 5.064 35.488 4.127 35.420 4.809 316 293 286

Nighttime 

passenger cars

43.642 8.048 36.167 5.431 34.942 4.855 35.226 5.289 257 242 226

Opposed 

passenger cars

44.306 7.210 36.972 5.543 35.272 3.792 35.036 5.203 252 235 224

Unopposed 

passenger cars

44.592 7.745 36.140 4.960 35.217 4.951 35.566 4.874 321 300 288

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 88 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 88 also shows the mean speed for trucks within 

the study section. As the figure shows, the passenger car speeds and truck speeds decelerated

substantially from the control point to the approach of the curve. Both passenger car speeds and 

the truck mean speeds were relatively stable with minimal speed changes between the approach

and the midpoint of the curve. The mean acceleration rate from the PC to the midpoint of the 

curve was 0.604 ft/s for passenger cars and 2.7 ft/s for trucks. 

α

147
Figure 88. Graph. Graphical representation of speeds on southbound Tucker Road.

Northbound Tucker Road, MA

This curve was located approximately 0.9 mi upstream of the southbound Tucker Road curve. 

The direction of travel for the data collection was northbound, and the curve direction was to the 

left. This curve to the left was part of a reverse curve, with a curve back to the right. The radius 

of curve and the curve length, calculated using Google EarthTM, were 568.76 ft and 293.24 ft, 

respectively. The PSL was 35 mph. The travel lanes were 12 ft wide, and there was no shoulder 

on either side of the road. There was a winding road sign (W1-5) located approximately 125 ft

before the PC. An advisory speed plaque (W13-1P) of 25 mph was located approximately 100 ft 

upstream of the winding road sign. As figure 89 shows, there was one chevron on the outside of 

the curve at approximately the curve midpoint.

The research team collected speed data at the control point, 0.4 mi before the curve approach, 

which was 270 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 262 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 89 shows the horizontal curve layout, along with the 

speed data-collection locations.

20

25

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Southbound Tucker Rd

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

148
Figure 89. Diagram. Geometric layout of northbound Tucker Road (not to scale).

149
Table 54 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the control point, approach, and PC for passenger cars versus heavy trucks, with the 

heavy truck speed lower at these points. There also was a statistically significant difference in 

speeds at the PC and curve midpoint for daytime versus nighttime passenger cars. There also was 

a difference at the curve midpoint for opposed versus unopposed passenger cars.

Table 54. Northbound Tucker Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 33.895 4.361 37.609 4.247 33.381 3.820 35.507 4.852 573 565 458

Passenger cars 33.919 4.361 37.633 4.251 33.403 3.820 35.525 4.858 569 561 455

Heavy trucks 30.500 3.000 34.250 1.500 30.250 2.500 32.667 3.055 4 4 3

Daytime 

passenger cars

34.135 4.263 37.768 4.219 33.683 3.551 36.145 4.549 341 338 276

Nighttime 

passenger cars

33.596 4.495 37.430 4.300 32.978 4.167 34.570 5.168 228 223 179

Opposed 

passenger cars

33.681 4.172 37.453 4.207 33.369 3.635 35.839 4.758 351 347 280

Unopposed 

passenger cars

34.303 4.634 37.922 4.315 33.458 4.111 35.023 4.986 218 214 175

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 90 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 90 also shows the mean speed for trucks within 

the study section. As the figure shows, the patterns of the speed changes were similar for the 

passenger car speeds and the truck mean speeds at this curve location. The speeds for passenger 

cars and the truck mean speeds increased from the control point to the approach of the curve,

decreased from the approach to the PC of the curve, and then increasing again from the PC to the 

midpoint of the curve. The speeds for passenger cars and the truck mean speeds along the curve 

were both higher than the PSL of 30 mph. The mean acceleration rate from the PC to the 

midpoint of the curve was 2.928 ft/s for passenger cars and 2.35 ft/s for trucks. A negative value 

indicates deceleration.

α

150
Figure 90. Graph. Graphical representation of speeds on northbound Tucker Road.

Southbound Reed Road, MA

The research team collected data on Reed Road in Dartmouth, MA. The direction of travel for 

the data collection was southbound and the curve direction was to the left. The radius of curve 

and the curve length, calculated using Google EarthTM, were 683.31 ft and 458.56 ft, 

respectively. The PSL was 40 mph until 150 ft before the curve approach, where it changed to 

25 mph. The travel lanes were 13 ft wide, and there was a 4-ft shoulder on both sides of the road. 

As figure 91 shows, there was a curve warning sign (W1-2) located between the curve approach 

and the PC. There were also three chevrons on the outside of the curve. 

The team collected speed data at the control point, 0.3 mi before the curve approach, which was 

431 ft before the PC. The research team also collected speed data at the PC and midpoint of the 

curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve, and 

the other one was placed 311 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 91 shows the horizontal curve layout, along with the 

speed data-collection locations.

20

25

30

35

40

45

Control Pt Approach PC MidPt

Speed (mph)

Northbound Tucker Rd

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

Advisory Speed

151
Figure 91. Diagram. Geometric layout of southbound Reed Road (not to scale).

152
Table 55 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was only a statistically significant difference 

in speeds at the control point and approach speed for passenger cars versus heavy trucks, with 

the heavy truck speed lower at these points.

Table 55. Southbound Reed Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

Observations 39.966 5.426 39.382 6.015 38.826 4.288 39.363 4.990 775 482 590

Passenger 

cars

40.036 5.395 39.450 5.985 38.811 4.227 39.416 4.945 756 471 575

Heavy trucks 37.211 6.070 36.684 6.758 39.455 6.654 37.333 6.355 19 11 15

Daytime 

passenger 

cars

39.754 5.282 39.249 6.262 38.558 3.773 39.692 4.767 337 224 247

Nighttime 

passenger 

cars

40.263 5.481 39.611 5.754 39.040 4.596 39.207 5.072 419 247 328

Opposed 

passenger 

cars

39.971 5.365 39.753 6.653 38.669 3.911 39.469 4.916 377 242 275

Unopposed 

passenger 

cars

40.100 5.432 39.148 5.227 38.961 4.542 39.367 4.979 379 229 300

Bold indicates significance at 95 percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 92 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 92 also shows the mean speed for trucks within 

the study section. The figure shows that the speeds for passenger cars remained relatively stable 

along the curve, and the speed changes were minimal. The truck mean speeds increased slightly 

from the control point to the PC and decreased slightly from the PC to the midpoint of the curve. 

The passenger car speeds and the truck mean speeds along the curve were higher than the PSL of 

25 mph, averaging between 37 to 39 mph. The mean acceleration rate from the PC to the 

midpoint of the curve was -0.092 ft/s for passenger cars and -1.863 ft/s for trucks. A negative 

value indicates deceleration.

α

153
Figure 92. Graph. Graphical representation of speeds on southbound Reed Road.

Southbound New Boston Road, MA

The research team collected data on New Boston Road in Fairhaven, MA. The direction of travel 

for the data collection was southbound, and the curve direction was to the left. The radius of 

curve and the curve length, calculated using Google EarthTM, were 592.52 ft and 226.37 ft, 

respectively. The PSL was 35 mph. The travel lanes were 11 ft wide, and there was no shoulder 

on either side of the road.

The team collected speed data at the control point, 0.2 mi before the curve approach, which was 

530 ft before the PC. The research team also collected speed data at the PC and midpoint of the 

curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve, and 

the other one was placed 460 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 93 shows the horizontal curve layout, along with the 

speed data-collection locations. 

20

25

30

35

40

45

50

Control Pt Approach PC MidPt

Speed (mph)

Southbound Reed Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

154
Figure 93. Diagram. Geometric layout of southbound New Boston Road (not to scale).

155
Table 56 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at curve midpoint for passenger cars versus heavy trucks. There also was a statistically 

significant difference in speeds at the control point and approach for opposed versus unopposed 

passenger cars.

Table 56. Southbound New Boston Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 37.004 6.532 37.704 5.967 37.489 5.607 36.624 6.206 257 229 229

Passenger cars 36.968 6.565 37.766 5.980 37.465 5.636 36.656 6.224 252 226 227

Heavy trucks 38.800 4.712 34.600 4.722 39.333 2.082 33.000 0.000 5 3 2

Daytime 

passenger cars

36.690 5.930 37.655 5.583 37.576 4.603 36.760 5.551 113 99 100

Nighttime 

passenger cars

37.194 7.052 37.856 6.302 37.378 6.343 36.575 6.728 139 127 127

Opposed 

passenger cars

35.638 5.307 36.259 5.872 36.788 5.410 35.962 6.145 58 52 52

Unopposed 

passenger cars

37.366 6.859 38.216 5.953 37.667 5.702 36.863 6.250 194 174 175

Bold indicates significance at the 95-percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 94 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 94 also shows the mean speed for trucks within 

the study section. The figure shows that the speeds for passenger cars remained relatively stable 

along the curve, and the speed changes were minimal. The truck mean speeds decreased slightly 

between the control point and the approach of the curve, increased significantly from the 

approach to the PC of the curve, and then decreased substantially from the PC to the midpoint of 

the curve. The 85th percentile speeds and the mean speeds for passenger cars along the curve 

were higher than the PSL of 35 mph. The mean acceleration rate from the PC to the midpoint of 

the curve was -0.490 ft/s for passenger cars and -0.960 ft/s for trucks. A negative value indicates 

deceleration.

α

156
Figure 94. Graph. Graphical representation of speeds on southbound New Boston Road.

Northbound New Boston Road, MA

This curve was located approximately 800 ft downstream of the southbound New Boston Road 

curve. The direction of travel for the data collection was northbound, and the curve direction was 

to the right. The radius of curve and the curve length, calculated using Google EarthTM, were 

470.83 ft and 186.21 ft, respectively. The PSL was 35 mph. The travel lanes were 11 ft wide, and 

there was no shoulder on either side of the road.

The research team collected speed data at the control point, 0.4 mi before the curve approach, 

which was 470 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 464 ft downstream of the first sensor to determine whether vehicles

were present in the opposing lane. Figure 95 shows the horizontal curve layout, along with the 

speed data-collection locations. 

20

25

30

35

40

45

Control Pt Approach PC MidPt

Speed (mph)

Southbound New Boston Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

157
Figure 95. Diagram. Geometric layout of northbound New Boston Road (not to scale).

158
Table 57 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the control point and approach for passenger cars versus heavy trucks, with the truck 

speed lower at these points. There also was a statistically significant difference in speeds at the 

curve midpoint for daytime versus nighttime passenger cars.

Table 57. Northbound New Boston Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 39.796 5.704 36.876 5.691 39.500 4.955 33.742 6.553 225 114 209

Passenger cars 39.857 5.680 36.928 5.686 39.558 4.939 33.720 6.563 223 113 207

Heavy trucks 33.000 5.657 31.000 2.828 33.000 N/A 36.000 7.071 2 1 2

Daytime 

passenger cars

40.074 5.352 37.475 5.801 40.066 4.694 34.627 6.531 122 61 110

Nighttime 

passenger cars

39.594 6.070 36.267 5.499 38.962 5.194 32.691 6.478 101 52 97

Opposed 

passenger cars

40.119 4.835 36.810 4.830 39.714 3.989 32.789 4.911 42 21 38

Unopposed 

passenger cars

39.796 5.870 36.956 5.878 39.522 5.149 33.929 6.874 181 92 169

Bold indicates significance at 95 percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint

N/A = Not Applicable

Figure 96 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 96 also shows the mean speed for trucks within 

the study section. The figure shows that the speeds for passenger cars remained relatively stable 

from the control point to the PC of the curve, but decreased substantially from the PC to the 

midpoint of the curve. The truck mean speeds decreased slightly from the control point to the 

approach of the curve and increased slightly from the approach through the curve. The 85th

percentile speeds for passenger cars along the curve were higher than the PSL of 35 mph. The 

mean acceleration rate from the PC to the midpoint of the curve was -5.478 ft/s for passenger 

cars and -0.2 ft/s for trucks. A negative value indicates deceleration.

α

159
Figure 96. Graph. Graphical representation of speeds on northbound New Boston Road.

Southbound Braley Hill Road, MA

The research team collected data on Braley Hill Road in Rochester, MA. The direction of travel 

for the data collection was southbound, and the curve direction was to the right. The radius of 

curve and the curve length, calculated using Google EarthTM, were 695.24 ft and 672.97 ft, 

respectively. There were trees and other growth on the inside of the curve, which partially 

restricted horizontal sight distance. The PSL was 30 mph. The travel lanes were 11 ft wide, and 

there was no shoulder on either side of the road. As figure 97 shows, there was a Dangerous 

Curves sign with a 30-mph speed limit sign (R2-1) located between the curve approach and the 

PC. 

The research team collected speed data at the control point, 0.4 mi before the curve approach, 

which was 461 ft before the PC. The team also collected speed data at the PC and midpoint of 

the curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve,

and the other one was placed 410 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 97 shows the horizontal curve layout, along with the 

speed data-collection locations. 

20

25

30

35

40

45

50

Control Pt Approach PC MidPt

Speed (mph)

Northbound New Boston Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

160
Figure 97. Diagram. Geometric layout of southbound Braley Hill Road (not to scale).

161
Table 58 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the control point and approach for passenger cars versus heavy vehicles, with the truck 

speed lower at these points. There also was a statistically significant difference in speeds at the 

control point, approach, and curve midpoint for daytime versus nighttime passenger cars, with 

the nighttime speeds higher at these points. There also was a statistically significant difference in 

speeds at the curve midpoint for opposed versus unopposed passenger cars. 

Table 58. Southbound Braley Hill Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 39.360 5.097 38.508 5.835 34.585 4.791 36.365 6.947 317 294 252

Passenger cars 39.472 5.136 38.600 5.872 34.665 4.693 36.502 6.905 305 284 243

Heavy trucks 36.500 2.844 36.167 4.345 32.300 6.977 32.667 7.483 12 10 9

Daytime 

passenger cars

38.640 4.423 37.953 4.997 34.433 4.591 35.697 7.398 150 141 122

Nighttime 

passenger cars

40.277 5.640 39.226 6.566 34.895 4.797 37.314 6.297 155 143 121

Opposed 

passenger cars

39.211 4.485 37.958 5.247 34.758 4.736 35.185 6.355 71 66 54

Unopposed 

passenger cars

39.551 5.324 38.795 6.046 34.638 4.691 36.878 7.025 234 218 189

Bold indicates significance at 95 percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 98 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 98 also shows the mean speed for trucks within 

the study section. The figure shows that the 85th percentile speeds and the mean speeds for 

passenger cars decreased slightly from the control point to the PC and then increased from the 

PC to the midpoint of the curve. The 15th percentile speeds of passenger car decreased slightly 

along the curve. The truck mean speeds increased slightly between the control point and the 

approach of the curve, decreased from the approach to the PC of the curve, and then increased 

significantly from the PC to the midpoint of the curve. The passenger car speeds and the truck 

mean speeds along the curve were higher than the PSL of 30 mph. The mean acceleration rate 

from the PC to the midpoint of the curve was 3.544 ft/s for passenger cars and 4.908 ft/s for 

trucks. 

α

162
Figure 98. Graph. Graphical representation of speeds on southbound Braley Hill Road.

Northbound Braley Hill Road, MA

The northbound Braley Hill Road curve was located approximately 0.4 mi downstream of the 

southbound Braley Hill Road curve. The curve is located at the start of a broken back curve and 

compound curve. The direction of travel for the data collection was northbound, and the curve 

direction was to the right. The radius of curve and the curve length, calculated using Google 

EarthTM, were 2,097.07 ft and 661.74 ft, respectively. There were trees and other growth 

approximately 5 to 10 ft off the inside of the curve, but horizontal sight distance was not 

restricted because of the large radius. The PSL was 40 mph. The travel lanes were 10 ft wide,

and there was no shoulder on either side of the road. There were driveways spaced 

approximately 100 to 400 ft on both sides of the road on the curve approach and on the left side 

throughout the curve.

The research team collected speed data at the control point, 0.4 mi before the curve approach, 

which was 575 ft before the PC. Speed data were also collected at the PC and midpoint of the 

curve. One sensor in the opposing direction of travel was placed at the midpoint of the curve, and 

the other one was placed 415 ft downstream of the first sensor to determine whether vehicles 

were present in the opposing lane. Figure 99 shows the horizontal curve layout, along with the 

speed data-collection locations.

20

25

30

35

40

45

50

Control Pt Approach PC MidPt

Speed (mph)

Southbound Braley Hill Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

163
Figure 99. Diagram. Geometric layout of northbound Braley Hill Road (not to scale).

164
Table 59 shows the speed data for the before period. The data are shown as all observations, 

passenger car versus heavy trucks, daytime versus nighttime speeds for passenger cars, and 

opposed versus unopposed passenger cars. All of the comparisons exclude vehicles with high 

accelerations. The research team performed a simple t-test for each of these comparisons at each 

of the curve locations. For this treatment site, there was a statistically significant difference in 

speeds at the approach, PC, and curve midpoint for passenger cars versus heavy vehicles, with 

the truck speeds lower at these points.

Table 59. Northbound Braley Hill Road before data.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 44.188 7.842 38.650 4.290 37.565 3.981 38.530 3.990 277 271 268

Passenger cars 44.169 7.738 38.692 4.294 37.603 3.993 38.572 3.992 273 267 264

Heavy trucks 45.500 15.022 35.750 3.096 35.000 1.826 35.750 3.096 4 4 4

Daytime 

passenger cars

44.238 6.538 38.524 4.084 37.431 3.703 38.565 3.823 147 144 147

Nighttime 

passenger cars

44.087 8.965 38.889 4.536 37.805 4.315 38.581 4.210 126 123 117

Opposed 

passenger cars

43.794 7.456 38.730 4.178 36.983 4.312 38.381 4.046 63 60 63

Unopposed 

passenger cars

44.281 7.835 38.681 4.338 37.783 3.889 38.632 3.983 210 207 201

Bold indicates significance at 95 percent confidence level ( =0.05) 

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint 

Figure 100 shows the observed mean, 15th percentile, and 85th percentile operating speeds for 

passenger cars along the study section. Figure 100 also shows the mean speed for trucks within 

the study section. As the figure shows, the passenger car speeds and truck speeds decelerated 

from the control point to the approach of the curve and then stabilized from the approach to 

midpoint of the curve. The 85th percentile speeds for passenger cars along the curve were higher 

than the PSL of 40 mph. Both the passenger car and truck mean speeds along the curve were 

lower than the PSL of 40 mph. The mean acceleration rate from the PC to the midpoint of the 

curve was 0.634 ft/s for passenger cars and 0.425 ft/s for trucks. 

α

165
Figure 100. Graph. Graphical representation of speeds on northbound Braley Hill Road.

COMPARISON OF BEFORE AND AFTER PERIOD SPEED DATA

After applying the OSBs, the research team collected the first after period data in Arizona in 

November 2012 and the second after period data in April 2013. In Massachusetts, the research 

team collected after period data in December 2012. In Alabama, the research team collected the 

first after period data in October 2013 and the second after period data in December 2013. The 

following sections describe the results of statistical comparisons between the before and after

conditions at these sites.

Before beginning the data analysis, the research team screened all raw data to exclude vehicles 

that could not be tracked completely from the control point to the curve midpoint. The analysis 

considered only free-flow vehicles. As previously defined, a vehicle was considered free-flow if 

it had headway of 5 s or greater. It was anticipated that vehicles present in the opposing travel 

lane would influence the speed of free-flow vehicles in the subject travel lane; therefore, the 

research team added an indicator variable to the data files to identify free-flow vehicles in the 

subject travel lane that were measured in the presence of an opposing vehicle. Missing data 

values were excluded from the analysis. Data points considered outliers were carefully evaluated 

to determine whether they should be eliminated or included in the analysis. Examples of outliers 

include vehicles traveling at very low speeds prior to entering or exiting nearby driveways.

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Northbound Braley Hill Road

PC 15th Percentile

PC Mean Speed

PC 85th Percentile

Truck Mean Speed

PSL

166
Mean Operating Speeds

After data screening, the research team calculated mean operating speeds at each sensor location 

for all sites and all data-collection periods. The research team also performed an initial 

comparison between corresponding speed parameters at each site for each data-collection period 

by calculating the numerical differences in these speed parameters. The t-statistic for 

independent samples was then applied to determine if the differences in mean speeds were

statistically significant. The mean operating speed comparisons were identified for each datacollection site, organized by the State.

Arizona

This section of the report presents the before-after comparisons for the four Arizona OSB sites. 

Northbound Pierce Ferry Road, AZ

As table 60 shows, in the first after period at northbound Pierce Ferry Road, operating speeds 

remained the same for most metrics. The only metric that changed at the control point was 

nighttime passenger car speeds, which decreased by approximately 3.6 mph, while all other 

metrics did not change from the before to after period. The speeds at the other data-collection 

points remained the same for nighttime passenger cars. The only other significant differences 

between the before and first after period were daytime passenger cars and unopposed passenger 

cars speeds at the curve midpoint, which decreased by approximately 1.4 and 1.5 mph, 

respectively.

In the second after period, there were several additional significant changes between the before

and second after period and between the two after periods. The only change at the control point 

was for opposed passenger cars, where speeds significantly increased by 3.1 mph in the second 

after period from the first after period. The speeds at the approach significantly increased for the 

following speed metrics: all observations, passenger cars, heavy trucks, nighttime passenger cars, 

and unopposed passenger cars, with speed increases of 1.7, 1.4, 6.8, 4.4, and 1.4 mph, 

respectively. Despite these significant increases at the approach, the speeds at the PC 

significantly decreased for all speed metrics, except for heavy trucks. These reductions ranged 

from approximately 4.6 to 5.6 mph. However, these reductions were not maintained throughout 

the curve, and speeds actually significantly increased at the curve midpoint for all speed metrics. 

These increases ranged from approximately 5.1 to 11.0 mph. 

Overall, the OSBs significantly reduced speeds at the PC (end of the OSB), but these reductions 

were not observed throughout the curve, and speeds actually increased at the curve midpoint 

after the application of the OSBs. It is possible that drivers adjusted their speeds upward to 

compensate for the slower speeds on the approach to the curve.

167
Table 60. Before-after operating speeds at northbound Pierce Ferry Road.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

48.532 7.764 46.165 8.162 46.432 6.817 38.056 6.841 218 176 214

All 

observations 

1st after

48.777 8.326 47.179 8.799 46.416 7.597 37.233 6.347 296 173 288

All 

observations 

2nd after

49.318 7.503 47.860 6.765 41.763 4.879 44.271 6.737 258 253 240

Passenger 

cars before 48.867 7.565 46.793 7.855 46.789 6.628 38.513 6.739 203 166 199

Passenger 

cars 1st after 49.411 8.095 47.863 8.559 46.873 7.625 37.536 6.327 270 157 263

Passenger 

cars 2nd after 49.868 7.405 48.209 6.768 41.969 4.943 44.395 6.954 234 229 218

Heavy trucks 

before 44.000 9.220 37.667 7.697 40.500 7.546 32.000 5.237 15 10 15

Heavy trucks 

1st after 42.192 7.965 40.077 8.236 41.938 5.802 34.040 5.755 26 16 25

Heavy trucks 

2nd after 43.958 6.355 44.458 5.831 39.792 3.753 43.045 3.885 24 24 22

Daytime 

passenger 

cars before

49.577 7.116 47.521 7.429 47.669 6.277 39.271 6.744 142 118 140

Daytime 

passenger 

cars 1st after

50.353 7.825 48.263 8.303 47.519 7.133 37.836 6.204 232 129 225

Daytime 

passenger 

cars 2nd after

50.117 7.318 48.089 6.534 42.133 4.912 44.414 6.913 214 211 198

Nighttime 

passenger 

cars before

47.213 8.347 45.098 8.594 44.625 7.028 36.712 6.430 61 48 59

Nighttime 

passenger 

cars 1st after

43.658 7.390 45.421 9.747 43.893 9.138 35.763 6.832 38 28 38

Nighttime 

passenger 

cars 2nd after

47.200 7.997 49.500 9.012 40.056 5.047 44.200 7.537 20 18 20

Opposed 

passenger 

cars before

47.806 6.122 46.444 8.833 47.621 7.683 38.029 6.671 36 29 35

Opposed 

passenger 

cars 1st after

49.787 8.172 47.872 7.881 47.536 7.923 39.370 6.839 47 28 46

Opposed 

passenger 

cars 2nd after

50.870 7.589 48.130 7.055 41.981 5.443 43.731 6.754 54 52 52

168
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Unopposed 

passenger 

cars before

49.096 7.838 46.868 7.655 46.613 6.400 38.616 6.769 167 137 164

Unopposed 

passenger 

cars 1st after

49.332 8.096 47.861 8.712 46.729 7.583 37.147 6.160 223 129 217

Unopposed 

passenger 

cars 2nd after

49.567 7.344 48.233 6.700 41.966 4.803 44.602 7.023 180 177 166

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before 

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 101 shows a graphical representation of the speed profiles for northbound Pierce Ferry 

Road. At the approach point and PC, the general shape of the speed profiles for the three 

collection periods remained relatively similar. At the midpoint, the mean and 85th percentile 

speeds showed an increase in the second after period.

Figure 101. Graph. Operating speeds comparison on northbound Pierce Ferry Road

(PSL = 55 mph).

α

α

30

35

40

45

50

55

60

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds 

(Northbound Pierce Ferry Road)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th

Percentile Speed

169
Southbound Shinarump Road, AZ

Table 61 shows speeds increased at the control point for the following speed metrics: all 

observations, passenger cars, nighttime passenger cars, and unopposed passenger cars, with the 

increases being 1.2, 1.4, 2.2, and 1.4 mph, respectively. All observations and heavy truck speeds 

decreased at the control point by 1.4 and 5.8 mph, respectively. The only other change in the first 

after period was heavy truck speeds, which decreased at the PC by 3.8 mph and at the curve 

midpoint by 4.7 mph. There was no strong trend initially in speed changes after the OSBs were 

installed, with only heavy truck speeds decreasing at the PC and curve midpoint.

There were more changes in speeds during the second after period. Speeds remained relatively 

similar at the control point, with only daytime passenger car speeds increasing by approximately 

1.6 mph. There were no speed changes at the approach. Speeds increased at the PC for all 

observations, heavy trucks, and daytime passenger cars, with speed increases of approximately 

1.9, 6.1, and 2.0 mph, respectively. However, the 2.0 mph increase for daytime passenger cars 

was not significant after accounting for the speed increase at the control point. Speeds at the 

curve midpoint significantly decreased for every speed metric. The speed reductions ranged from 

6.0 to 8.2 mph. Based on the second after period, speeds at the curve midpoint significantly 

decreased after the application of the OSBs, with a practical decrease (greater than 5 mph). 

Table 61. Before-after operating speeds at southbound Shinarump Road.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

47.317 6.928 51.099 8.603 47.299 6.864 51.100 8.042 303 288 209

All 

observations 

1st after

48.542 6.689 49.716 7.630 46.393 6.947 49.838 8.216 236 224 154

All 

observations 

2nd after

47.979 8.414 51.277 9.756 49.244 9.528 44.662 6.987 242 176 225

Passenger 

cars before 47.566 6.768 51.241 8.023 48.017 6.341 51.537 7.773 249 238 175

Passenger 

cars 1st after 48.930 6.887 50.592 7.471 47.409 6.490 50.780 8.036 201 193 132

Passenger 

cars 2nd 

after

48.375 8.105 51.491 9.502 49.158 9.245 45.099 6.954 216 158 203

Heavy 

trucks before 46.167 7.583 50.444 10.956 43.880 8.188 48.853 9.099 54 50 34

Heavy 

trucks 1st 

after

46.314 4.928 44.686 6.597 40.065 6.413 44.182 7.062 35 31 22

Heavy 

trucks 2nd 

after

44.692 10.248 49.500 11.724 50.000 12.020 40.636 6.067 26 18 22

Daytime 

passenger 

cars before

46.686 7.001 50.777 8.431 47.009 6.033 50.894 7.375 121 115 94

Daytime 47.571 6.276 50.420 7.582 46.654 6.513 50.759 7.871 112 107 79

170
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

passenger 

cars 1st after

Daytime 

passenger 

cars 2nd 

after

48.316 8.146 51.181 9.422 49.017 9.247 44.805 6.618 171 119 159

Nighttime 

passenger 

cars before

48.398 6.458 51.680 7.624 48.959 6.500 52.284 8.193 128 123 81

Nighttime 

passenger 

cars 1st after

50.640 7.266 50.809 7.365 48.349 6.374 50.811 8.353 89 86 53

Nighttime 

passenger 

cars 2nd 

after

48.600 8.032 52.667 9.819 49.590 9.346 46.159 8.046 45 39 44

Opposed 

passenger 

cars before

45.967 6.646 48.200 5.580 45.933 4.982 50.875 6.556 30 30 24

Opposed 

passenger 

cars 1st after

46.263 5.086 49.211 5.127 46.105 5.259 52.636 5.608 19 19 11

Opposed 

passenger 

cars 2nd 

after

47.889 7.192 49.741 5.769 48.526 7.516 44.400 5.276 27 19 25

Unopposed 

passenger 

cars before

47.785 6.770 51.658 8.224 48.317 6.468 51.642 7.964 219 208 151

Unopposed 

passenger 

cars 1st after

49.209 7.000 50.736 7.670 47.552 6.608 50.612 8.218 182 174 121

Unopposed 

passenger 

cars 2nd 

after

48.444 8.242 51.741 9.907 49.245 9.477 45.197 7.165 189 139 178

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before 

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 102 shows a graphical representation of the speed profiles for southbound Shinarump 

Road. The general shape of the mean and 85th percentile speed profiles remained relatively 

similar in the before and first after period. In the second after period, the mean and 85th

percentile speeds increased at the midpoint.

α

α

171
Figure 102. Graph. Operating speeds comparison on southbound Shinarump Road

(PSL = 45 mph).

Southbound Diamond Bar Road, AZ

As table 62 shows, in the first after period at southbound Diamond Bar Road, operating speeds 

remained the same for most metrics. The only significant change at the control point was heavy 

truck speeds decreased by approximately 4.0 mph. Heavy truck speeds also decreased at the 

approach by approximately 2.7 mph, while all other speed metrics did not change significantly. 

The only speed metric at the PC that changed was nighttime passenger car speeds, which

decreased by approximately 4.9 mph. The only speed metric at the curve midpoint that changed 

was heavy truck speeds, which decreased by approximately 4.7 mph. After taking into account

the reduction in heavy truck speeds at the control point speed, truck speeds did not decrease in 

the first after period at the curve midpoint. The OSBs had virtually no effect on any of the other 

speed metrics in the first after period.

There were more speed changes in the second after period when compared with the before

period, than there were between the first after period and before period. The only change at the 

control point was heavy truck speeds, which decreased from both the before period and first after

period. These speed reductions were 4.0 and 6.9 mph, respectively. Speeds for all metrics 

increased at the approach, except heavy truck speeds did not change from the before period. 

Speed increases ranged between approximately 3.7 and 6.7 mph at this data-collection point. 

Speeds did not significantly increase at the PC, except heavy truck speeds decreased by 

approximately 5.2 mph. All measured speed metrics decreased at the curve midpoint, with speed 

decreases ranging between approximately 5.0 and 10.6 mph. 

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound Shinarump Road)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th

Percentile Speed

172
Based on the second after period, speeds at the curve midpoint significantly decreased after the 

application of the optical speed bars, with a practical decrease (greater than 5 mph).

Table 62. Before-after operating speeds at southbound Diamond Bar Road.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

53.421 8.312 49.171 6.730 50.299 7.116 50.435 7.621 292 214 209

All 

observations 

1st after

52.111 9.266 48.144 6.865 49.969 8.313 49.091 8.654 153 64 110

All 

observations 

2nd after

53.317 8.817 54.410 7.940 51.506 6.705 42.695 6.953 183 89 177

Passenger 

cars before 53.867 8.389 49.516 6.675 50.874 6.996 50.703 7.611 256 182 182

Passenger 

cars 1st after 53.476 9.418 49.097 7.084 50.925 8.655 50.375 8.743 124 53 88

Passenger 

cars 2nd after 54.071 8.616 55.035 7.831 52.083 6.446 43.061 7.017 170 84 164

Heavy trucks 

before 50.250 7.064 46.722 6.704 47.031 7.014 48.630 7.581 36 32 27

Heavy trucks 

1st after 46.276 5.738 44.069 3.760 45.364 4.202 43.955 6.122 29 11 22

Heavy trucks 

2nd after 43.462 4.502 46.231 3.811 41.800 1.483 38.077 3.904 13 5 13

Daytime 

passenger 

cars before

54.061 8.582 49.873 7.057 51.706 7.113 51.109 7.876 181 126 128

Daytime 

passenger 

cars 1st after

53.718 9.678 49.500 7.121 52.318 8.596 50.831 9.011 110 44 77

Daytime 

passenger 

cars 2nd after

53.832 8.857 54.904 8.035 52.576 6.361 42.475 7.134 125 66 122

Nighttime 

passenger 

cars before

53.400 7.939 48.653 5.598 49.000 6.399 49.741 6.918 75 56 54

Nighttime 

passenger 

cars 1st after

51.571 7.035 45.929 6.120 44.111 5.183 47.182 5.930 14 14 11

Nighttime 

passenger 

cars 2nd after

54.733 7.964 55.400 7.309 50.278 6.614 44.762 6.446 45 18 42

Opposed 

passenger 

cars before

53.472 9.376 50.057 6.320 51.000 8.218 50.057 8.359 53 35 35

Opposed 

passenger 

cars 1st after

52.500 10.988 48.611 7.047 52.714 9.050 52.077 9.996 18 7 13

173
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Opposed 

passenger 

cars 2nd after

53.889 5.989 53.722 6.115 52.692 4.461 42.588 6.820 18 13 17

Unopposed 

passenger 

cars before

53.970 8.134 49.374 6.773 50.844 6.705 50.857 7.445 203 147 147

Unopposed 

passenger 

cars 1st after

53.642 9.175 49.179 7.120 50.652 8.665 50.080 8.548 106 46 75

Unopposed 

passenger 

cars 2nd after

54.092 8.890 55.191 8.012 51.972 6.765 43.116 7.060 152 71 147

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before 

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint 

Figure 103 shows a graphical representation of the speed profiles for southbound Diamond Bar 

Road. The general shape of the mean and 85th percentile speed profiles remained relatively 

similar in the before and first after period. In the second after period, the mean and 85th

percentile speeds increased at the approach and midpoints. 

Figure 103. Graph. Operating speeds comparison on southbound Diamond Bar Road

(PSL = 45 mph).

α

α

40

45

50

55

60

65

70

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound Diamond Bar Road)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th

Percentile Speed

174
Southbound County Route 1, AZ

As table 63 shows, in the first after period at southbound County Route 1, operating speeds 

remained the same for most metrics. There was a significant increase at the control point for the 

following speed metrics: all observations, passenger cars, daytime passenger cars, nighttime 

passenger cars, and unopposed passenger cars, with speed increases of approximately 

2.0, 2.2, 2.8, and 2.1 mph, respectively. There were no significant speed changes at the approach. 

Speeds at the PC remained the same in the first after period, except daytime passenger car speeds 

significantly decreased by approximately 1.1 mph. Speeds also remained constant at the curve 

midpoint, with the exception that opposed passenger car speeds significantly increased by 

approximately 3.4 mph. The optical speed bars had virtually no effect on speeds in the first after

period.

There were more speed changes in the second after period when compared with the before period 

than there were between the first after period and before period. There were no significant speed 

differences at the control point between the second after period and before period. Speeds 

generally decreased from the first to second after period, with speeds returning closer to the 

before period. Speeds remained the same at the approach, except speeds significantly increased 

for all observations, passenger cars, and unopposed passenger cars, increasing by approximately 

1.1, 1.0, and 1.1 mph, respectively. Speeds significantly increased at the PC for all measured 

speed metrics, expect opposed passenger car speeds remained the same. Speed increases ranged 

between approximately 1.8 and 6.3 mph. These speed increases were also observed at the curve 

midpoint, with all measured speed metrics, except heavy trucks, increasing significantly by 

approximately 3.5 to 7.1 mph. 

The OSBs did not have a strong effect on operating speeds in the first after period, but after 

several months, the speeds at the PC and curve midpoint significantly increased between 2.1 and 

7.1 mph. It is possible that drivers decelerated on the curve approach but increased speeds 

through the curve influenced by the large curve radii.

Table 63. Before-after operating speeds at southbound County Route 1.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 

before 53.471 8.882 47.731 5.559 44.021 5.211 43.919 7.259 342 329 307

All observations 

1st after 55.448 9.376 47.924 5.972 43.565 5.031 43.677 7.210 382 363 341

All observations 

2nd after 53.622 9.856 48.820 5.650 46.521 5.742 48.014 7.115 233 219 145

Passenger cars 

before 53.532 8.901 47.810 5.515 44.134 5.125 43.918 7.262 327 314 292

Passenger cars 

1st after 55.746 9.419 48.045 5.896 43.635 5.013 43.877 7.147 355 337 316

Passenger cars 

2nd after 53.532 9.792 48.792 5.656 46.417 5.719 47.986 7.166 216 204 138

Heavy trucks 

before 52.133 8.651 46.000 6.414 41.667 6.532 43.933 7.450 15 15 15

Heavy trucks 

1st after 51.519 7.939 46.333 6.811 42.654 5.284 41.160 7.679 27 26 25

175
Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Heavy trucks 

2nd after 54.765 10.889 49.176 5.736 47.933 6.076 48.571 6.477 17 15 7

Daytime 

passenger cars 

before

53.847 9.266 49.038 5.430 44.977 4.895 44.599 7.081 183 174 162

Daytime 

passenger cars 

1st after

55.689 9.357 48.222 5.420 43.895 4.746 43.969 7.107 257 248 229

Daytime 

passenger cars 

2nd after

54.046 9.582 49.408 5.225 47.034 5.326 48.316 7.149 152 145 98

Nighttime 

passenger cars 

before

53.132 8.428 46.250 5.238 43.086 5.228 43.069 7.421 144 140 130

Nighttime 

passenger cars 

1st after

55.898 9.628 47.582 7.004 42.910 5.656 43.632 7.287 98 89 87

Nighttime 

passenger cars 

2nd after

52.313 10.249 47.328 6.375 44.898 6.383 47.175 7.236 64 59 40

Opposed 

passenger cars 

before

53.479 9.299 47.125 5.354 44.111 4.900 41.091 7.844 48 45 44

Opposed 

passenger cars 

1st after

56.000 9.372 48.301 5.721 43.843 5.029 44.506 6.613 93 89 85

Opposed 

passenger cars 

2nd after

53.407 9.616 47.963 4.642 45.373 5.564 48.171 6.667 54 51 41

Unopposed 

passenger cars 

before

53.541 8.848 47.928 5.543 44.138 5.171 44.419 7.053 279 269 248

Unopposed 

passenger cars 

1st after

55.656 9.452 47.954 5.965 43.560 5.015 43.645 7.333 262 248 231

Unopposed 

passenger cars 

2nd after

53.574 9.879 49.068 5.943 46.765 5.745 47.907 7.399 162 153 97

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before 

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 104 shows a graphical representation of the speed profiles for southbound County 

Route 1. The general shape of the mean and 85th percentile speed profiles, at the curve approach

point and PC, for the three collection periods remained relatively similar in the before and first 

after period. However, the midpoint speeds increased in the second after period.

α

α

176
Figure 104. Graph. Operating speeds comparison on southbound County Route 1

(PSL = 35 mph).

Arizona Summary of Results

Overall, the OSBs did not have an effect on operating speeds at the Arizona sites. There were no 

changes in speeds that were consistent across all of the sites.

Alabama

This section of the report presents the before-after comparisons for the eight Alabama OSB sites. 

Alabama Location #1

As table 64 shows, in the first after period at Alabama Location #1, operating speeds decreased 

for several speed metrics. There was a significant decrease at the control point for all speed 

metrics. These speed decreases ranged between approximately 2.1 and 6.7 mph. Speeds at the 

approach significantly decreased for all speed metrics. However, after accounting for the speed 

decrease at the control point, none of these reductions were significant, and speeds for passenger 

cars, daytime passenger cars, and unopposed passenger cars actually increased. Speeds at the PC 

significantly decreased for the following speed metrics: all observations, passenger cars, daytime 

passenger cars, and unopposed passenger cars. However, after accounting for the speed decrease 

at the control point, none of these reductions were significant, and speeds for passenger cars and 

opposed passenger cars actually increased. Speeds at the curve midpoint did not change 

significantly from the before period. If the speed reduction at the control point was taken into 

account, speeds increased slightly at the curve midpoint.

There were more speed changes in the second after period when compared with the before

period, than there were between the first after period and before period. Speeds at the control 

40

45

50

55

60

65

70

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound County Route 1)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th

Percentile Speed

2nd After 85th

Percentile Speed

177
point increased for all speed metrics, except for heavy trucks. The range of speed increases was 

between approximately 1.7 and 2.7 mph. Not taking the speed increase at the control point into 

account, speeds at the approach increased from the first after period, but they remained the same 

when compared with the before period, except all observations significantly decreased by

approximately 0.8 mph. Not taking into account the speed increase at the control point, speeds at 

the PC increased from the first after period, but remained the same when compared with the 

before period, except opposed passenger cars significantly increased by approximately 3.3 mph. 

Speeds significantly decreased at the curve midpoint for all speed metrics, except for heavy 

trucks. The speed decreases were between approximately 1.4 and 2.6 mph. If the speed increases 

at the control point were taken into account, these decreases became more significant. 

The OSBs did not have a strong effect on operating speeds in the first after period, but after 

several months, the speeds at the curve midpoint significantly decreased between 1.4 and 

2.6 mph.

Table 64. Before-after operating speeds at Alabama Location #1.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

47.883 9.368 49.208 7.596 50.103 8.770 42.323 6.912 375 87 353

All 

observations 

1st after

43.306 6.928 45.497 6.752 47.431 5.886 41.691 6.951 340 204 333

All 

observations 

2nd after

50.190 7.863 48.380 6.788 49.776 6.830 40.364 9.437 822 223 733

Passenger 

cars before 47.917 9.380 49.218 7.540 50.429 8.700 42.516 6.892 362 84 341

Passenger 

cars 1st after 43.575 6.880 46.134 6.490 48.148 5.530 42.523 6.342 313 183 306

Passenger 

cars 2nd after 50.226 7.931 48.522 6.792 49.906 6.914 40.475 9.413 793 213 710

Heavy trucks 

before 46.923 9.332 48.923 9.394 41.000 6.083 36.833 5.132 13 3 12

Heavy trucks 

1st after 40.185 6.850 38.111 5.243 41.190 5.269 32.259 6.671 27 21 27

Heavy trucks 

2nd after 49.207 5.722 44.483 5.468 47.000 3.944 36.957 9.740 29 10 23

Daytime 

passenger 

cars before

47.638 9.418 48.805 7.641 50.795 8.551 42.288 6.764 174 39 160

Daytime 

passenger 

cars 1st after

42.964 6.865 46.016 6.568 48.020 5.060 42.470 6.112 252 151 247

Daytime 

passenger 

cars 2nd after

49.417 7.985 48.296 6.904 49.578 7.058 40.840 9.469 348 102 306

Nighttime 

passenger 

cars before

48.176 9.362 49.601 7.444 50.111 8.912 42.718 7.016 188 45 181

178
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Nighttime 

passenger 

cars 1st after

46.098 6.395 46.623 6.186 48.750 7.427 42.746 7.282 61 32 59

Nighttime 

passenger 

cars 2nd after

50.858 7.838 48.699 6.705 50.207 6.797 40.198 9.373 445 111 404

Opposed 

passenger 

cars before

47.529 10.661 48.793 7.385 46.833 7.648 42.037 6.512 87 24 82

Opposed 

passenger 

cars 1st after

43.250 5.583 44.775 4.699 46.667 4.151 41.725 6.345 40 21 40

Opposed 

passenger 

cars 2nd after

49.228 7.986 47.772 6.816 50.130 5.361 39.479 10.074 158 46 142

Unopposed 

passenger 

cars before

48.040 8.955 49.353 7.596 51.867 8.736 42.668 7.014 275 60 259

Unopposed 

passenger 

cars 1st after

43.623 7.057 46.333 6.696 48.340 5.666 42.643 6.345 273 162 266

Unopposed 

passenger 

cars 2nd after

50.474 7.904 48.709 6.778 49.844 7.297 40.724 9.233 635 167 568

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at 95 percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC 

N3 = Number of observations at the midpoint

Figure 105 shows a graphical representation of the speed profiles for Alabama Location #1. The 

mean and 85th percentile operating speeds increased in the first after period but remained 

relatively similar during the before and second after data-collection periods.

α

α

179
Figure 105. Graph. Operating speeds comparison at Alabama Location #1 (PSL = 55 mph).

Alabama Location #2

As table 65 shows, in the first after period at Alabama Location #2, operating speeds remained 

the same for most metrics. The only significant change at the control point was unopposed 

passenger car speeds decreased by approximately 1.1 mph. Speeds at the approach increased for 

the following speed metrics: all observations, passenger cars, and opposed passenger cars, with 

speed increases of 1.0, 1.1, and 2.4 mph, respectively. There were no significant speed changes 

at the PC. Speeds at the curve midpoint significantly increased for the following speed metrics: 

all observations, passenger cars, daytime passenger cars, and opposed passenger cars, with speed 

increases of approximately 1.0, 1.1, 1.9, and 3.4 mph, respectively. After installing the OSBs, 

speeds significantly increased at the curve midpoint during the first after period, but most of the 

speed increases were not practically significant.

The speed changes that occurred in the first after period continued through the second after

period, and speeds in the second after period were similar to the first after period. The only 

significant change at the control point was opposed passenger car speeds increased by 

approximately 2.1 mph. Speeds at the approach increased for the same speed metrics as in the 

first after period: all observations, passenger cars, and opposed passenger cars, with speed 

increases of approximately 1.0, 0.9, and 3.5 mph, respectively. There were no significant speed 

changes at the PC. Speeds increased at the curve midpoint for the following speed metrics: all 

observations, daytime passenger cars, and opposed passenger cars, with speed increases of 

approximately 5.6, 1.5, and 3.0 mph, respectively. However, if the speed increase at the control 

point was taken into account, the speed increase at the curve midpoint for opposed passenger 

30

35

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Alabama Location #1)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th Percentile

Speed

180
cars was no longer significant. Speeds significantly increased for several speed metrics in both 

after periods at the curve midpoint, but many speed metrics did not increase.

Table 65. Before-after operating speeds at Alabama Location #2.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

49.269 7.604 44.291 5.822 42.472 5.747 38.363 7.094 398 290 358

All 

observations 

1st after

48.843 6.991 45.328 5.034 42.245 4.882 39.310 5.429 470 413 462

All 

observations 

2nd after

49.374 6.823 45.335 5.407 43.163 5.419 43.949 6.719 495 307 316

Passenger 

cars before 49.569 7.238 44.479 5.623 42.630 5.554 38.418 7.129 376 273 336

Passenger 

cars 1st 

after

49.039 6.984 45.549 4.977 42.552 4.742 39.556 5.325 439 386 432

Passenger 

cars 2nd 

after

49.472 6.787 45.413 5.181 43.192 5.263 39.003 5.624 632 499 585

Heavy 

trucks 

before

44.136 11.319 41.091 8.053 39.941 8.050 37.091 6.560 22 17 22

Heavy 

trucks 1st 

after

46.065 6.582 42.194 4.861 37.852 4.825 35.767 5.764 31 27 30

Heavy 

trucks 2nd 

after

46.429 7.386 43.000 10.015 42.200 9.466 37.111 8.345 21 15 18

Daytime 

passenger 

cars before

49.884 8.070 45.072 5.722 43.263 5.737 37.821 7.802 138 99 122

Daytime 

passenger 

cars 1st 

after

49.302 6.916 45.764 4.782 42.782 4.626 39.770 5.158 318 280 313

Daytime 

passenger 

cars 2nd 

after

49.584 6.915 45.776 5.031 43.692 5.102 39.381 5.647 375 295 344

Nighttime 

passenger 

cars before

49.387 6.721 44.134 5.548 42.270 5.432 38.762 6.720 238 174 214

Nighttime 

passenger 

cars 1st 

after

48.347 7.143 44.983 5.437 41.943 5.008 38.992 5.725 121 106 119

Nighttime 

passenger 

cars 2nd 

49.307 6.607 44.883 5.359 42.471 5.419 38.465 5.557 257 204 241

181
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

after

Opposed 

passenger 

cars before

47.809 7.949 43.022 6.312 41.721 5.057 36.378 7.241 89 61 82

Opposed 

passenger 

cars 1st 

after

49.026 6.713 45.421 4.674 42.338 5.027 39.787 5.602 76 68 75

Opposed 

passenger 

cars 2nd 

after

49.918 6.386 46.541 4.829 44.012 4.633 39.337 5.721 98 81 92

Unopposed 

passenger 

cars before

50.115 6.928 44.930 5.323 42.892 5.674 39.075 6.976 287 212 254

Unopposed 

passenger 

cars 1st 

after

49.041 7.048 45.576 5.044 42.597 4.686 39.507 5.272 363 318 357

Unopposed 

passenger 

cars 2nd 

after

49.390 6.861 45.206 5.221 43.033 5.367 38.941 5.609 534 418 493

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 106 shows a graphical representation of the speed profiles for Alabama Location #2. The 

general shape of the speed profiles for the three collection periods remained relatively similar.

α

α

182
Figure 106. Graph. Operating speeds comparison at Alabama Location #2 (PSL = 55 mph).

Alabama Location #3

As table 66 shows, in the first after period at Alabama Location #3, operating speeds changed for 

many speed metrics. As in the before period, operating speeds at the control point were high. It 

was originally thought that a sensor malfunction caused these high speed measurements, but 

these high speeds persisted through all three time periods. Speeds at the control point increased 

for all speed metrics, except nighttime passenger cars. These speed increases were between 

2.5 and 3.4 mph. Speeds at the approach decreased for all speed metrics, except nighttime 

passenger cars and opposed passenger cars. These speed decreases were between approximately 

1.0 and 3.0 mph. The only change at the PC was passenger car speeds, which increased by 

approximately 0.6 mph. Speeds at the curve midpoint decreased for all speed metrics, except 

heavy trucks. These speed reductions were between approximately 1.9 and 2.8 mph. Speeds at 

the curve midpoint were slightly lower immediately after the OSBs were installed.

Most of the changes in speeds from the first after period did not persist through the second after

period. Speeds at the control point increased for all speed metrics, with speed increases between 

approximately 2.0 and 3.5 mph. Speeds at the approach remained the same, except all 

observations decreased by approximately 0.6 mph. There were no significant speed changes at 

the PC. Speeds at the curve midpoint increased from the first after period and returned closer to 

the before period. There were no significant speed changes at the curve midpoint. 

Speeds slightly decreased at the curve midpoint immediately after installing the OSBs, but the 

decrease was not maintained through the second after period. 

30

35

40

45

50

55

60

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Alabama Location #2)

Before Period Mean

Speed

1st After Mean

Speed

2nd After Mean

Speed

Before 85th

Percentile Speed

1st After 85th

Percentile Speed

2nd After 85th

Percentile Speed

183
Table 66. Before-after operating speeds at Alabama Location #3.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

65.253 12.908 49.831 6.463 41.307 4.663 41.233 5.914 498 472 472

All 

observations 

1st after

67.813 11.357 48.246 5.062 41.365 4.737 38.677 6.919 513 493 511

All 

observations 

2nd after

68.027 11.822 49.208 5.335 41.622 4.770 41.085 6.888 960 891 879

Passenger cars 

before 65.520 13.004 50.000 6.522 41.629 4.652 41.740 5.683 440 415 415

Passenger cars 

1st after 68.215 11.509 49.018 4.728 42.239 4.371 39.085 7.219 400 381 398

Passenger cars 

2nd after 68.302 11.785 49.606 5.297 42.065 4.712 41.571 6.823 819 752 748

Heavy trucks 

before 63.224 12.070 48.552 5.891 38.965 4.066 37.544 6.299 58 57 57

Heavy trucks 

1st after 66.389 10.732 45.513 5.276 38.393 4.748 37.239 5.534 113 112 113

Heavy trucks 

2nd after 66.433 11.955 46.901 4.969 39.223 4.366 38.313 6.618 141 139 131

Daytime 

passenger cars 

before

66.424 12.482 50.549 6.973 41.923 4.682 41.689 5.979 264 246 251

Daytime 

passenger cars 

1st after

68.880 11.622 49.098 4.733 42.278 4.364 38.861 7.470 317 302 316

Daytime 

passenger cars 

2nd after

69.931 11.578 50.006 5.282 42.450 4.634 41.924 6.831 466 436 432

Nighttime 

passenger cars 

before

64.165 13.675 49.176 5.702 41.201 4.589 41.817 5.214 176 169 164

Nighttime 

passenger cars 

1st after

65.675 10.759 48.711 4.725 42.089 4.421 39.951 6.118 83 79 82

Nighttime 

passenger cars 

2nd after

66.150 11.726 49.076 5.278 41.535 4.774 41.089 6.793 353 316 316

Opposed 

passenger cars 

before

65.516 13.031 49.979 6.684 41.423 5.063 41.928 6.036 188 175 180

Opposed 

passenger cars 

1st after

68.953 11.438 48.929 5.002 41.900 4.482 39.318 6.634 85 80 85

Opposed 

passenger cars 

2nd after

68.935 12.198 49.245 5.109 41.894 4.961 42.335 7.003 200 180 185

184
Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Unopposed 

passenger cars 

before

65.524 13.010 50.016 6.413 41.779 4.332 41.596 5.405 252 240 235

Unopposed 

passenger cars 

1st after

68.016 11.538 49.041 4.659 42.329 4.344 39.022 7.378 315 301 313

Unopposed 

passenger cars 

2nd after

68.097 11.651 49.722 5.355 42.119 4.634 41.320 6.751 619 572 563

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint 

Figure 107 shows a graphical representation of the speed profiles for Alabama Location #3. The 

general shape of the speed profiles for the three collection periods remained relatively similar.

Figure 107. Graph. Operating speeds comparison at Alabama Location #3 (PSL = 55 mph).

α

α

30

40

50

60

70

80

90

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds 

(Alabama Location #3)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th Percentile

Speed

185
Alabama Location #4

As Table 67 shows, in the first after period at Alabama Location #4, operating speeds decreased 

for many speed metrics. There was a significant decrease at the control point for all measured 

speed metrics. Speed decreases were between approximately 1.6 and 3.3 mph for passenger cars 

and 5.3 mph for heavy trucks. There was a significant decrease at the approach for all speed 

metrics, except heavy trucks and opposed passenger cars. These speed decreases were all 

approximately 1.5 mph. However, if the decrease in speed at the control point was taken into 

account, the speed decreases at the approach were no longer significant. There was a significant 

decrease at the PC for all measured speed metrics, except heavy trucks. Speed decreases were 

between 2.0 and 2.5 mph. However, if the speed decreases at the control point were taken into

account, the only speed decrease at the PC that was significant was for daytime passenger cars, 

and nighttime speeds actually increase slightly. Speeds were also significantly lower at the curve 

midpoint for all measured speed metrics. However, if the speed decreases at the control point 

were taken into account, none of the speed decreases at the curve midpoint were significant. 

Overall, installing the OSBs did not have an effect on operating speeds in the first after period.

Most of the speed changes in the first after period were no longer present in the second after

period. Speeds at the control point were closer to speeds in the before period, and there were no 

significant speed changes. Speeds at the approach were also closer to speeds in the before period,

and there were no significant speed changes, except daytime passenger speeds increased by 

approximately 1.1 mph. Speeds at the PC significantly decreased for the following speed 

metrics: all observations, passenger cars, and opposed passenger cars, with speed decreases of 

approximately 0.6, 0.7, and 1.2 mph, respectively. Speeds at the curve midpoint did not 

significantly change, except nighttime speeds were approximately 1.5 mph lower. 

Speeds slightly decreased at the curve midpoint after installing the OSBs, but the decrease was 

not maintained through the second after period.

186
Table 67. Before-after operating speeds at Alabama Location #4.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

50.761 9.466 46.666 7.082 39.091 4.939 34.664 8.205 494 471 455

All 

observations 

1st after

48.515 8.022 45.152 5.409 36.891 4.357 31.938 6.086 513 512 513

All 

observations 

2nd after

50.322 7.655 47.172 6.128 38.469 4.754 34.433 8.094 615 603 564

Passenger 

cars before 50.633 9.369 46.703 7.019 39.153 4.883 34.506 8.197 472 452 437

Passenger 

cars 1st after 48.541 7.986 45.242 5.431 37.000 4.330 31.819 6.162 475 474 475

Passenger 

cars 2nd 

after

50.381 7.664 47.155 6.038 38.455 4.709 34.434 8.125 582 571 535

Heavy 

trucks 

before

53.500 11.237 45.864 8.481 37.632 6.103 38.500 7.649 22 19 18

Heavy 

trucks 1st 

after

48.184 8.561 44.026 5.059 35.526 4.519 33.421 4.864 38 38 38

Heavy 

trucks 2nd 

after

49.273 7.543 47.485 7.649 38.719 5.566 34.414 7.623 33 32 29

Daytime 

passenger 

cars before

50.588 9.045 46.631 7.464 39.528 5.023 33.861 8.062 187 176 173

Daytime 

passenger 

cars 1st after

48.966 8.241 45.564 5.389 37.020 4.325 31.969 5.975 351 350 351

Daytime 

passenger 

cars 2nd 

after

50.324 7.331 47.770 6.113 38.953 4.793 35.084 8.230 343 338 320

Nighttime 

passenger 

cars before

50.663 9.592 46.751 6.723 38.913 4.786 34.928 8.273 285 276 264

Nighttime 

passenger 

cars 1st after

47.339 7.111 44.331 5.466 36.944 4.362 31.395 6.668 124 124 124

Nighttime 

passenger 

cars 2nd 

after

50.464 8.132 46.272 5.829 37.734 4.499 33.465 7.887 239 233 215

Opposed 

passenger 

cars before

50.886 9.349 46.429 8.484 39.141 5.234 34.328 8.582 140 128 125

187
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Opposed 

passenger 

cars 1st after

49.156 8.039 45.227 5.317 36.836 4.814 31.953 6.551 128 128 128

Opposed 

passenger 

cars 2nd 

after

51.089 7.337 47.274 6.375 37.910 4.802 34.535 8.608 124 122 114

Unopposed 

passenger 

cars before

50.527 9.390 46.819 6.311 39.157 4.746 34.577 8.051 332 324 312

Unopposed 

passenger 

cars 1st after

48.314 7.966 45.248 5.480 37.061 4.143 31.769 6.021 347 346 347

Unopposed 

passenger 

cars 2nd 

after

50.190 7.746 47.122 5.950 38.604 4.678 34.406 8.000 458 449 421

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 108 shows a graphical representation of the speed profiles for Alabama Location #4. The 

general shape of the speed profiles for the three collection periods remained relatively similar.

α

α

188
Figure 108. Graph. Operating speeds comparison at Alabama Location #4 (PSL = 35 mph).

Alabama Location #5

As table 68 shows, in the first after period at Alabama Location #5, operating speeds changed for 

several speed metrics. There were no significant speed changes at the control point or approach. 

Speeds at the PC significantly decreased for the following speed metrics: all observations, 

passenger cars, and unopposed passenger cars, with speed decreases of approximately 

2.2, 2.1, and 2.9 mph, respectively. Speeds for opposed passenger cars significantly increased by 

approximately 5.4 mph. Speeds at the curve midpoint significantly increased for all speed 

metrics, except heavy trucks. These speed increases were between approximately 4.2 and 

7.8 mph. Speeds at the PC significantly decreased after the installation of the OSBs, but vehicles 

maintained a more constant speed throughout the curve, and speeds increased at the curve 

midpoint. 

The speed changes that occurred in the first after period continued through the second after

period, and speeds in the second after period were similar to the first after period. There were no 

significant speed changes at the control point or approach. Speeds at the PC significantly 

decreased for the following speed metrics: all observations, passenger cars, heavy trucks, and 

unopposed passenger cars, with speed decreases of approximately 1.9, 1.8, 5.2, 1.7, and 2.6 mph. 

Speeds for opposed passenger cars significantly increased by approximately 6.5 mph. Speeds at 

the curve midpoint significantly increased for all speed metrics. Speed increases were between 

approximately 3.6 and 8.5 mph for passenger cars and 7.8 mph for heavy trucks. 

Installing the OSBs decreased operating speeds at the PC during both after periods between 

approximately 1.7 and 2.9 mph for passenger cars, while speeds at the curve midpoint increased 

during both after periods between approximately 3.6 and 8.5 mph.

30

35

40

45

50

55

60

65

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds 

(Alabama Location #4)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th

Percentile Speed

2nd After 85th

Percentile Speed

189
Table 68. Before-after operating speeds at Alabama Location #5.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

41.944 7.212 43.742 8.327 45.781 7.524 39.810 6.842 233 64 221

All 

observations 

1st after

41.467 7.184 43.170 7.194 43.636 6.437 44.182 7.264 353 236 242

All 

observations 

2nd after

41.889 7.277 43.069 7.426 43.847 6.047 43.949 6.719 495 307 316

Passenger 

cars before 42.299 7.094 44.054 8.250 45.794 7.584 40.028 6.782 224 63 212

Passenger 

cars 1st 

after

41.851 7.086 43.460 7.037 43.689 6.435 44.384 7.164 335 222 232

Passenger 

cars 2nd 

after

42.185 7.110 43.344 7.168 44.024 5.960 44.020 6.672 471 294 302

Heavy 

trucks 

before

33.111 3.822 36.000 6.614 45.000 0.000 34.667 6.557 9 1 9

Heavy 

trucks 1st 

after

34.333 5.018 37.778 8.128 42.786 6.647 39.500 8.383 18 14 10

Heavy 

trucks 2nd 

after

36.083 8.214 37.667 10.120 39.846 6.842 42.429 7.773 24 13 14

Daytime 

passenger 

cars before

41.947 6.887 44.405 7.941 45.619 7.450 39.787 6.772 131 42 122

Daytime 

passenger 

cars 1st 

after

41.644 6.846 43.222 7.071 43.668 6.212 44.273 7.151 284 193 198

Daytime 

passenger 

cars 2nd 

after

42.272 6.988 43.276 7.003 43.921 6.131 43.858 7.030 301 190 204

Nighttime 

passenger 

cars before

42.796 7.383 43.559 8.686 46.143 8.021 40.356 6.821 93 21 90

Nighttime 

passenger 

cars 1st 

after

43.000 8.280 44.784 6.763 43.828 7.888 45.029 7.309 51 29 34

Nighttime 

passenger 

cars 2nd 

after

42.029 7.340 43.465 7.471 44.212 5.660 44.357 5.877 170 104 98

190
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Opposed 

passenger 

cars before

40.235 7.242 41.353 11.045 38.833 7.333 34.933 7.045 17 6 15

Opposed 

passenger 

cars 1st 

after

41.905 9.286 42.762 8.630 44.200 6.609 42.692 6.851 42 30 26

Opposed 

passenger 

cars 2nd 

after

41.867 10.281 44.567 8.063 45.294 5.828 43.389 5.782 30 17 18

Unopposed 

passenger 

cars before

42.469 7.072 44.275 7.972 46.526 7.290 40.416 6.621 207 57 197

Unopposed 

passenger 

cars 1st 

after

41.843 6.733 43.560 6.790 43.609 6.421 44.597 7.190 293 192 206

Unopposed 

passenger 

cars 2nd 

after

42.206 6.858 43.261 7.106 43.946 5.970 44.060 6.732 441 277 284

Bold indicates significance at 95 percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at 95 percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 109 shows a graphical representation of the speed profiles for Alabama Location #5. The 

PC mean operating speeds decreased in the two after periods while the midpoint speeds 

increased. The midpoint 85th percentile speeds increased in the two after periods. 

α

α

191
Figure 109. Graph. Operating speeds comparison at Alabama Location #5 (PSL = 40 mph).

Alabama Location #6

As table 69 shows, in the first after period at Alabama Location #6, operating speeds decreased 

for many speed metrics. There was a significant decrease at the control point for the following 

speed metrics: all observations, passenger cars, nighttime passenger cars, and unopposed 

passenger cars, with speed decreases of approximately 2.0, 2.0, 4.4, and 2.2 mph, respectively.

There was a significant increase at the approach for all speed metrics. These increases ranged 

from approximately 8.3 to 9.5 mph for passenger cars. However, these increased speeds were not 

maintained, and speeds at the PC significantly decreased for the following speed metrics: all 

observations, passenger cars, heavy trucks, and unopposed passenger cars, with speed decreases 

of approximately 1.6, 1.4, 4.4, and 1.8 mph, respectively. Speeds were also significantly lower at 

the curve midpoint for all passenger car speed metrics. These speed reductions were 

approximately 3.9 to 8.8 mph. Speeds throughout the curve decreased between 1.4 and 8.8 mph 

at this site after installing the OSBs.

In the second after period, there were several additional significant changes between the before

and second after period and between the two after periods. Speeds generally remained the same 

at the control point. Only all observations and heavy trucks had a significant reduction in speeds, 

with speed reductions of approximately 1.3 and 7.0 mph, respectively. Speeds at the approach

were lower than in the first after period, but they were still significantly higher in the second 

after period for the following speed metrics: all observations, passenger cars, nighttime 

passenger cars, and opposed passenger cars, with speed increases of approximately 

1.3, 1.2, 1.9, and 4.3 mph, respectively. Despite these significant increases at the approach, the 

speeds at the PC remained constant from the before to second after period with the exception of 

nighttime passenger cars. There was a significant increase of approximately 2.9 mph; however, 

after accounting for the speed increase at the approach, this increase was no longer significant. 

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Alabama Location #5)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th Percentile

Speed

192
Speeds increased slightly at the curve midpoint in the second after period when compared with

the first after period for several speed metrics, but speeds were lower than the before period for 

all speed metrics. These speed reductions were approximately 3.2 to 4.75 mph. 

Overall, the OSBs significantly reduced speeds at the curve midpoint in both the first and second 

after periods.

Table 69. Before-after operating speeds at Alabama Location #6.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

43.413 9.211 45.102 7.201 46.442 6.431 45.495 7.111 196 86 97

All 

observations 

1st after

41.382 9.064 54.627 8.674 44.879 6.628 40.780 7.109 220 190 205

All 

observations 

2nd after

42.082 10.108 46.412 7.360 47.644 7.706 41.762 7.679 478 104 433

Passenger 

cars before 43.399 9.294 45.426 6.939 46.447 6.469 45.613 7.199 188 85 93

Passenger 

cars 1st after 41.371 9.028 54.709 8.760 45.005 6.642 40.848 7.159 213 183 198

Passenger 

cars 2nd after 42.326 10.069 46.652 7.339 47.859 7.775 41.925 7.674 457 99 415

Heavy trucks 

before 43.750 7.498 37.500 9.457 46.000 0.000 42.750 4.272 8 1 4

Heavy trucks 

1st after 41.714 10.889 52.143 5.242 41.571 5.682 38.857 5.581 7 7 7

Heavy trucks 

2nd after 36.762 9.705 41.190 5.828 43.400 4.930 38.000 6.979 21 5 18

Daytime 

passenger 

cars before

43.504 9.135 45.434 6.731 46.586 6.489 45.032 7.759 129 58 62

Daytime 

passenger 

cars 1st after

41.937 8.633 54.931 8.493 45.219 6.581 40.810 7.160 175 151 163

Daytime 

passenger 

cars 2nd after

42.604 9.832 46.247 7.189 46.725 7.582 41.664 7.769 283 51 253

Nighttime 

passenger 

cars before

43.169 9.708 45.407 7.433 46.148 6.538 46.774 5.869 59 27 31

Nighttime 

passenger 

cars 1st after

38.763 10.393 53.684 9.957 44.000 6.942 41.029 7.258 38 32 35

Nighttime 

passenger 

cars 2nd after

41.874 10.455 47.310 7.552 49.063 7.875 42.333 7.530 174 48 162

Opposed 

passenger 

cars before

41.056 7.565 42.944 10.067 43.400 4.881 46.750 4.070 18 10 12

193
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Opposed 

passenger 

cars 1st after

40.273 10.612 52.545 6.743 43.545 6.362 37.909 7.368 11 11 11

Opposed 

passenger 

cars 2nd after

42.824 11.301 47.235 6.602 44.800 6.301 43.605 6.670 51 5 43

Unopposed 

passenger 

cars before

43.647 9.443 45.688 6.508 46.853 6.571 45.444 7.556 170 75 81

Unopposed 

passenger 

cars 1st after

41.431 8.961 54.827 8.855 45.099 6.666 41.021 7.129 202 172 187

Unopposed 

passenger 

cars 2nd after

42.264 9.917 46.579 7.431 48.021 7.840 41.731 7.767 406 94 372

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 110 shows a graphical representation of the speed profiles for Alabama Location #6. The 

general shape of the speed profiles for the three collection periods remained relatively similar.

Figure 110. Graph. Operating speeds comparison at Alabama Location #6 (PSL = 40 mph).

α

α

30

35

40

45

50

55

60

65

70

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Alabama Location #6)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th Percentile

Speed

194
Alabama Location #7

As table 70 shows, in the first after period at Alabama Location #7, operating speeds changed for 

many speed metrics. The only significant change at the control point was heavy truck speeds, 

which decreased by approximately 6.0 mph. Speeds at the approach decreased for all measured 

speed metrics. These speed decreases were between approximately 2.2 and 2.9 mph for 

passenger cars and 5.6 mph for heavy trucks. However, if the speed decrease at the control point 

was taken into account, this speed decrease was no longer significant. Speeds at the PC 

significantly decreased for the following speed metrics: all observations, passenger cars, daytime 

passenger cars, opposed passenger cars, and unopposed passenger cars. Speed decreases were 

practically insignificant, with speed decreases between approximately 0.7 and 1.3 mph. Speeds at 

the curve midpoint significantly decreased for all measured speed metrics. These speed decreases 

were between approximately 2.8 and 3.6 mph for passenger cars. Speeds for heavy trucks 

decreased by approximately 7.3 mph. However, if the speed decrease at the control point was

taken into account, this speed decrease was no longer significant. After installing the OSBs, 

speeds initially decreased through the curve.

Many of the changes in the first after period were also present in the second after period. There 

were no significant speed changes at the control point. Speeds at the approach increased from the 

first after period, but speeds were still significantly lower than the before period for all speed 

metrics, except heavy trucks. Speed decreases were between approximately 1.4 and 1.7 mph. 

Speeds at the PC were similar to speeds in the first after period and were significantly lower for 

all passenger car speed metrics, except opposed passenger cars. These speed decreases were 

small, with decreases between approximately 0.8 and 1.2 mph. Passenger car speeds at the curve 

midpoint increased from the first after period, but they were all still lower than the before period, 

except opposed passenger car speeds were not significantly lower. These speed decreases were 

between approximately 1.2 and 1.9 mph. 

Overall, speeds decreased at the approach, PC, and curve midpoint after the installation of the 

OSBs. However, these speed decreases were not practically significant. 

Table 70. Before-after operating speeds at Alabama Location #7.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

Observations 

before

53.159 9.499 43.648 5.400 36.950 4.293 38.819 5.257 429 422 419

All 

Observations 

1st after

52.538 9.914 41.247 5.013 36.176 4.156 35.527 4.771 580 574 579

All 

Observations 

2nd after

53.113 9.203 42.260 5.270 36.148 4.034 37.234 5.337 795 764 745

Passenger 

cars before 53.036 9.497 43.635 5.391 36.971 4.310 38.768 5.230 419 412 409

Passenger 

cars 1st after 52.546 9.918 41.341 4.992 36.249 4.150 35.594 4.777 560 554 559

Passenger 

cars 2nd after 53.127 9.141 42.285 5.234 36.164 4.048 37.225 5.259 780 751 730

195
Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Heavy trucks 

before 58.300 8.433 44.200 6.033 36.100 3.604 40.900 6.208 10 10 10

Heavy trucks 

1st after 52.300 10.069 38.600 5.020 34.150 3.884 33.650 4.320 20 20 20

Heavy trucks 

2nd after 52.400 12.362 41.000 7.000 35.231 3.059 37.667 8.566 15 13 15

Daytime 

passenger 

cars before

53.408 8.731 44.387 5.235 37.646 4.548 39.175 5.316 191 189 189

Daytime 

passenger 

cars 1st after

52.361 9.748 41.537 5.062 36.360 4.189 35.566 4.962 402 397 401

Daytime 

passenger 

cars 2nd after

53.165 9.232 42.644 5.289 36.448 4.154 37.260 5.336 514 500 481

Nighttime 

passenger 

cars before

52.724 10.104 43.004 5.450 36.399 4.020 38.418 5.141 228 223 220

Nighttime 

passenger 

cars 1st after

53.019 10.354 40.842 4.788 35.968 4.048 35.665 4.284 158 157 158

Nighttime 

passenger 

cars 2nd after

53.053 8.980 41.590 5.065 35.598 3.773 37.157 5.118 266 251 249

Opposed 

passenger 

cars before

52.148 8.668 43.241 5.701 36.657 4.310 38.355 4.989 108 105 107

Opposed 

passenger 

cars 1st after

51.773 10.502 41.000 4.558 35.625 3.671 35.042 4.632 97 96 96

Opposed 

passenger 

cars 2nd after

53.025 8.605 41.893 5.107 36.182 3.870 37.514 4.969 159 154 148

Unopposed 

passenger 

cars before

53.344 9.763 43.772 5.282 37.078 4.312 38.914 5.313 311 307 302

Unopposed 

passenger 

cars 1st after

52.708 9.795 41.413 5.079 36.380 4.235 35.708 4.803 463 458 463

Unopposed 

passenger 

cars 2nd after

53.153 9.280 42.385 5.266 36.159 4.096 37.151 5.332 621 597 582

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

α

α

196
Figure 111 shows a graphical representation of the speed profiles for Alabama Location #7. The 

general shape of the speed profiles for the three collection periods remained relatively similar.

Figure 111. Graph. Operating speeds comparison at Alabama Location #7 (PSL = 35 mph).

Alabama Location #8

As table 71 shows, in the first after period at Alabama Location #8, operating speeds remained 

the same for most metrics. The only significant change at the control point was daytime 

passenger car speeds, which decreased by approximately 1.9 mph. There were no significant 

speed changes at the approach or PC for any speed metric. Speeds decreased at the curve 

midpoint for all speed metrics, except heavy trucks. The speed decreases were between 

approximately 2.7 and 3.5 mph. After the OSBs were installed, speeds significantly decreased at 

the curve midpoint during the first after period.

There were more speed changes in the second after period, but most these changes were from the 

first after period and not the before period. The only significant changes at the control point 

compared with the before period were speeds for all observations, passenger cars, and nighttime 

passenger cars increased, with increases of approximately 0.9, 0.9, and 1.2 mph, respectively. 

There were no significant speed changes at the approach when compared with the before period. 

Speeds did not significantly change at the PC, except heavy truck speeds increased by 

approximately 4.0 mph. Speeds at the curve midpoint decreased for the following speed metrics: 

all observations, passenger cars, daytime passenger cars, and unopposed passenger cars, with 

speed decreases of approximately 1.0, 1.0, 1.3, and 1.5 mph. Based on the second after period, 

speeds at the curve midpoint slightly decreased after applying the OSBs, but these speed 

reductions were not practical, with less than a 2.0-mph reduction.

30

35

40

45

50

55

60

65

Control

Pt

Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Alabama Location #7)

Before Period Mean

Speed

1st After Mean

Speed

2nd After Mean

Speed

Before 85th

Percentile Speed

1st After 85th

Percentile Speed

2nd After 85th

Percentile Speed

197
Table 71. Before-after operating speeds at Alabama Location #8.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 

before 41.540 6.029 44.644 8.437 40.657 5.331 42.239 6.340 376 341 310

All observations 

1st after 41.095 6.122 43.958 6.022 40.503 4.697 39.032 5.118 379 370 375

All observations 

2nd after 42.467 5.824 45.129 6.511 41.091 4.821 41.275 6.115 614 571 538

Passenger cars 

before 41.566 6.053 44.672 8.317 40.751 5.334 42.348 6.349 366 333 302

Passenger cars 

1st after 41.108 6.173 43.919 5.967 40.560 4.701 39.058 5.138 369 361 365

Passenger cars 

2nd after 42.416 5.734 45.213 6.434 41.106 4.798 41.320 6.144 587 548 515

Heavy trucks 

before 40.600 5.254 43.600 12.624 36.750 3.655 38.125 4.612 10 8 8

Heavy trucks 

1st after 40.600 3.978 45.400 8.072 38.222 4.116 38.100 4.458 10 9 10

Heavy trucks 

2nd after 43.593 7.582 43.296 7.927 40.739 5.429 40.261 5.446 27 23 23

Daytime 

passenger cars 

before

43.145 5.833 44.612 8.251 40.842 4.928 42.375 5.922 165 146 136

Daytime 

passenger cars 

1st after

41.245 6.185 43.931 5.902 40.428 4.732 38.951 5.148 306 299 303

Daytime 

passenger cars 

2nd after

42.984 5.802 45.665 6.153 40.865 4.563 41.108 6.125 367 347 334

Nighttime 

passenger cars 

before

40.269 5.934 44.721 8.391 40.679 5.642 42.325 6.696 201 187 166

Nighttime 

passenger cars 

1st after

40.444 6.117 43.857 6.319 41.194 4.533 39.581 5.101 63 63 62

Nighttime 

passenger cars 

2nd after

41.468 5.502 44.459 6.825 41.522 5.164 41.713 6.177 220 201 181

Opposed 

passenger cars 

before

41.750 6.708 42.841 7.546 40.823 6.354 42.000 7.255 88 79 71

Opposed 

passenger cars 

1st after

40.991 6.438 42.616 5.091 39.773 4.692 38.545 4.781 112 110 110

Opposed 

passenger cars 

2nd after

42.582 5.029 45.277 6.065 40.983 4.497 42.173 5.403 184 177 168

198
Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

Unopposed 

passenger cars 

before

41.507 5.842 45.252 8.477 40.728 4.988 42.455 6.057 278 254 231

Unopposed 

passenger cars 

1st after

41.160 6.066 44.486 6.235 40.904 4.673 39.278 5.279 257 251 255

Unopposed 

passenger cars 

2nd after

42.340 6.032 45.184 6.603 41.164 4.940 40.908 6.439 403 371 347

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before 

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods 

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 112 shows a graphical representation of the speed profiles for Alabama Location #8. The 

general shape of the speed profiles for the three collection periods remained relatively similar.

Figure 112. Graph. Operating speeds comparison at Alabama Location #8 (PSL = 35 mph).

α

α

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Alabama Location #8)

Before Period Mean

Speed

1st After Mean Speed

2nd After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

2nd After 85th

Percentile Speed

199
Alabama Summary of Results

Overall, the optical speed bars had no effect on operating speeds at the Alabama sites. There 

were no changes in speeds that were consistent across all sites.

Massachusetts

This section of the report presents the before-after comparisons for the seven Massachusetts OSB 

sites. 

Southbound Tucker Road, MA

As table 72 shows, operating speeds changed significantly at the southbound Tucker Road site in 

the after period. Oddly, speeds at the control point decreased between approximately 5.6 and 

7.3 mph for all passenger car speed metrics, and approximately 9.4 mph for heavy trucks. This 

difference in operating speeds at the control point cannot be explained, except it may be a result 

of a measurement error caused by the on-pavement sensor. Speeds in the after period remained 

relatively constant from the control point to the approach. Speeds increased slightly at the 

approach for the following speed metrics: all observations, passenger cars, daytime passenger 

cars, and unopposed passenger cars, with speed increases of approximately 0.8, 0.9, 1.2, and 

1.1 mph, respectively. These speed increases were minimal and were not practically significant. 

Speeds also increased at the PC for all measured speed metrics, with speeds increasing between 

approximately 3.0 and 3.7 mph for all passenger car speed metrics, and approximately 4.3 mph

for heavy trucks. Speeds in the first after period remained relatively constant from the control 

point to the approach. There was a sensor malfunction at the curve midpoint, and no speeds were 

collected and no t-test was performed. Speeds at the PC increased between 3.0 and 3.7 mph for 

passenger cars after the OSBs were installed at this site.

200
Table 72. Before-after operating speeds at southbound Tucker Road.

Speed

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

44.458 7.485 36.492 5.228 35.223 4.467 35.329 5.014 577 539 514

All 

observations 

after

37.651 5.164 37.337 5.164 38.547 6.650 0.000 0.000 341 139 0

Passenger 

cars before 44.466 7.510 36.506 5.236 35.241 4.475 35.334 5.022 573 535 512

Passenger 

cars after 37.753 5.147 37.428 5.169 38.569 6.692 0.000 0.000 332 137 0

Heavy 

trucks 

before

43.250 0.957 34.500 3.873 32.750 2.500 34.000 1.414 4 4 2

Heavy 

trucks after 33.889 4.567 34.000 3.873 37.000 2.828 0.000 0.000 9 2 0

Daytime 

passenger 

cars before

45.136 6.983 36.782 5.064 35.488 4.127 35.420 4.809 316 293 286

Daytime 

passenger 

cars after

38.616 5.033 37.966 5.145 38.493 7.690 0.000 0.000 203 71 0

Nighttime 

passenger 

cars before

43.642 8.048 36.167 5.431 34.942 4.855 35.226 5.289 257 242 226

Nighttime 

passenger 

cars after

36.395 5.049 36.581 5.114 38.652 5.476 0.000 0.000 129 66 0

Opposed 

passenger 

cars before

44.306 7.210 36.972 5.543 35.272 3.792 35.036 5.203 252 235 224

Opposed 

passenger 

cars after

38.686 5.503 37.822 5.583 38.390 8.812 0.000 0.000 118 41 0

Unopposed 

passenger 

cars before

44.592 7.745 36.140 4.960 35.217 4.951 35.566 4.874 321 300 288

Unopposed 

passenger 

cars after

37.238 4.876 37.210 4.926 38.646 5.603 0.000 0.000 214 96 0

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 113 shows a graphical representation of the speed profiles for southbound Tucker Road. 

In the after period, mean and 85th percentile speeds decreased significantly at the control point 

while they increased at the PC. Midpoint speeds were not available because of a sensor 

malfunction. 

α

201
Figure 113. Graph. Operating speeds comparison at southbound Tucker Road

(PSL = 30 mph).

Northbound Tucker Road, MA

As table 73 shows, operating speeds significantly changed at northbound Tucker Road, but the 

changes did not follow a clear trend. Speeds at the control point did not change in the first after

period. Speeds decreased slightly at the approach for the following speed metrics: all 

observations, heavy trucks, daytime passenger cars, and opposed passenger cars, with speed 

decreases of approximately 0.8, 0.7, 0.7, and 0.9 mph, respectively. These changes in speeds 

were minimal and not practically significant. Speeds at the PC increased between approximately 

1.8 and 3.1 mph for all speed metrics. However, speeds at the curve then decreased for all speed 

metrics, except heavy trucks. Speeds at the curve midpoint decreased between approximately 

1.1 and 1.7 mph. There was no strong trend in the effects of the OSBs at this site, with speeds 

significantly increasing at the PC but then decreasing at the curve midpoint.

30

40

50

60

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound Tucker Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th

Percentile Speed

202
Table 73. Before-after operating speeds at northbound Tucker Road.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

33.895 4.361 37.609 4.247 33.381 3.820 35.507 4.852 573 565 458

All 

observations 

after

33.761 4.403 36.850 5.004 35.768 4.249 33.904 5.674 394 367 355

Passenger cars 

before 33.919 4.361 37.633 4.251 33.403 3.820 35.525 4.858 569 561 455

Passenger cars 

after 33.903 4.347 36.911 5.037 35.821 4.230 33.980 5.645 383 358 348

Heavy trucks 

before 30.500 3.000 34.250 1.500 30.250 2.500 32.667 3.055 4 4 3

Heavy trucks 

after 28.818 3.516 34.727 3.133 33.667 4.743 30.143 6.283 11 9 7

Daytime 

passenger cars 

before

34.135 4.263 37.768 4.219 33.683 3.551 36.145 4.549 341 338 276

Daytime 

passenger cars 

after

34.416 3.787 37.024 4.764 36.771 3.545 34.455 5.391 209 192 187

Nighttime 

passenger cars 

before

33.596 4.495 37.430 4.300 32.978 4.167 34.570 5.168 228 223 179

Nighttime 

passenger cars 

after

33.287 4.877 36.776 5.358 34.723 4.680 33.429 5.896 174 166 161

Opposed 

passenger cars 

before

33.681 4.172 37.453 4.207 33.369 3.635 35.839 4.758 351 347 280

Opposed 

passenger cars 

after

34.126 4.032 36.581 4.621 36.017 3.937 34.320 4.864 191 179 172

Unopposed 

passenger cars 

before

34.303 4.634 37.922 4.315 33.458 4.111 35.023 4.986 218 214 175

Unopposed 

passenger cars 

after

33.682 4.640 37.240 5.412 35.626 4.506 33.648 6.313 192 179 176

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 114 shows a graphical representation of the speed profiles for northbound Tucker Road. 

In the after period, the mean and 85th percentile speeds increased slightly at the PC and 

midpoints. The control point and approach speeds remained relatively similar during both the 

before and after data-collection periods. 

α

203
Figure 114. Graph. Operating speeds comparison at northbound Tucker Road

(PSL = 35 mph).

Southbound Reed Road, Massachusetts

As table 74 shows, operating speeds changed significantly at the southbound Reed Road site in 

the first after period. Operating speeds decreased slightly at the control point for the following 

speed metrics: all observations, passenger cars, nighttime passenger cars, opposed passenger 

cars, and unopposed passenger cars, with speed decreases of approximately 1.2, 1.2, 2.7, 1.2, and 

1.1 mph, respectively. These speed decreases were not practically significant, except for the 

nighttime speed decrease of 2.7 mph. There was a sensor malfunction at the approach, so no 

speeds were collected, but the research team performed a t-test. Speeds increased significantly 

for all passenger car speed metrics at the PC, with speed increases between approximately 

1.4 and 3.8 mph. These speed increases become more significant and larger in magnitude if the 

speed decrease at the control point was taken into account. However, speeds were then 

significantly lower at the curve midpoint for all passenger car speed metrics. These speed 

decreases were approximately 2.7 to 4 mph. There was no clear trend in operating speeds at this 

site after the OSBs were installed. Operating speeds increased at the PC in the after period, but 

then operating speeds decreased at the curve midpoint.

30

35

40

45

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Northbound Tucker Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th

Percentile Speed

204
Table 74. Before-after operating speeds at southbound Reed Road.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 

before 39.966 5.426 39.382 6.015 38.826 4.288 39.363 4.990 775 482 590

All observations 

after 38.723 4.995 0.000 0.000 41.525 6.728 36.190 5.133 328 324 327

Passenger cars 

before 40.036 5.395 39.450 5.985 38.811 4.227 39.416 4.945 756 471 575

Passenger cars 

after 38.831 4.957 0.000 0.000 41.541 6.732 36.232 5.111 320 316 319

Heavy trucks 

before 37.211 6.070 36.684 6.758 39.455 6.654 37.333 6.355 19 11 15

Heavy trucks 

after 34.375 4.868 0.000 0.000 40.875 6.978 34.500 6.094 8 8 8

Daytime 

passenger cars 

before

39.754 5.282 39.249 6.262 38.558 3.773 39.692 4.767 337 224 247

Daytime 

passenger cars 

after

39.691 4.417 0.000 0.000 42.326 7.233 36.963 4.597 188 184 187

Nighttime 

passenger cars 

before

40.263 5.481 39.611 5.754 39.040 4.596 39.207 5.072 419 247 328

Nighttime 

passenger cars 

after

37.606 5.422 0.000 0.000 40.447 5.816 35.197 5.618 132 132 132

Opposed 

passenger cars 

before

39.971 5.365 39.753 6.653 38.669 3.911 39.469 4.916 377 242 275

Opposed 

passenger cars 

after

38.781 4.926 0.000 0.000 41.372 6.445 36.445 4.910 228 226 227

Unopposed 

passenger cars 

before

40.100 5.432 39.148 5.227 38.961 4.542 39.367 4.979 379 229 300

Unopposed 

passenger cars 

after

38.957 5.056 0.000 0.000 41.967 7.427 35.707 5.570 92 90 92

Bold indicates significance at 95 percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 115 shows a graphical representation of the speed profiles for southbound Reed Road. In 

the after period, mean speeds increased at the midpoint while 85th percentile speeds increased at 

the PC point. Approach speeds were not available because of a malfunctioning sensor. 

α

205
Figure 115. Graph. Operating speeds comparison at southbound Reed Road

(PSL = 25 mph).

Southbound New Boston Road, MA

Overall, operating speeds were higher in the after period at southbound New Boston Road. As 

table 75 shows, operating speeds increased for all passenger car speed metrics, with speed 

increases between approximately 1.3 to 4.2 mph. Speeds increased at the approach for the 

following speed metrics: all observations, passenger cars, heavy trucks, and opposed passenger 

cars, with speed increases of approximately 1.0, 0.9, 6.1, and 3.2 mph, respectively. However, if 

the speed increase at the control point was taken into account, speeds at the approach for all 

observations and passenger cars actually decreased slightly. Speeds increased at the PC for all 

passenger car speed metrics, with speed increases between approximately 1.6 and 2.7 mph. 

However, if the speed increase at the control point was taken into accounted, the speeds at the 

PC did not change from the before period for any passenger car speed metric. Speeds at the curve 

midpoint increased for all speed metrics, with speed increases between approximately 0.9 and

2.6 mph for passenger cars and 5.6 mph for heavy trucks. Once again, none of these speed 

increases for passenger cars were significant if the speed increase at the control point was taken 

into accounted. Operating speeds were higher at southbound New Boston Road in the after

period, but the OSBs had no effect on speeds after accounting for higher speeds at the control 

point. 

30

35

40

45

50

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound Reed Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

206
Table 75. Before-after operating speeds at southbound New Boston Road.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All observations 

before 37.004 6.532 37.704 5.967 37.489 5.607 36.624 6.206 257 229 229

All observations 

after 39.003 6.359 38.675 5.154 39.345 5.446 38.025 6.192 381 293 325

Passenger cars 

before 36.968 6.565 37.766 5.980 37.465 5.636 36.656 6.224 252 226 227

Passenger cars 

after 38.962 6.366 38.630 5.160 39.323 5.470 38.013 6.211 373 288 318

Heavy trucks 

before 38.800 4.712 34.600 4.722 39.333 2.082 33.000 0.000 5 3 2

Heavy trucks 

after 40.875 6.081 40.750 4.713 40.600 4.037 38.571 5.653 8 5 7

Daytime 

passenger cars 

before

36.690 5.930 37.655 5.583 37.576 4.603 36.760 5.551 113 99 100

Daytime 

passenger cars 

after

38.567 6.228 38.424 5.389 39.403 5.390 38.073 6.152 210 154 178

Nighttime 

passenger cars 

before

37.194 7.052 37.856 6.302 37.378 6.343 36.575 6.728 139 127 127

Nighttime 

passenger cars 

after

39.472 6.525 38.896 4.852 39.231 5.579 37.936 6.307 163 134 140

Opposed 

passenger cars 

before

35.638 5.307 36.259 5.872 36.788 5.410 35.962 6.145 58 52 52

Opposed 

passenger cars 

after

39.796 6.541 39.500 5.061 39.500 5.780 38.525 6.375 108 86 99

Unopposed 

passenger cars 

before

37.366 6.859 38.216 5.953 37.667 5.702 36.863 6.250 194 174 175

Unopposed 

passenger cars 

after

38.623 6.275 38.275 5.167 39.248 5.346 37.781 6.136 265 202 219

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 116 shows a graphical representation of the speed profiles for southbound New Boston 

Road. In the after period, 85th percentile speeds increased at the PC and midpoint. All other 

speed profiles remained relatively similar in the before and after data-collection periods. 

α

207
Figure 116. Graph. Operating speeds comparison on southbound New Boston Road (PSL =

35 mph).

Northbound New Boston Road, MA

As table 76 shows, operating speeds changed significantly at the northbound New Boston Road 

site in the after period. All observations and passenger car speeds increased at the control point 

by approximately 1.0 and 0.9 mph, respectively. These slight speed increases do not have any 

practical significance. Approach speeds increased for the following speed metrics: all 

observations, passenger cars, heavy trucks, nighttime passenger cars, and unopposed passenger 

cars, with speed increases of approximately 1.5, 1.4, 6.8, 2.3, and 1.5 mph, respectively. Speeds 

at the PC did not change in the after period. Speeds at the curve midpoint increased between 

approximately 2.8 and 4.5 mph for all speed metrics, except heavy trucks. Speeds significantly 

increased at the curve midpoint after the application of the OSBs at this site. Overall, the 

installation of the OSBs did not result in reduced operating speed at this site.

30

35

40

45

50

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound New Boston Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

208
Table 76. Before-after operating speeds at northbound New Boston Road.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

39.796 5.704 36.876 5.691 39.500 4.955 33.742 6.553 225 114 209

All 

observations 

after

40.769 7.248 38.356 6.573 39.559 6.720 37.568 7.593 320 118 229

Passenger cars 

before 39.857 5.680 36.928 5.686 39.558 4.939 33.720 6.563 223 113 207

Passenger cars 

after 40.780 7.267 38.366 6.555 39.535 6.781 37.546 7.608 314 114 227

Heavy trucks 

before 33.000 5.657 31.000 2.828 33.000 0.000 36.000 7.071 2 1 2

Heavy trucks 

after 40.167 6.706 37.833 8.159 40.250 5.315 40.000 7.071 6 4 2

Daytime 

passenger cars 

before

40.074 5.352 37.475 5.801 40.066 4.694 34.627 6.531 122 61 110

Daytime 

passenger cars 

after

40.719 7.186 38.270 6.268 39.134 6.080 37.443 7.915 196 67 131

Nighttime 

passenger cars 

before

39.594 6.070 36.267 5.499 38.962 5.194 32.691 6.478 101 52 97

Nighttime 

passenger cars 

after

40.881 7.430 38.525 7.031 40.106 7.704 37.688 7.207 118 47 96

Opposed 

passenger cars 

before

40.119 4.835 36.810 4.830 39.714 3.989 32.789 4.911 42 21 38

Opposed 

passenger cars 

after

40.662 8.230 37.954 5.792 38.048 6.561 37.289 7.884 65 21 38

Unopposed 

passenger cars 

before

39.796 5.870 36.956 5.878 39.522 5.149 33.929 6.874 181 92 169

Unopposed 

passenger cars 

after

40.811 7.012 38.474 6.747 39.871 6.819 37.598 7.572 249 93 189

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 117 shows a graphical representation of the speed profiles for northbound New Boston 

Road. Mean and 85th percentile speeds increased at the midpoint in the after period. The general 

shape of the speed profiles at all other locations remained relatively similar.

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209
Figure 117. Graph. Operating speeds comparison on northbound New Boston Road

(PSL = 35 mph).

Southbound Braley Hill Road, MA

As table 77 shows, operating speeds changed significantly at the southbound Braley Hill Road 

site in the after period. At the control point, daytime passenger car speeds increased by 

approximately 1.2 mph, and nighttime passenger car speeds decreased by approximately 

1.7 mph. Speeds at the approach were significantly higher for all speed metrics, with increases 

between 5.6 and 7.3 mph for the different passenger car speed metrics and 11.6 mph for heavy 

trucks. The speeds at the approach were approximately 5 to 6 mph higher than speeds at the 

control point in the after period. This does not reflect how drivers typically drive, so this 

significant increase at the approach may have resulted from a measurement error from the onpavement sensor. Speeds then decreased at the PC for the following speed metrics: all 

observations, passenger cards, nighttime passenger cars, opposed passenger cars, and unopposed 

passenger cars, with speed decreases of approximately 1.2, 1.2, 1.6, 1.9, and 1.0 mph, 

respectively. The speed decreases at the PC were small in magnitude and not practically

significant. Speeds at the curve midpoint also decreased in the after period for the following 

speed metrics: all observations, passenger cars, daytime passenger cars, nighttime passenger 

cars, and unopposed passenger cars, with speed decreases of approximately 2.2, 2.3. 1.7, 2.8, and 

2.5 mph, respectively. Speeds throughout the curve decreased between 1 and 3 mph at this site 

after the application of the OSBs; this did not consider the significant increase at the approach 

speed because that appears to be the result of a measurement error.

30

35

40

45

50

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Northbound New Boston Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

210
Table 77. Before-after operating speeds at southbound Braley Hill Road.

Speed 

Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

39.360 5.097 38.508 5.835 34.585 4.791 36.365 6.947 317 294 252

All 

observations 

after

39.040 5.667 45.191 7.031 33.415 4.160 34.176 7.407 277 260 256

Passenger 

cars before 39.472 5.136 38.600 5.872 34.665 4.693 36.502 6.905 305 284 243

Passenger 

cars after 39.208 5.645 45.075 6.760 33.520 4.174 34.244 7.497 265 250 246

Heavy 

trucks 

before

36.500 2.844 36.167 4.345 32.300 6.977 32.667 7.483 12 10 9

Heavy 

trucks after 35.333 5.033 47.750 11.671 30.800 2.821 32.500 4.577 12 10 10

Daytime 

passenger 

cars before

38.640 4.423 37.953 4.997 34.433 4.591 35.697 7.398 150 141 122

Daytime 

passenger 

cars after

39.801 4.950 45.298 6.401 33.701 4.205 34.038 7.345 141 134 132

Nighttime 

passenger 

cars before

40.277 5.640 39.226 6.566 34.895 4.797 37.314 6.297 155 143 121

Nighttime 

passenger 

cars after

38.532 6.297 44.823 7.164 33.310 4.146 34.482 7.696 124 116 114

Opposed 

passenger 

cars before

39.211 4.485 37.958 5.247 34.758 4.736 35.185 6.355 71 66 54

Opposed 

passenger 

cars after

38.981 5.634 44.096 7.604 32.837 4.520 33.820 7.176 52 49 50

Unopposed 

passenger 

cars before

39.551 5.324 38.795 6.046 34.638 4.691 36.878 7.025 234 218 189

Unopposed 

passenger 

cars after

39.263 5.660 45.315 6.534 33.687 4.080 34.352 7.591 213 201 196

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 118 shows a graphical representation of the speed profiles for southbound Braley Hill 

Road. In the after period, the mean and 85th percentile speeds increased significantly at the PC 

point. Speed profiles at all other points remained relatively similar during both the before and 

after data-collection periods.

α

211
Figure 118. Graph. Operating speeds comparison at southbound Braley Hill Road

(PSL = 30 mph).

Northbound Braley Hill Road, MA

As table 78 shows, operating speeds changed significantly at the northbound Braley Hill Road 

site in the after period. Oddly, speeds at the control point decreased between approximately 

6.1 and 7.8 mph for all speed metrics, except heavy trucks. Heavy truck speeds decreased by 

approximately 9.2 mph, but this was not significant because the SD was so high and there were 

few observations in both periods. This difference in operating speeds at the control point cannot 

be explained, except that it may be a result of a measurement error caused by the on-pavement 

sensor. Speeds at the approach did not change for any speed metric if the significant reductions 

in speeds at the control point were not taken into account. Speeds at the PC increased between 

approximately 2.8 and 4 mph for all speed metrics. These speed increases at the PC increase in

magnitude and become more significant if the speed decreases at the control were taken into 

accounted. Speeds at the curve midpoint also increased between approximately 1.0 and 1.4 mph 

for all speed metrics, except heavy trucks. Heavy truck speeds decreased by approximately 

2.7 mph, but this was not significant because there were few observations in both periods. These 

speed increases at the curve midpoint increased in magnitude and become more significant if the 

speed decreases at the control were taken into account. Based on the first after period, speeds at 

the PC and curve midpoint significantly increased after the application of the OSBs. The speed 

increase at the PC was higher than at the curve midpoint, with the speed increase at the curve 

midpoint not being practically significant at a maximum speed increase of 1.4 mph for all speed 

metrics.

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Southbound Braley Hill Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th Percentile

Speed

212
Table 78. Before-after operating speeds at northbound Braley Hill Road.

Speed Metric

Control 

Point 

Speed

Control 

Point 

SD

Approach 

Speed

Approach 

SD

PC 

Speed

PC 

SD

Mid 

Speed

Mid 

SD N1 N2 N3

All 

observations 

before

44.188 7.842 38.650 4.290 37.565 3.981 38.530 3.990 277 271 268

All 

observations 

after

37.166 6.209 38.456 4.774 40.500 4.758 39.719 4.198 331 224 320

Passenger cars 

before 44.169 7.738 38.692 4.294 37.603 3.993 38.572 3.992 273 267 264

Passenger cars 

after 37.185 6.201 38.469 4.759 40.541 4.795 39.748 4.168 324 218 313

Heavy trucks 

before 45.500 15.022 35.750 3.096 35.000 1.826 35.750 3.096 4 4 4

Heavy trucks 

after 36.286 7.017 37.857 5.815 39.000 2.966 38.429 5.623 7 6 7

Daytime 

passenger cars 

before

44.238 6.538 38.524 4.084 37.431 3.703 38.565 3.823 147 144 147

Daytime 

passenger cars 

after

37.994 5.366 38.893 4.567 40.518 4.922 39.921 4.115 169 137 164

Nighttime 

passenger cars 

before

44.087 8.965 38.889 4.536 37.805 4.315 38.581 4.210 126 123 117

Nighttime 

passenger cars 

after

36.303 6.910 38.006 4.934 40.580 4.604 39.557 4.230 155 81 149

Opposed 

passenger cars 

before

43.794 7.456 38.730 4.178 36.983 4.312 38.381 4.046 63 60 63

Opposed 

passenger cars 

after

37.703 5.891 38.099 3.981 40.457 5.413 39.644 4.193 91 70 90

Unopposed 

passenger cars 

before

44.281 7.835 38.681 4.338 37.783 3.889 38.632 3.983 210 207 201

Unopposed 

passenger cars 

after

36.983 6.319 38.614 5.031 40.581 4.493 39.789 4.166 233 148 223

Bold indicates significance at the 95-percent confidence level ( =0.05)

SD = Standard Deviation

PC = Point of Curvature 

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Figure 119 shows a graphical representation of the speed profiles for northbound Braley Hill 

Road. The mean and 85th percentile control point speeds decreased in the after period while 

speed profiles at all points remained relatively similar in both the before and after period. 

α

213
Figure 119. Graph. Operating speeds comparison at northbound Braley Hill Road

(PSL = 40 mph).

Massachusetts Results Summary 

Overall, the OSBs did not have an effect on operating speeds at the Massachusetts sites. There 

were no changes in speeds that were consistent across all of the sites.

Speed Difference Analysis

The next measures computed using the speed data were the change in speed from the approach to 

PC and the change in speed from the control point to the midpoint of the horizontal curve. These 

measures were taken in the before and both after periods at each of the treatment sites. As 

discussed previously, the research team used a t-test for independent samples to compare the two 

after periods with the before period and to each other. A positive value of delta speed indicates 

that a mean decrease in speed occurred from the approach to PC or from the control point to the 

curve midpoint. A negative value represents a mean increase in the speed difference between the 

two locations.

Arizona

Table 79 shows the change in speed (delta) from the approach to the PC and from the control 

point to the curve midpoint.

30

35

40

45

50

55

Control Pt Approach PC MidPt

Speed (mph)

Passenger Car Operating Speeds

(Northbound Braley Hill Road)

Before Period Mean

Speed

1st After Mean Speed

Before 85th Percentile

Speed

1st After 85th

Percentile Speed

214
Table 79. Change in speeds for Arizona sites.

Speed Metric

Delta Speed 

(Approach 

to PC)

Standard 

Deviation

Delta Speed 

(Control Point 

to Midpoint)

Standard 

Deviation N1 N2

NB Pierce Ferry Road before 0.267 4.527 10.514 7.776 90 107

NB Pierce Ferry Road 1st after 1.059 5.513 12.806 8.689 102 180

NB Pierce Ferry Road 2nd after 5.733 4.654 5.392 7.379 161 148

SB County Route 1 before 4.142 3.903 8.907 9.947 141 129

SB County Route 1 1st after 4.243 4.167 12.123 10.490 169 154

SB County Route 1 2nd after 2.216 3.438 5.183 10.640 97 60

SB Diamond Bar Road before -1.535 4.277 3.152 7.979 99 99

SB Diamond Bar Road 1st after -1.676 5.662 2.031 9.751 37 64

SB Diamond Bar Road 2nd after 1.547 3.856 11.600 8.375 53 105

SB Shinarump Road before 4.656 6.367 -3.973 7.219 90 73

SB Shinarump Road 1st after 4.043 4.798 -3.056 6.111 93 72

SB Shinarump Road 2nd after 3.149 6.500 3.566 9.846 101 136

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

NB = Northbound

SB = Southbound

PC = Point of Curvature

N1 = Number of observations approach to PC

N2 = Number of observations control point to midpoint

As table 79 shows, there was no difference in delta speed from the approach to the PC for any 

sites in the first after period. There was a significant increase in delta speed (control point to 

midpoint) of approximately 2.3 mph on northbound Pierce Ferry Road in the first after period. 

This was a result of vehicles having a slower speed at the curve midpoint in the first after period. 

There was also a significant increase in delta speed (control point to midpoint) of approximately 

3.2 mph on southbound County Route 1. This was a result of vehicles travelling faster at the 

control point in the first after period.

There were more significant changes in delta speed in the second after period than there were in 

the first after period, with delta speed changing at every site. Delta speed (approach to PC) from 

the approach to the PC increased by approximately 5.5 mph on northbound Pierce Ferry Road, 

which was a result of higher speeds at the PC in the second after period. Conversely, delta speed 

(control point to midpoint) decreased by approximately 5.1 mph on northbound Pierce Ferry 

Road, which was a result of higher speeds at the curve midpoint in the second after period. 

Speeds significantly decreased at this site at the PC on northbound Pierce Ferry Road, but then 

they significantly increased at the curve midpoint in the second after period. Delta speed 

(approach to PC) decreased by approximately 1.9 mph on southbound County Route 1, which 

was a result of higher speeds at the curve approach, but even higher speeds at the PC. Delta 

speed (control point to midpoint) also decreased by approximately 3.7 mph on southbound 

County Route 1, which resulted from vehicles accelerating out of the curve. Delta speed 

(approach to PC) was actually negative in the before period on southbound Diamond Bar Road, 

representing speeds increased from the approach to PC. However, delta speed (approach to PC) 

was positive in the second after period at this site. There was a significant increase of 

α

α

215
approximately 3.1 mph in delta speed, which was a result of vehicles accelerating slightly from 

the control point to the approach in the second after period. Delta speed (control point to 

midpoint) changed drastically in the second after period on southbound Diamond Bar Road. 

Delta speed increased by approximately 8.4 mph, which was a result of vehicles decelerating at a 

much greater rate from the PC to the curve midpoint in the second after period. Finally, delta 

speed (control point to midpoint) was actually negative in the before period, but delta speed was 

positive in the second after period. Delta speed (control point to midpoint) increased by 

approximately 7.5 mph on southbound Shinarump Road, which resulted from vehicles 

decelerating from the PC to the curve midpoint in the second after period, where vehicles 

accelerated from the PC to the curve midpoint in the before period.

Overall, delta speed did not change in the first after period after the OSBs were installed at the 

Arizona sites, but delta speeds were significantly different at all sites in the second after period. 

However, there was no clear trend in the change in delta speed as a result of installing the OSBs. 

Delta speed from the PC to the approach increased by approximately 5.5 and 3.1 mph at two 

sites, while delta speed decreased by approximately 1.9 mph at another site. Delta speed from the 

control point to the curve midpoint decreased by approximately 5.1 and 3.7 mph at two sites, 

while delta speed increased by approximately 8.4 and 7.5 mph at two other sites. The change in 

delta speed varied both in direction and magnitude across the different Arizona sites, with no 

strong trend present. Overall, the OSBs did not have an effect on operating speeds at the Arizona 

sites. There were no changes in speeds that were consistent across all of the sites. 

Alabama

Table 80 shows the change in speed (delta) from the approach to the PC and from the control 

point to the curve midpoint.

216
Table 80. Change in speeds for Alabama sites.

Speed Metric

Delta Speed 

(Approach 

to PC)

Standard 

Deviation

Delta Speed 

(Control Point 

to Midpoint)

Standard

Deviation N1 N2

Alabama Location #1 before 0.037 3.653 5.252 8.817 27 115

Alabama Location #1 1st after -0.933 4.173 0.549 7.154 134 213

Alabama Location #1 2nd after -0.685 3.947 8.695 10.378 73 226

Alabama Location #2 before 3.068 5.175 11.612 9.533 74 85

Alabama Location #2 1st after 3.127 3.909 9.533 7.555 220 246

Alabama Location #2 2nd after 2.526 3.984 10.210 7.864 234 276

Alabama Location #3 before 8.796 4.115 24.444 13.239 142 144

Alabama Location #3 1st after 6.418 3.244 30.227 13.700 225 234

Alabama Location #3 2nd after 7.160 3.253 27.872 12.219 306 298

Alabama Location #4 before 7.253 4.303 16.891 11.210 99 101

Alabama Location #4 1st after 8.534 3.981 16.823 9.590 236 237

Alabama Location #4 2nd after 8.560 4.400 14.489 10.179 241 229

Alabama Location #5 before 0.541 5.450 1.820 8.132 37 111

Alabama Location #5 1st after 0.097 4.304 -3.264 6.864 165 174

Alabama Location #5 2nd after -0.210 3.920 -1.738 6.337 176 191

Alabama Location #6 before -0.611 3.568 -0.964 12.250 54 56

Alabama Location #6 1st after 7.915 4.975 0.732 9.227 141 153

Alabama Location #6 2nd after 0.327 4.516 1.197 10.233 49 228

Alabama Location #7 before 6.827 3.501 14.381 8.213 127 126

Alabama Location #7 1st after 4.925 2.926 16.709 9.636 319 323

Alabama Location #7 2nd after 6.089 2.951 15.883 8.963 382 369

Alabama Location #8 before 3.838 4.295 0.290 6.497 105 100

Alabama Location #8 1st after 3.607 3.797 2.405 6.296 196 200

Alabama Location #8 2nd after 4.479 3.945 2.308 7.735 217 211

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

PC = Point of Curvature

N1 = Number of observations approach to PC

N2 = Number of observations control point to midpoint

As table 80 shows, there were many changes in the delta speed between the approach and the PC 

and the delta speed between the control point and the curve midpoint in Alabama. As table 80

shows, the speed difference from the approach to the PC increased for two sites in the first after

period, while the difference also decreased for two sites. The difference increased by 

approximately 8.5 mph at Alabama Location #6. This was a result of vehicles having a higher 

speed at the approach in the first after period. There was also a significant increase in delta speed 

of approximately 1.3 mph at Alabama Location #6. This was a result of vehicles having a slower 

speed at the PC in the first after period. The difference decreased by approximately 2.4 mph at 

Alabama Location #3. This was a result of vehicles having a slower speed at the approach in the 

first after period. There was also a significant decrease of approximately 1.9 mph at Alabama 

Location #7. This was a result of vehicles having a slower speed at the approach in the first after

period.

α

α

217
Most of the significant changes in delta speed (approach to PC) from the first after period were 

also significant in the second after period. The delta speed at Alabama Location #6 returned 

closer to the before period, and the difference was no longer significant in the second after

period. The delta speed at Alabama Location #3 returned closer to the before period, but the 

difference was still significant, with a decrease of approximately 1.6 mph. The delta speed at 

Alabama Location #4 was similar to the first after period, with a delta increase of approximately 

1.3 mph from the before period. The delta speed at Alabama Location #7 returned closer to the 

before period, but the difference was still significant, with an increase of approximately 0.7 mph.

As table 80 shows, the speed difference from the control point to the curve midpoint increased 

for three sites in the first after period, while the difference also decreased for three sites. The 

delta speed at Alabama Location #1 significantly decreased by approximately 4.7 mph. This was 

a result of vehicles having a slower speed at the control point. There was also a decrease in delta 

speed at Alabama Location #5 of approximately 5.1 mph. This was a result of speeds actually 

being higher at the curve midpoint than at the control point. Delta speed also decreased at 

Alabama Location #2 by approximately 2.1 mph. This was a result speeds at the curve midpoint 

increasing in the first after period.

In addition to the sites where there was a delta speed (control point to midpoint) difference from 

the before to first after period, there were also other sites where there was a change in delta speed 

in the second after period. Delta speed actually increased at Alabama Location #1 by 

approximately 3.4 mph, while there was a decrease in the first after period. This was a result of 

vehicles having a higher speed at the control point. The delta speed at Alabama Location #8 of 

was similar to the first after period, with a delta increase of approximately 2.0 mph from the 

before period. This was a result of vehicles having a higher speed at the control point and a lower 

speed at the curve midpoint. There was an increase in delta speed at Alabama Location #3 of 

approximately 3.4 mph. This was a result of vehicles having a higher speed at the control point. 

There was a decrease in delta speed at Alabama Location #4 of approximately 2.4 mph. This was

a result of control point speeds being slightly lower. There was a decrease in delta speed at 

Alabama Location #5 of approximately 3.6 mph. Speeds actually increased from the control 

point to the curve midpoint. There was an increase in delta speed at Alabama Location #7 of 

approximately 1.5 mph. This was a result of vehicles having a slower speed at the curve 

midpoint.

There were many changes in delta speed, but there was no clear trend in the change. Delta speed 

increased at several sites, while it also decreased at other sites. Many of the speed changes were 

a result of control point speeds changing from the before to after periods. These changes at the 

control point make it difficult to determine whether the OSBs had an effect on delta speed. The 

change in delta speed varied both in direction and magnitude across the different Alabama sites, 

with no strong trend present.

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Massachusetts

Table 81 shows the change in speed (delta) from the approach to the PC and from the control 

point to the curve midpoint.

Table 81. Change in speeds for Massachusetts sites.

Speed Metric

Delta Speed 

(Approach 

to PC)

Standard 

Deviation

Delta Speed 

(Control Point 

to Midpoint)

Standard 

Deviation N1 N2

NB Braley Hill Road before 0.714 2.685 5.769 5.783 91 91

NB Braley Hill Road after -1.313 3.009 -2.042 5.485 80 96

NB New Boston Road before -1.409 3.472 4.805 6.582 44 77

NB New Boston Road after -0.551 3.731 3.373 9.249 49 102

NB Reed Road before 0.380 2.432 11.155 7.481 50 110

NB Tucker Road before 3.889 2.603 -1.931 5.164 72 58

NB Tucker Road after 1.027 3.820 0.293 6.415 75 75

SB Braley Hill Road before 4.021 4.786 2.402 7.960 94 82

SB Braley Hill Road after 11.126 5.021 5.765 7.726 103 102

SB Tucker Road before 0.957 3.440 9.717 7.580 117 120

SB Tucker Road after 0.976 5.015 - - 42 -

SB Reed Road before 1.563 3.956 0.343 5.573 64 73

SB Reed Road after - - 3.566 6.116 - 53

SB New Boston Road before 0.125 3.485 -0.167 7.053 64 66

SB New Boston Road after -0.809 3.465 0.1 6.208 110 120

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

NB = Northbound

SB = Southbound

PC = Point of Curvature

N1 = Number of observations approach to PC

N2 = Number of observations control point to midpoint

As table 81 shows, there were many changes in the delta speed between the approach and the PC 

and the delta speed between the control point and the curve midpoint in Massachusetts. Delta 

speed (approach to PC) on northbound Braley Hill Road decreased by approximately 2.0 mph. In 

the before period delta speed was positive, which represents a decrease in speed from the 

approach to the PC. However, in the after period delta speed (approach to PC) was negative. 

Delta speed (control point to midpoint) also decreased in the after period on northbound Braley 

Hill Road by approximately 7.8 mph. Delta speed (control point to midpoint) was also negative 

in the second after period, which was a result from the control point speed being significantly 

lower and vehicles maintaining a more constant speed throughout the curve. As previously 

discussed, this was most likely a result of measurement error with the on-pavement sensor at the 

control point. There was also a decrease in delta speed (approach to PC) on northbound Tucker 

Road of approximately 2.9 mph. However, delta speed (control point to midpoint) increased in 

the first after period by approximately 2.2 mph. Delta speed was negative in the before period, 

but was positive in the first after period. Next, delta speed (approach to PC) and delta speed 

(control point to midpoint) increased by approximately 7.1 and 3.4 mph, respectively, on 

southbound Braley Hill Road. The large increase in delta speed (approach to PC) was the result 

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of a significant increase in speeds at the approach, which was most likely the result of a 

measurement error with the on-pavement sensor, as previously discussed. Delta speed (control 

point to midpoint) increased as a result of speeds being lower at the curve midpoint in the first 

after period. Next, there was an increase in delta speed (control point to midpoint) on southbound 

Reed Road of approximately 3.2 mph. This was a result of lower speeds at the curve midpoint in 

the after period. Because approach speeds were not collected at this site in the first after period, a 

delta speed between the approach and PC was not calculated. Finally, delta speed (approach to 

PC) on southbound New Boston Road decreased by approximately 0.9 mph. This was a minimal 

decrease, and vehicles essentially maintained their speed from the approach to PC in both the 

before and first after period.

Unlike the Arizona sites, there was a weak trend in the change of delta speed at the 

Massachusetts sites. If the change in delta speed between the approach and PC on southbound 

Braley Hill Road was ignored because there most likely was a problem with the on-pavement 

sensor, the delta speed between the approach and PC decreased at three sites and remained the 

same at two others. If the change in delta speed between the control point and curve midpoint on

southbound Braley Hill Road was ignored because there most likely was a problem with the onpavement sensor, the delta speed between the control point and curve midpoint decreased at two 

sites, increased at one site, and remained the same at two sites. The OSBs may have a small 

effect on the delta speed between the approach and the PC and the delta speed between the 

control point and curve midpoint by decreasing the difference slightly.

Analysis of Variance for Speed Differences

An analysis of variance was used to compare speed differences in the before and after periods.

The results are organized and grouped by State.

Arizona

As table 82 shows, the speed difference between the control point and the curve midpoint in the 

first after period significantly increased by 2.82 mph, which was a result of speeds at the curve 

midpoint decreasing and speeds at the control point increasing. The speed difference also 

increased in the second after period; however, this increase was not statistically significant. After 

installing the additional OSBs, the speed difference did not decrease from the control point to 

curve midpoint after the novelty effect period.

Table 82. Speed difference between the control point and the curve midpoint.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

First after period 35.62 < 0.001 2.82

Second after period 1.35 0.246 0.57

Second after period 

(additional OSBs installed) 2.71 0.100 -0.92

Bold indicates significance at the 95-percent confidence level ( =0.05)

OSB = Optical Speed Bar

As table 83 shows, there was an increase in the speed difference from the approach to the PC in 

the first after period; however, this increase was not significant. There was a significant increase 

in the speed difference in the second after period and after installing the additional OSBs of 

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1.33 and 1.41 mph, respectively. The increase in the difference from the approach to the PC in 

the second after period may show that the OSBs were effective in reducing drivers’ speeds while 

in the OSBs.

Table 83. Speed difference between the approach and the PC.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

First after period 8.39 0.004 0.73

Second after period 26.11 <0.001 1.33

Second after period 

(additional OSBs installed) 23.08 <0.001 1.41

Bold indicates significance at the 95-percent confidence level ( =0.05)

OSB = Optical Speed Bar

As table 84 shows, the speed difference from the control point to the PC in the first before period 

significantly increased by 2.20 mph. The speed difference also increased in the second after

period and after installing the additional OSBs; however, these increases were not significant.

Table 84. Speed difference between the control point and the PC.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

First after period 26.00 <0.001 2.20

Second after period 1.11 0.292 0.47

Second after period 

(additional OSBs installed) 0.35 0.552 0.30

Bold indicates significance at the 95-percent confidence level ( =0.05)

Alabama

As table 85 shows, the speed difference from the control point to the curve midpoint in the first 

after period did not significantly change. The speed difference significantly increased in the 

second after period by approximately 0.68 mph. After installing the additional OSBs, the speed 

difference decreased slightly from the control point to the curve midpoint. This decrease was not 

practically significant.

Table 85. Speed difference between the control point and the curve midpoint.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

First after period 2.14 0.143 0.51

Second after period 4.38 0.036 0.68

Bold indicates significance at 95 percent confidence level ( =0.05)

As table 86 shows, the speed difference from the approach to the PC significantly decreased in 

the after periods, which means that vehicles maintained a more constant speed as they 

approached the curve.

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Table 86. Speed difference between the approach and the PC.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

First after period 34.65 <0.001 -0.81

Second after period 28.68 <0.001 -0.7

Bold indicates significance at the 95-percent confidence level ( =0.05)

As table 87 shows, the speed difference from the control point to the PC significantly decreased 

in the first after period, but there was no significant change in the second after period. The 

decrease in the first after period was approximately 1.68 mph. This corresponds with the 

decrease in the difference from the approach to the PC, and vehicles maintained a more constant 

speed from the control point to the PC.

Table 87. Speed difference control Point to PC.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

First after period 20.93 <0.001 -1.68

Second after period 0.05 0.829 0.08

Bold indicates significance at the 95-percent confidence level ( =0.05)

Massachusetts

As table 88, table 89, and table 90 show, all three speed differences decreased in the after period 

at the Massachusetts sites, with speed becoming more uniform throughout the horizontal curves. 

There was much variability in the speed changes at the different sites in Massachusetts, with the 

speed differences increasing at some sites, while decreasing at others. Overall, the analysis of 

variance shows the speed difference decreased from the control point to the curve midpoint, the 

approach to the PC, and the control point to the PC, with speed difference decreases of 

1.80, 1.88, and 4.87 mph, respectively.

Table 88. Difference between the control point and the curve midpoint.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

After period 48.78 <0.001 -1.80

Bold indicates significance at the 95-percent confidence level ( =0.05)

Table 89. Difference between the approach and the PC.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

After period 71.87 <0.001 -1.88

Bold indicates significance at the 95-percent confidence level ( =0.05)

Table 90. Difference between the control point and the PC.

Time Period F Statistic Significance

Magnitude of 

Difference (mph)

After period 508.45 <0.001 -4.87

Bold indicates significance at the 95-percent confidence level ( =0.05)

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Vehicles Exceeding the Posted Speed Limit

Finally, in addition to the t-test, the percentage of vehicles exceeding the PSL and the advisory 

speed at the treatment and control sites was calculated and compared between data-collection 

periods. The following sections present the results for each State.

Arizona

Table 91 shows the number of passenger cars observed as exceeding the speed limit at each 

location at every site in Arizona in the before and both after periods. A test of proportions was 

used to determine whether the proportion of speeding vehicles changed at each location of every 

site from the before to after treatment application. From table 91, it was clear there were no 

visible trends from the before period to after treatment application. There was no change in the 

proportion of passenger cars exceeding the speed limit at the control point at any site, in any 

analysis period. The only change in proportion of passenger cars exceeding the speed limit at the 

approach was in the second after period on southbound Diamond Bar Road, where slightly fewer 

vehicles exceeded the speed limit. These results were expected because these data collection 

points were before or at the beginning of the OSBs, so no change would be expected. The only 

change at the PC between the before and after periods was the proportion of vehicles exceeding 

the PSL on northbound Pierce Ferry Road decreased in the second after period. The effect of the 

OSBs on the proportion of vehicles exceeding the speed limit varies from site to site and from 

the first to second after period. On northbound Pierce Ferry Road, the proportion decreased in 

the first after period, but then it increased in the second after period. On southbound County 

Route 1, the proportion decreased in the first after period, but then returned to the proportion in 

the before period. On southbound Diamond Bar Road, the proportion increased in the first after

period, but then decreased in the second after period. On southbound Shinarump Road, the 

proportion decreased in the second after period. The fact that there was no trend in the change of 

the proportion of vehicles exceeding the speed limit and those with decreased speeds, while 

others increased, probably means the OSBs had no effect.

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Table 91. Number of vehicles exceeding the PSL in Arizona.

Location and Data Collection 

Period

Speed Observation Site

NB Pierce 

Ferry Rd

SB County 

Route 1

SB Diamond 

Bar Rd

SB Shinarump 

Rd

Control Point PCs

Before 83 145 115 55

1st after 138 173 73 62

2nd after 127 100 89 90

Approach PCs

Before 69 147 95 71

1st after 106 174 63 70

2nd after 101 102 96 101

PC PCs 

Before 57 139 80 59

1st after 60 166 25 52

2nd after 39 97 47 61

Midpoint PCs

Before 21 122 80 55

1st after 15 135 43 56

2nd after 77 58 30 62

Number of PCs at 

Control Point and

Approach

Before 108 147 136 96

1st after 186 175 92 98

2nd after 162 102 108 146

Number of PCs at 

PC

Before 90 141 99 90

1st after 102 169 37 93

2nd after 161 97 53 101

Number of PCs at 

Midpoint

Before 107 129 99 73

1st after 180 154 64 72

2nd after 148 60 105 136

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

NB = Northbound

SB = Southbound

PC = Point of Curvature

Alabama

Table 92 shows the number of passenger cars observed to exceed the speed limit at each location 

at every site in Alabama in the before and both after periods. A test of proportions was used to 

determine whether the proportion of speeding vehicles changed at each location of every site 

from the before to after treatment application. From table 92, it was clear there were no longterm effects on the number of vehicles speeding after the application of the OSBs. 

Alabama locations #1, #2, and #3 were the only sites where there was a change in the proportion 

of vehicles exceeding the speed limit at the control point. The proportion decreased at Alabama

Location #1 in the first after period, but returned to the before period proportion in the second 

after period. The proportion decreased at Alabama Location #2 in the second after period, but 

increased at Alabama Location #3. The proportion of vehicles exceeding the speed limit at the 

approach decreased in the first after period at Alabama locations #1, #3, and #7, but the 

decreased proportions were only maintained through the second after period at Alabama

Location #3. The proportion of vehicles exceeding the speed limit at the approach increased for 

Alabama Location #6 in the first after period and Alabama Location #8 in the second after

period. The only change in the proportion of vehicles exceeding the speed limit at the PC was a 

decrease as in the first after period. The proportion of vehicles exceeding the speed limit 

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decreased during the first after period at the following locations: #6, #8, #4, #2, and #7. 

However, the reductions were only maintained through the second after period at locations #6 

and #7. The proportion of vehicles exceeding the speed limit increased at Location #5 during 

both after periods. There was no visible long-term trend in the effects of the OSBs on the 

proportion of vehicles exceeding the PSL. There was a decrease at the curve midpoint for only 

two sites in the second after period, but there was also an increase at another site. The fact that 

there was no consistent trend in the change of the proportion of vehicles exceeding the speed 

limit, but no change at most sites, probably means the OSBs had no effect.

Table 92. Number of vehicles exceeding the PSL in Alabama.

Location and Data 

Collection Period

Speed Observation Site

Alabama 

Location 

#6

Alabama 

Location 

#1

Alabama 

Location 

#8

Alabama 

Location 

#3

Alabama 

Location 

#4

Alabama 

Location 

#5

Alabama 

Location 

#2

Alabama 

Location 

#7

Control 

Point PCs

Before 85 28 107 131 100 75 22 126

1st after 109 5 171 214 226 135 40 314

2nd 

after 180 50 216 302 239 177 43 383

Approach 

PCs

Before 96 24 109 31 99 90 2 122

1st after 156 14 193 19 231 165 7 284

2nd 

after 196 26 229 42 238 192 7 364

PC PCs 

Before 47 9 92 0 86 30 0 89

1st after 110 8 174 1 157 117 2 197

2nd 

after 38 13 193 4 199 125 3 236

Midpoint 

PCs

Before 42 5 92 1 44 50 2 105

1st after 79 3 152 0 62 128 0 168

2nd 

after 119 7 178 7 108 143 1 230

Number 

of PCs at 

Control 

Point & 

Approach

Before 118 125 117 152 103 118 97 128

1st after 165 218 201 235 237 244 250 323

2nd 

after 253 256 234 323 244 277 303 393

Number 

of PCs at 

PC

Before 54 27 105 142 99 37 74 127

1st after 141 134 196 225 236 165 220 319

2nd 

after 49 73 217 306 241 176 303 382

Number 

of PCs at 

Midpoint

Before 56 115 100 144 101 111 85 126

1st after 153 213 200 234 237 174 246 323

2nd 

after 228 226 211 298 229 191 234 369

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and before

period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

PC = Point of Curvature

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Massachusetts

Table 93 shows the number of passenger cars observed that exceeded the speed limit at each 

location at every site in Massachusetts in the before and both after periods. A test of proportions 

was used to determine whether the proportion of speeding vehicles changed at each location of 

every site from the before to after treatment application. From table 93, it was clear there were 

no visible trends from the before period to after treatment application. Northbound Braley Hill 

Road and northbound Tucker Road were the only sites where there was a change in the 

proportion of vehicles exceeding the speed limit at the control point. The proportion decreased 

on northbound Braley Hill Road, but increased on northbound Tucker Road. Northbound Tucker 

Road was the only site where there was a change in the proportion of vehicles exceeding the 

speed limit at the approach. The proportion increased, which corresponds with the increase in the 

proportion at the control point. Northbound Braley Hill Road and northbound Tucker Road were 

the only sites where there was a change in the proportion of vehicles exceeding the speed limit at 

the PC. The proportion increased at both sites, which corresponds with the increase in the 

proportion at the control point of northbound Tucker Road. The increase on northbound Braley 

Hill Road does not correspond with the change at the control point because the proportion 

decreased there. Finally, these two sites were the only sites where there was a change in the 

proportion of vehicles exceeding the speed limit at the curve midpoint. The proportion increased 

at both sites, which corresponds with the increase in the proportion at the control point of 

northbound Tucker Road. Again, the increase does not correspond with the change at the control 

point, because the proportion decreased there. There was no visible trend in the effects of the 

OSBs on the proportion of vehicles exceeding the PSL. There was a change at two sites only, 

and at one site, there was also an increase in the proportion at the control point. The fact that 

there was no trend in the change of the proportion of vehicles exceeding the speed limit, with an 

increase at several sites but no change at most sites, probably means the OSBs had no effect. 

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Table 93. Number of vehicles exceeding the PSL in Massachusetts.

Location and Data 

Collection Period

Speed Observation Site

NB 

Braley 

Hill Rd

NB New 

Boston 

Rd

NB 

Reed 

Rd

NB 

Tucker 

Rd

SB 

Braley 

Hill Rd

SB 

Tucker 

Rd

SB 

Reed 

Rd

SB New 

Boston 

Rd

Control Point 

PCs

Before 69 69 116 27 95 124 102 49

1st after 33 116 - 68 106 110 53 110

2nd after 0 0 0 0 0 0 0 0

Approach PCs

Before 28 54 114 51 95 116 101 56

1st after 39 97 - 77 109 108 - 104

2nd after 0 0 0 0 0 0 0 0

PC PCs 

Before 18 38 50 27 79 103 64 43

1st after 40 37 - 72 90 38 49 85

2nd after 0 0 0 0 0 0 0 0

Midpoint PCs

Before 28 38 72 32 69 106 72 42

1st after 45 64 - 58 77 - 51 85

2nd after 0 0 0 0 0 0 0 0

Number of PCs 

at Control Point 

& Approach

Before 91 85 116 73 98 127 103 75

1st after 100 143 - 81 109 114 53 148

2nd after 0 0 0 0 0 0 0 0

Number of PCs 

at PC

Before 91 44 50 72 94 117 64 64

1st after 80 49 - 75 103 42 51 110

2nd after 0 0 0 0 0 0 0 0

Number of PCs 

at Midpoint

Before 91 77 110 58 82 120 73 66

1st after 96 102 - 75 102 - 53 120

2nd after 0 0 0 0 0 0 0 0

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

NB = Northbound

SB = Southbound

PC = Point of Curvature

Speed Variance Analysis

The final speed performance metric considered in the current study was speed variance. A twosided F-test was used to compare the variances of vehicle operating speeds in the before and 

after periods for passenger cars and heavy trucks. The results are organized by State.

Arizona

Table 94 shows the SD of speeds at each location at every site in Arizona for the before and both 

after periods. From table 93, it was clear there were no visible trends in a change in SD from the 

before period to first after period. The SD of control point speeds did not change at any site in 

the first after period. Northbound Pierce Ferry Road was the only site where there was a change 

in the SD of approach speeds, which was an increase of approximately 1.3 mph. There was also 

an increase of approximately 1.2 mph in the SD of speeds at the PC of northbound Pierce Ferry 

Road. There was no change in the SD of speeds at the PC at any other site. Finally, there was no 

change in the SD of speeds at the curve midpoint of any site.

As in the first after period, there were no visible trends in the change in SD from the before to 

second after period. The only change at the control point was on southbound Shinarump Road, 

where the SD increased by approximately 1.3 mph. There was no change in the SD of the speeds 

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at the approach. There was a change in the SD of speeds at the PC for both northbound Pierce 

Ferry Road and southbound Shinarump Road. The SD decreased by approximately 1.0 mph on 

northbound Pierce Ferry Road and increased by approximately 3.3 mph on southbound 

Shinarump Road. The increase on southbound Shinarump Road was still significant even after

accounting for the increase at the control point. Finally, there was no change in the SD of speeds 

at the curve midpoint between the second after period and the before period. If the OSBs had any 

effect on the speed deviation, it would have been most prevalent at the PC and curve midpoint, 

because these were after the OSBs. The fact that there was no consistent trend in the change of 

the SD of speeds at most sites probably means the OSBs had no effect.

Table 94. Change in standard deviation of speed in Arizona.

Site

Control 

Point SD

Approach 

SD PC SD

Midpoint 

SD N1 N2 N3

NB Pierce Ferry Road before 7.308 7.121 5.795 6.695 108 90 107

NB Pierce Ferry Road 1st after 7.836 8.415 6.970 5.989 186 102 180

NB Pierce Ferry Road 2nd after 7.377 6.373 4.753 7.012 162 161 148

SB County Route 1 before 9.132 5.325 4.846 6.655 147 141 129

SB County Route 1st after 9.497 5.280 4.544 7.241 175 169 154

SB County Route 2nd after 9.920 5.562 5.347 7.531 102 97 60

SB Diamond Bar Road before 8.543 7.230 6.758 7.590 136 99 99

SB Diamond Bar 1st after 9.450 7.161 8.636 8.862 92 37 64

SB Diamond Bar 2nd after 9.244 8.364 6.781 7.215 108 53 105

SB Shinarump Road before 7.047 8.893 6.248 7.692 96 90 73

SB Shinarump Road 1st after 6.374 7.863 6.713 8.109 98 93 72

SB Shinarump Road 2nd after 8.309 9.902 9.530 6.813 146 101 136

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

NB = Northbound

SB = Southbound

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

Alabama

Table 95 shows the SD of speeds at each location at every site in Alabama for the before and 

both after periods. From table 95, it was clear there were no visible trends in the change in SD

from the before period to first after period. The only change in the SD at the control point was at 

Location #1, which was a decrease of approximately 1.8 mph. The OSBs were not visible at this 

location, which corresponds to the SDs remaining the same as the before period. The SD

decreased at the approach at locations #8 and #4 by approximately 2.1 and 2.2 mph, respectively. 

The SD also decreased at the PC at Location #1 and Location #2 by approximately 3.4 and 

1.5 mph, respectively. The SD decreased at the curve midpoint at Location #4 and Location #2 

by approximately 2.0 and 2.4 mph, respectively. However, the SD increased at the curve 

midpoint at Location #3 by approximately 2.4 mph. 

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As in the first after period, there were no visible trends in the change in the SD from the before

to second after period. The SD decreased at the control point at Location #4 by approximately 

1.7 mph. As in the first after period, the SD decreased at the approach at Location #8 and 

Location #3 by approximately 1.9 and 1.5 mph, respectively. The SD also increased at the 

approach at Location #6 by approximately 1.3 mph. The only change at the PC was the SD

increased at Location #3 by approximately 0.6 mph. The SD increased at the curve midpoint at 

Location #1 by approximately 2.4 mph. As in the first after period, the SD increased at the curve 

midpoint at Location #3 by approximately 1.3 mph. The SD decreased at the curve midpoint at 

Location #2 by approximately 1.8 mph. If the OSBs had any effect on the speed deviation, it 

would have been most prevalent at the PC and curve midpoint, because these were after the 

OSBs. The SD decreased at the PC for two sites in the first after period, but these decreases did 

not persist throughout the second after period. The fact that there was no consistent trend in the 

change of the SD of speeds at most sites, with an increase at some sites, probably means the 

OSBs had no effect.

Table 95. Change in standard deviation of speed in Alabama.

Site

Control 

Point SD

Approach 

SD PC SD

Midpoint 

SD N1 N2 N3

Alabama Location #1 before 8.953 7.773 8.541 6.979 125 27 115

Alabama Location #11st after 7.113 6.823 5.181 6.102 218 134 213

Alabama Location #1 2nd after 7.959 6.901 7.593 9.344 256 73 226

Alabama Location #2 before 7.218 5.239 5.980 7.485 97 74 85

Alabama Location #2 1st after 6.986 4.882 4.532 5.038 250 220 246

Alabama Location #2 2nd after 7.132 5.105 5.221 5.651 303 234 276

Alabama Location #3 before 12.267 6.872 4.058 5.495 152 142 144

Alabama Location #3 1st after 11.686 4.676 4.349 7.731 235 225 234

Alabama Location #3 2nd after 11.413 5.385 4.655 6.809 323 306 298

Alabama Location #4 before 9.000 5.784 4.627 7.770 103 99 101

Alabama Location #4 1st after 8.434 5.462 4.126 5.790 237 236 237

Alabama Location #4 2nd after 7.286 5.883 4.677 8.131 244 241 229

Alabama Location #5 before 6.783 7.346 6.959 6.603 118 37 111

Alabama Location #5 1st after 6.687 6.808 6.126 7.155 244 165 174

Alabama Location #5 2nd after 6.704 7.059 6.159 7.098 277 176 191

Alabama Location #6 before 9.141 5.970 6.466 8.027 118 54 56

Alabama Location #6 1st after 8.521 8.573 6.578 7.108 165 141 153

Alabama Location #6 2nd after 9.615 7.279 7.619 7.857 253 49 228

Alabama Location #7 before 9.446 5.276 4.730 5.497 128 127 126

Alabama Location #7 1st after 9.866 5.229 4.307 5.052 323 319 323

Alabama Location #7 2nd after 9.392 5.449 4.246 5.431 393 382 369

Alabama Location #8 before 5.742 8.262 4.442 5.804 117 105 100

Alabama Location #8 1st after 6.192 6.198 4.723 5.335 201 196 200

Alabama Location #8 2nd after 6.249 6.372 4.895 6.486 234 217 211

Bold indicates significance at the 95-percent confidence level ( =0.05) between the 1st/2nd after period and 

before period

Italics indicates significance at the 95-percent confidence level ( =0.05) between the 1st and 2nd after periods

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

α

α

229
Massachusetts

Table 96 shows the SD of speeds at each location at every site in Massachusetts for the before

and both after periods. Unlike at the Arizona sites, there may have been a change in the SD of 

speeds after installing the OSBs. The SD of speeds at the control point increased by 

approximately 1.6 mph on northbound New Boston Road, decreased by approximately 0.6 mph

on northbound Tucker Road, and decreased by approximately 2.4 mph on southbound Tucker 

Road. These changes were not the result of applying the OSBs because they were not visible 

from the control point. The SD of speeds at the approach increased by approximately 1.0 mph on

northbound Braley Hill Road, 1.3 mph on northbound Tucker Road, and 1.5 mph on southbound

Braley Hill Road. The optical speeds bars may have affected these SDs as they would be visible 

prior to reaching the approach. The SD of speeds at the PC increased by approximately 1.1 mph

on northbound Braley Hill Road, 4.1 mph at southbound Reed Road, and 0.8 mph on southbound 

New Boston Road. Finally, the SD of speeds at the curve midpoint increased by approximately 

2.2 mph on northbound Tucker Road. All of these changes were still significant after accounting 

for the changes at the control point, because there was no change at the control point for any of 

these sites, except northbound Tucker Road, but the SD decreased at that site. The SD at the 

approach increased between 1.0 and 1.5 mph at three sites and remained the same at the other 

three in the after period. The SD at the PC increased between 0.8 and 4.1 mph at three sites and 

remained the same at the other four sites in the after period. The SD at the curve midpoint 

increased by 2.2 mph at one site and remained the same at the five other sites. It appears the SD

may increase slightly at the approach and PC, while remaining the same at the curve midpoint 

after installing the OSBs.

Table 96. Change in standard deviation of speed in Massachusetts.

Site

Control 

Point SD

Approach 

SD PC SD

Midpoint 

SD N1 N2 N3

NB Braley Hill Road before 5.855 3.912 3.202 3.698 91 91 91

NB Braley Hill Road 1st after 5.390 4.908 4.269 3.891 100 80 96

NB New Boston Road before 5.523 6.106 4.877 7.002 85 44 77

NB New Boston Road 1st after 6.820 6.336 5.826 8.009 143 49 102

NB Tucker Road before 4.471 3.708 3.388 4.059 73 72 58

NB Tucker Road 1st after 3.653 5.005 3.625 6.242 81 75 75

SB Braley Hill Road before 4.519 4.577 4.536 7.847 98 94 82

SB Braley Hill Road 1st after 4.856 6.085 3.957 7.277 109 103 102

SB Tucker Road before 7.357 4.281 4.870 4.579 127 117 120

SB Tucker Road 1st after 4.964 4.673 5.861 0.000 114 42 0

SB Reed Road before 5.203 5.096 4.094 5.093 103 64 73

SB Reed Road 1st after 4.587 0.000 8.267 4.757 53 51 53

SB New Boston Road before 6.132 5.332 4.496 5.412 75 64 66

SB New Boston Road 1st after 5.952 5.376 5.277 6.162 148 110 120

Bold indicates significance at the 95-percent confidence level ( =0.05)

NB = Northbound

SB = Southbound

SD = Standard Deviation

PC = Point of Curvature

N1 = Number of observations at the control point and approach

N2 = Number of observations at the PC

N3 = Number of observations at the midpoint

α

230
SUMMARY

Results of this study showed that OSBs may have some minor effects on vehicle speeds. 

However, the magnitude of speed reductions was generally small, and because of the 

inconsistent magnitude of speed reductions at all the test sites, no conclusion can be drawn 

regarding the effect of OSB treatment to reduce speeds. Even though minor speed reductions 

occurred at some locations, average and 85th percentile speeds observed at all the sites were still 

higher than the PSLs, indicating the OSBs were not effective enough in providing the desired 

speed limit compliance. Future analyses may consider featuring an enforcement component, 

which was out of the scope of this study.

It is clear from the data that driver operating speeds are influenced by the curve radius. Further, 

the benefits gained by a reduction in driver operating speeds before the PC may be lost as drivers 

compensate and accelerate through the curve (for treatments that end prior to the PC). While this 

study did not show any consistent benefits as a result of installing the OSBs, consideration 

should be given to extending the treatment through the curve—keeping in mind that the entrance 

and midpoint are the most severe areas.

231

6. SAFETY EFFECTS OF LANE-WIDTH–SHOULDER-WIDTH COMBINATIONS ON 

RURAL, TWO-LANE ROADS

This section of the report describes a study to estimate the safety effects of lane width–shoulder 

width combinations on rural two-lane, two-way roads. This report first describes the background 

and study motivation. Next, it discusses the process for collecting safety data, including steps for 

identifying and defining segments, measuring geometric features, and gathering traffic and crash 

data. The research team then presents the statistical analysis methods for estimating the effects of 

lane and shoulder width allocation on both crash frequencies and severities; this is followed by 

the model estimation results and interpretation. The section concludes with a discussion of major 

findings and considerations for future research. 

OVERVIEW

The conclusion that safety increases as lane width increases is based on the premise that wider 

lanes reduce the consequences of driver deviations from their intended path. Vehicles traveling 

in opposite directions on undivided, two-way roads are separated by larger distances if lanes are 

wider. Vehicles traveling in the same direction on multilane roads are also separated by larger 

distances if lanes are wider. Wider lanes provide more room for recovery in near-crash situations 

(e.g., evasive maneuvers to miss an object on the roadway or inadvertently drifting toward the 

roadside).

Using some of the same logic, it is also assumed that wider shoulders are associated with 

increased safety because they provide increased separation between a parked or disabled vehicle 

and the traveled way. Wider shoulders also provide more room for recovery following an 

unintentional (e.g., inattentive driver drift) or intentional (e.g., evasive maneuver) shoulder 

encroachment. Wider shoulders are also associated with larger lateral clearances from roadside 

objects and longer available sight distances when there are sight obstructions to the inside of 

horizontal curves.

Wider lanes and shoulders also appear to result in faster operating speeds.(47) For example, 

methodologies in the Highway Capacity Manual (HCM) predict an approximately 1.3 to 1.7 mph 

increase in speeds for every 1 ft increase in shoulder width on two-lane highways. Similarly, the 

HCM 2010 predicts an approximately 0.4 to 1.1 mph increase in speeds on two-lane highways 

for every 1 ft increase in lane width. (37)

All else being equal, drivers traveling at faster speeds 

may be less likely to successfully react to unexpected situations (e.g., changes in lead vehicle 

behavior, non-motorized users crossing traveled way, changes in roadway alignment, roadside 

encroachments) than drivers traveling at slower speeds. In addition, the energy dissipated during 

a crash is directly proportional to the square of travel speed at the time of the crash. Impact 

forces that drivers experience increase as this initial speed increases and decreases as the time 

over which energy is dissipated decreases. The crash severity (i.e., probability of fatality or 

severe injury) therefore increases as initial travel speed increases.

The tradeoffs among speed, safety, lane width, and shoulder width are complex. Conclusions 

inferred from existing research are that wider cross sections tend to improve safety performance 

(i.e., fewer expected crashes); however, narrower cross sections tend to produce lower vehicle 

operating speeds. If these two points are independently true, then implementing reduced lane 

233
widths and shoulder widths as a speed management technique—a topic of interest for quite some 

time—should increase the number of crashes. However, some published safety studies indicate 

that there are cases where narrower cross sections are not necessarily associated with a higher 

expected crash frequency. For example, Gross et al. developed CMFs for lane-width–shoulderwidth combinations on rural, two-lane highways.

(48)

The CMF estimation of interactions between 

lane width and shoulder width used a case-control methodology. Results yielded the following 

logical conclusions:

• Shoulder width has a larger effect on safety when lanes are narrow, but the effect of 

shoulder width decreases as lane width increases.

• An increase in lane width does not always increase safety, particularly when shoulder 

widths are wider.

Rural, two-lane highway segments with lane-width–shoulder-width combinations totaling 16 to 

17 ft (e.g., 10-ft lanes with 6-ft shoulders; 11-ft lanes with 6-ft shoulders, 12-ft lanes with 5-ft 

shoulders) may not be any less safe than rural, two-lane highway segments meeting HSM base 

conditions (i.e., 12-ft lanes with 6-ft shoulders). 

Bonneson and Pratt also estimated interactions between lane and shoulder width and drew

similar conclusions—the safety effect of lane width depends on the shoulder width.

(49) Research 

on lane width and safety on urban and suburban arterials, conducted as part of developing the 

HSM, concluded, “No consistent relationship was found between lane width and safety. 

Therefore, lane width was not included in the model.” (78) Other research on lane width in urban 

areas indicated that the “Broad lane indicator (lanes wider than 12 ft) was associated with a 

higher frequency of urban section run-off-road accidents. A plausible explanation is that a 

broader lane could be expected to allow a higher traveling speed and thereby create a greater 

likelihood for run-off-road [crashes] on urban sections”.

(79)

The above-mentioned studies do have some limitations. For example, in the study by Gross et al. 

found the following:(48)

• Transferability of results across States was uncertain.

• Horizontal alignment was not considered.

• Several of the differences in cross-section combinations were not significant because 

of the limited sample sizes. 

Harwood et al. did not report any model parameters for lane width, only the general conclusion 

about inconsistent relationships cited above.

(78) No conclusive statements can be made to date 

other than considering lane width and shoulder width interactions appears to uncover crosssection combinations that will result in lower speeds (according to published speed prediction 

models) without a relative reduction in safety on rural two-lane roads. This is different than the 

current state-of-knowledge in the HSM and has the potential to contribute significantly to 

knowledge on geometric design, speed, and safety relationships and on the use of road geometry 

as a speed management technique.

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Following a review of the literature conducted during an earlier task of this research, there was 

enough evidence for FHWA’s technical advisory team for this project to support exploring 

different combinations of lane and shoulder widths as a strategy to reduce operating speeds and 

improve safety on rural roads. This strategy has the potential to be low cost by reallocating

existing pavement widths. This study focuses only on safety effects of lane-width–shoulderwidth combinations. The study addresses the following limitations to previously published speed 

and safety research.

Most of the speed- and safety-related geometric design research reviewed in earlier tasks of this 

research focused on the effects of design elements in isolation and then combined the isolated 

effects through some additive or multiplicative process. This research looks at lane-width–

shoulder-width combinations as opposed to isolated effects and used a variety of variable 

specifications for lane and shoulder widths, including indicator variables, continuous variables, 

and interaction terms.

Speed and safety prediction models reviewed in earlier tasks of this research were estimated by 

relating crashes and speed at some location to traffic, roadway, and other surrounding features at 

that same location (e.g., a short, homogenous segment). Proponents of self-enforcing, selfexplaining roads have argued that the using cross-sectional geometry as a speed management 

technique will appear effective only when applied and studied over a significant stretch of 

road.(80)

This research looks at the safety effects of lane widths and shoulder widths over 

significant stretches of road as opposed to short, homogenous segments. The research team used 

alignment indices to capture changes in alignment over these road segments.

Databases used to estimate models were verified and enhanced using satellite imagery from 

Google EarthTM. The research team checked and confirmed or (when necessary) recoded with the 

correct measurement to verify accuracy of every attribute (e.g., lane width, shoulder width) in the 

electronically coded databases used for model estimation. In addition, the existing electronically

coded databases were enriched by adding new attributes (e.g., curve radii; driveway density;

barrier presence, length, and offset; roadside hazard rating; pavement markings) to lower the 

chances of omitted variable bias.

The research team explored the effects of lane-width–shoulder-width combinations on crash 

severity by estimating severity distribution functions (SDF) in addition to estimating different 

crash frequency models for various severity levels. The databases used to estimate the severity 

models contain the same crashes and road segments as the frequency model databases, but were 

restructured so that the basic observation unit (i.e., database row) is the crash instead of the road 

segment. The severity models can be used to estimate the probability, or proportion, of each 

severity level given the traffic, geometric, and traffic control characteristics. The newest HSM

edition proposes methodologies for SDFs on freeways and interchanges, which appears to be a 

promising approach; however, to date, the applications in applied safety analysis are relatively 

limited.

DATA COLLECTION

The data collection effort focused on rural two-lane, two-way road segments in Minnesota and 

Illinois. The study did not include safety relationships at intersections or on intersection 

235
approaches. Rural areas were defined as those outside of urban boundaries, but not suburban. 

Suburban areas may be inside or outside urban boundaries. Some subjectivity was involved in 

defining an area as suburban. 

The research initially identified three Highway Safety Information System (HSIS) States as 

possible data alternatives for this study: Illinois, Minnesota, and North Carolina. These three 

States were initially selected because of the availability of a number of precipitating event 

variables that could provide several alternatives for identifying a “speed-related crash” and data 

for roads classified “lower than” arterials (i.e., collectors and local roads). However, a majority 

of rural roads in North Carolina have unpaved shoulders, which would limit the ability to study 

different pavement allocations between lanes and shoulders. Thus, the research team considered 

only data from Minnesota and Illinois for the analysis. Initially, having access to multiple 

alternatives for identifying a “speed-related crash” was an important criterion because the safety 

results were to be linked with observational speed studies conducted along the same segments in 

the selected States. However, FHWA decided to focus on a more general safety study of lanewidth–shoulder-width combinations and spend the remaining resources on more extensive field 

data collection for other treatments studied as part of this research effort (OSBs and high-friction 

surfaces). 

The safety effects of lane-width–shoulder-width combinations were estimated through a crosssectional study design for two reasons: 1) State and local transportation agencies do not routinely 

reallocate existing pavement widths, particularly in rural areas; and 2) the proportion of all 

possible lane-width–shoulder-width combinations that could be evaluated using a before–after 

study during this project, and their respective sample sizes, would be limited. 

To overcome some of the documented limitations of cross-sectional study designs, such as those 

outlined in FHWA’s A Guide to Developing Quality Crash Modification Factors (FHWA-SA10-32), the research team executed an in-depth, manual data collection effort to verify and enrich 

typical electronic databases often used for safety studies.

(81) The research team also used 

modeling alternatives that address possible confounding factors between road segments with 

different lane-width–shoulder-width combinations not captured in the models (e.g., terrain, 

weather, driver characteristics, crash reporting thresholds, and practices). The following sections 

discuss these strategies. 

DATA COLLECTION SOURCES, TOOLS, AND STRATEGIES

Data for this study included geometric features, traffic data, and crash data from rural roads. The 

research team used data collected from the following tools and information sources:

• HSIS: Roadway, traffic, and crash data were collected from FHWA’s HSIS database. 

• Geographic Information System (GIS) roadway databases from the Illinois and 

Minnesota Departments of Transportation: Roadway networks in GIS data formats 

are publicly available for download. The research team used ESRI ArcMapTM GIS 

software package to process the GIS files.

236
• Google EarthTM and Google Street ViewTM: The research team used these two 

publicly available mapping and imaging tools to collect, check, and confirm the 

geometric features as well as enhance the electronic data with additional variables.

Database Verification and Enrichment

Safety models are commonly developed using electronically coded traffic and roadway data for 

independent variables; however, information in these datasets can be limited and inaccurate. 

Limited data means that the database may not include variables that could influence safety. 

Estimating safety models without these variables can result in omitted variable bias (i.e., 

erroneous parameter estimates for variables in the models). Including inaccurate information 

(e.g., incorrect dimensions for lane width) will result in biased parameter estimates. Based on 

this discussion, the research team applied the following techniques:

• Used electronically coded databases to verify the accuracy of every attribute used for 

estimating the safety models.

• Added new attributes to enrich existing databases.

The research team used the aforesaid tools and techniques to conduct verification and 

enhancement activities. 

Geometric Features

The team used a combination of HSIS roadway data files, GIS roadway databases, and Google 

EarthTM/Google Street ViewTM to collect roadway geometric characteristics. The team also 

manually defined each study segment. The segments were homogenous in terms of the number 

of lanes, lane width, shoulder width, shoulder type, and traffic volume. The segments did not 

include unsignalized or signalized intersections, and they began and ended at least 250 ft from 

adjacent intersections. The 250-ft number is consistent with research used to develop HSM 

predictive methods.

(82)

The team explored different alignment indices to capture changes in horizontal alignment. This 

approach allowed longer segments to be defined in the database than those that would result 

from separating curves from tangents. Defining longer road segments was seen as a crucial step 

to determining whether geometry can be used to achieve desirable speed and safety effects. Most 

existing speed and safety prediction models relate crashes and speed at a specific location (e.g., a 

short, homogenous section) to traffic, roadway, and other surrounding features at that same 

specific location. The concept of driver expectancy recognizes that drivers make decisions based 

on previous experiences. Similarly, proponents of self-enforcing, self-explaining roads have 

argued that using geometry as a speed management technique appears effective only when 

applied and studied over a significant stretch of road.(80) Research to date has not captured this 

effect, but instead indicated that geometric design decisions made to reduce speeds (e.g., 

increased curvature, narrower lane widths) are expected to increase the expected number crashes. 

The team defined road segments, collected their features and then checked and confirmed using 

Google EarthTM’s satellite images and Google Street ViewTM photographs. The team used the 

237
Ruler tools in Google EarthTM to measure distances and to check and confirm lane width, 

shoulder width, segment length, and barrier presence and length. These tools were also used to 

measure deflection angles and horizontal curve lengths. The research team developed a set of 

Google EarthTM calculation tools to automate this process. NCHRP 17-45, Enhanced Safety 

Prediction Methodology and Analysis Tool for Freeways and Interchanges, used similar 

techniques.(83) The team also developed new tools compatible with the rural, two-lane context of 

interest for this current FHWA effort.

Segment Location

The first step of the data-collection process was locating the roadway segment of interest in 

Google EarthTM and determining its mileposts. Google EarthTM and other publicly available 

mapping and satellite imaging tools do not provide milepost information. However, the milepost 

of any point along a given State route in Minnesota and Illinois can be determined by using a 

combination of HSIS roadway data, GIS data for roadway networks, and Google EarthTM. The 

following discussion provides a step-by-step description of the process. Any point along a route 

was identified by all three of the following identifiers:

• County number and name (County).

• State route number (rte_nbr or s_rtenbr).

• Milepost.

HSIS roadway data files include all of these variables for both Illinois and Minnesota. The goal 

of this process was to then transfer these pieces of information from the HSIS roadway data files 

into Google EarthTM so the team could verify and enhance the data. HSIS data identified

roadway segments by county, route number, and milepost. Google EarthTM uses coordinates. The 

team therefore used GIS data and ArcGISTM software to translate location information from

HSIS roadway inventory files into Google EarthTM. 

GIS roadway files from Illinois and Minnesota have different structures and information; 

therefore, the team could not use a single method of transferring HSIS data points into Google 

EarthTM through GIS for both States. Although there are many similarities, the procedure is

described separately for Minnesota and Illinois. The procedure is illustrated by two examples, 

one for each State.

Minnesota Step 1: Collect route number, county number, and milepost from the HSIS 

roadway data file 

Figure 120 shows an example of the segment location information in the HSIS roadway data file

for Minnesota. In this example, the beginning point of the segment shown in the seventh row is 

the point of interest. It is used throughout the process of locating this segment in Google EarthTM.

The point is located on Route 1, in County 4, at milepost 110.453.

238
Source: University of Utah

Figure 120. Chart. Location information in Minnesota’s HSIS Roadway File.

Minnesota Step 2: Locate the same point in Minnesota’s GIS roadway file and calculate its 

coordinates 

Minnesota’s GIS roadway data file also includes route number, county number, and milepost 

information. The point of interest (Route 1, County 4, Milepost 110.453) can be located and 

highlighted by opening the attribute table in ArcMapTM software. Figure 121 is a screenshot that

illustrates this process. The eighth row (yellow-highlighted) has the beginning milepost of 

110.453, the point of interest in this example. Two new columns named Beg_X and Beg_Y are 

created to store the x and y coordinates of the point (milepost 110.453). The team used the 

Calculate Geometry tool in ArcMapTM to transform the coordinate information of the point from 

its original NAD 1983 UTM (Zone 15N) to longitude and latitude in the WGS84 Coordinate 

System.

Source: University of Utah

Figure 121. Chart. Location information of the roadway segment in GIS File (Minnesota).

239
Minnesota Step 3: Locate and mark the point in Google EarthTM

The team transferred the coordinates calculated from Step 2 into Google EarthTM. A marker was 

placed at the location for future reference. Figure 122 is a screenshot of the point (MN Route 1, 

County 4, Milepost 110.453) located and marked with a place marker in Google EarthTM.

Original image: ©2014 Google®; annotations by University of Utah.

Figure 122. Photo. Locate and mark the point of interest in Google EarthTM using its 

coordinates (Minnesota).(84)

The above step-by-step process is systematically performed for all beginning points of the road 

segments on each route of interest in Minnesota. The coordinates of all points are then exported 

and automatically transferred into Google EarthTM using Keyhole Markup Language (KML) 

codes. The result of this process is a longitudinal reference system along each route in Google 

EarthTM with mileposts marked.

Illinois Step 1: Collect route number, county number, and milepost from the HSIS roadway 

data file

This step is very similar to Step 1 for Minnesota because the HSIS roadway data files from the 

two States have similar structures and identical information for county number, State route 

number, and milepost. However, GIS data files from Illinois do not have milepost information. 

Therefore, an additional piece of information is necessary for this step: the milepost of the route 

at the county line. The county line is then used as a reference point to calculate mileposts and 

locate all other points. Figure 123 shows an example of location information found in the Illinois

HSIS roadway data file. Two rows in this figure are highlighted. The sixth row (green

highlighted) is the first roadway segment on Route 24 in Brown County. The beginning milepost 

of this segment is the milepost of Route 24 at the county line (begmp = 31.54). Milepost 31.54 

then becomes the reference point for all other points on Route 24 in Brown County. The 

beginning milepost of the tenth row (yellow highlighted) is the point of interest in this example. 

It is located in County 5 (Brown County), on Route 24, at milepost 33.06.

240
Source: University of Utah

Figure 123. Chart. Location information in Illinois HSIS Roadway data file.

Illinois Step 2: Locate the same point in Illinois GIS roadway file

Again, unlike Minnesota data, GIS files for the Illinois roadway network do not include milepost 

information. Illinois GIS files have two variables named BEG_STA and END_STA representing 

the stations (in units of mi) of beginning and ending points of each GIS roadway segment. (It 

should be noted that Illinois GIS deviates from standard surveying station measurements, which 

are usually in increments of 100 ft). Although actual milepost information is not available, the 

station can be used to compute the milepost of any point along the route. In most cases, 

BEG_STA=0.00 at the county line, and it increases west to east or south to north throughout the 

county. In some cases, the station resets back to 0.00 at some major intersecting points with other 

major routes.

The milepost of any given point on an Illinois route is computed using the equation shown in 

figure 124.

Figure 124. Equation. Reference point milepost.

Where:

Milepostref = the milepost of the reference point

STA = the station information (BEG_STA or END_STA) of the point in the GIS data file

In most cases, the milepost of the reference point is the milepost at the county line (determined in 

step 1). In some cases, it is the milepost of a major intersection where the beginning station 

(BEG_STA) resets back to 0.00. This reference point can be identified by looking through the 

241
attribute table of the GIS file and locating it using the same procedure as that used to compute

mileposts.

While the direction of increasing milepost is the same as the direction of increasing station in the 

GIS files in most cases, they can be opposite in some rare instances. Because the distances are 

still the same, mileposts can be computed by reversing the direction of increasing station using 

the equation shown in figure 125.

Figure 125. Equation. Reference point milepost by reversing the direction of increasing 

station.

Where:

Milepostref = the milepost of the reference point

STAmax = the largest value of END_STA in the GIS file of a given county

STA = the station information (BEG_STA or END_STA) of the point in the GIS data file

Figure 126 shows an example of identifying the point of interest in this example. The first row of 

the data table indicates the county line with BEG_STA=0.00. The fifth row (yellow highlighted)

shows the point of interest with a beginning station of 1.52 at milepost 33.06.

242
Source: University of Utah

Figure 126. Chart. Location information of the roadway segment in GIS file (Illinois).

Illinois Step 3: Determine the coordinates and locate the point in Google EarthTM

This step is similar to Minnesota step 2 and step 3. The research team used the Calculate 

Geometry tool in ArcGISTM to coordinate each point in the WGS 1984 Coordinate System. 

Figure 127 shows the example of obtaining the coordinate information of milepost 33.06 

(STA=1.52) along Illinois Route 24. The team then transferred the coordinates into Google 

EarthTM, and the points were marked in the same way. Figure 128 is a Google EarthTM screenshot 

with the marker of milepost 33.06.

243
Source: University of Utah

Figure 127. Chart. Identify coordinate information associated with the roadway segment 

(Illinois).

Original image: ©2014 Google®; annotations by University of Utah.

Figure 128. Photo. Locate and mark the roadway segment in Google EarthTM with its 

coordinates.(85)

244
Segment Definition

Following the steps outlined above, the research team created a series of mile markers in Google 

EarthTM—creating a longitudinal reference system along each route. The team then explored 

each route over the 3 years of the analysis period (2007, 2008, 2009) to determine the candidate 

study segments. In the process, the team also checked whether there were any significant 

changes to the route (indicating a possible reconstruction project that changed milepost 

definitions). The team used historical satellite imagery (in Google EarthTM) and crash data codes 

to eliminate sections of roadway with work zones during the analysis period. The team selected 

and marked candidate study segments based on the following three criteria:

• The segment does not include a signalized or an unsignalized intersection.

• The segment can include driveways.

• The number of lanes, lane width, shoulder width, shoulder type, and traffic volume 

are the same throughout the segment.

Through this process, the team retained only longer segments (about 0.5 mi and longer). As 

explained above, the purpose of using the longer segments is to address a limitation of previous 

studies and capture results regarding the proposed idea that using geometry as a speed 

management technique will appear effective from a safety perspective only when applied and 

studied over a significant stretch of road.

Cross-Section Features

Using the HSIS roadway files, the research team had a basic idea of the lane configuration (i.e., 

number of through lanes and auxiliary lane present), lane width, shoulder width, and shoulder 

types. The team then used a combination of Google EarthTM satellite images and a set of Google 

EarthTM calculation tools created by the research team using Visual Basic for Applications 

(VBA) in MicrosoftTM Excel to check these features at incremental distances along the defined 

segments. Figure 129, figure 130, and figure 131 are screenshots of Google EarthTM and Google 

Street ViewTM illustrating the procedure. The team tested the accuracy of the Google EarthTM

measurements of widths using Google EarthTM’s distance measurement tools to take 

measurements of known distances (e.g., football field markings), which were found to be 

accurate. The determination of lane width was partly automated by developing VBA codes to 

continuously calculate the height of a moving triangle along each segment. Two points on one 

edge line and another on the opposite edge of the road form the triangle. Figure 131 illustrates 

this concept. 

245
Original image: ©2014 Google®; annotations by University of Utah.

Figure 129. Photo. Measurement of cross-section features in Google EarthTM.

(86)

Original image: ©2014 Google®; annotations by University of Utah.

Figure 130. Photo. Conceptual illustration of calculating lane.

(87)

246
Original image: ©2014 Google®; annotations by University of Utah.

Figure 131. Photo. Visual checks of cross-section features in Google Street ViewTM.

(88)

Other roadside elements may also influence safety and should be controlled for when trying to 

determine the safety effects of lane-width–shoulder-width combinations. These include barrier 

presence, barrier length and offset (from the travel lane), type of center line and edge line 

markings, number of driveways, and the roadside hazard rating. The team adopted the roadside 

hazard rating developed by Zegeer et al. and currently used in the HSM predictive method for 

rural, two-lane roads for this study.(89) The team collected these data elements and then coded for 

the defined segments.

Table 97 provides a summary of the dataset by cross-section configuration with the number of 

roadway segments by each lane-width and shoulder-width category.

247
Table 97. Number of segments by lane-width and shoulder-width.

Lane Width (ft) Shoulder Width (ft)

State

Illinois Minnesota Total

10

All 55 6 61

0–3 38 0 38

4–6 15 2 17

> 6 2 4 6

11

All 267 81 348

0–3 109 9 118

4–6 142 16 158

> 6 16 56 72

12

All 219 249 468

0–3 57 28 85

4–6 126 53 179

> 6 36 168 204

13

All 0 9 9

0–3 0 6 6

4–6 0 1 1

> 6 0 2 2

Total 541 345 886

Table 98 provides a summary of the dataset by the presence of roadside barriers; table 99 shows 

the presence of driveways.

Table 98. Number of segments with roadside barriers.

Roadside Barriers

State

Illinois Minnesota Total

No 416 300 716

Yes 125 45 170

Total 541 345 886

Table 99. Number of segments by driveway presence.

Number of Driveways

State

Illinois Minnesota Total

0 134 95 229

1–10 368 242 610

11–20 30 8 38

> 20 9 0 9

Total 541 345 886

248
Horizontal Alignment

A limitation of previous studies of lane-width–shoulder-width combinations was the lack of 

control for horizontal curvature, particularly if the data were from States other than Washington. 

Horizontal curve data are not available in most roadway inventory databases, but these data are

crucial to modeling safety performance along rural and suburban roads. The research team used a 

combination of Google EarthTM path-marking tools and custom-made Google EarthTM

calculation tools developed using VBA in MicrosoftTM Excel to collect data for each horizontal 

curve on the defined road segments. The method was developed and tested using horizontal 

curves of known geometry and found to be accurate (i.e., measured and actual radius within 

approximately 2.5 percent). The following steps illustrate this technique, which measures the 

deflection angle and long chord.

Step 1: Place a path on the centerline. Use the Add path tool in Google EarthTM to trace along 

the centerline of roadway. This path needs to cover the entire curve and extend to partly cover 

both tangent lines. This path is visually placed and adjusted so that it matches the centerline of 

the roadway as closely as possible (see figure 132).

Step 2: Export the overlaid Google EarthTM path and extract the coordinate information. 

The path is then exported from Google EarthTM into a KML file. The KML file holds coordinate 

information of points along this path. These coordinates are then extracted using VBA codes 

specifically developed for this task. A computer algorithm also developed specifically for this 

task detects and categorizes these points into those on the curve and those on the two tangents 

based on their coordinates and positions relative to each other.

Step 3: Develop straight-line equations for the tangents and compute the deflection angle.

The VBA program then uses the coordinates of the points on the tangents to compute two 

straight-line equations through linear regression. The coordinates of point of intersection (PI) and 

the deflection angle (Δ) are then computed from these two straight-line equations.

249
Original image: ©2014 Google®; annotations by University of Utah.

Figure 132. Photo. Screenshot of estimating deflection angles in Google EarthTM.

(90)

Step 4: Calculate external distance E, radius R, and length of curve L. With the coordinates 

of the PI known, a minimization algorithm determines the smallest distance between the PI and 

the curve. The computer code searches for the smallest distance between the PI and all points 

along the curve using the equation shown in figure 133.

Figure 133. Equation. Smallest distance between PI and all points along the curve.

The curve radius is then calculated using the equation shown in figure 134.

250
Figure 134. Equation. Curve radius.

The length of the curve is then calculated using the equation shown in figure 135.

Figure 135. Equation. Length of the curve.

This four-step process is applied to every horizontal curve along the defined study segments. The 

team explored alignment indices to capture changes in horizontal alignment to define longer 

segments with multiple curves in the database. The advantages of this approach are discussed 

earlier in this section. Table 100 provides alternative indices explored as ways to quantify the 

horizontal alignment characteristic of each extended road segment. These are based on a 

previous study that attempted to use alignment indices to predict operating speeds.

(91)

It is 

important to note that the objective of this study is not to estimate the effects of the alignment 

indices on speed and safety, but to control for horizontal alignment characteristics on extended 

lengths of road while studying the effects of lane-width–shoulder-width combinations.

251
Table 100. Alignment indices for quantifying horizontal alignment characteristics (based 

on Fitzpatrick et al., 2000).

(91)

Horizontal Alignment Index Formula

Curvature Change Rate (CCR) (degrees/mi) Where:

I = deflection angle (degrees)

L = length of section (mi)

Degree of Curvature (DC) (degrees/mi) Where:

DC = degree of curvature (degrees)

L = length of section (mi)

Curve Length: Roadway Length (CL:RL) Where:

CL = curve length (mi)

L = length of section (mi)

Average Radius—AVG R (ft) Where:

R = radius of curve (ft)

n = number of curves within section

Average Tangent—AVG T (ft) Where:

TL = tangent length (ft)

n = number of tangents within section

Other Features

The research team also used maps with area type boundaries combined with the Google EarthTM

images and Google Street ViewTM photography to collect other variables that describe the road 

segment. These include area type (rural, rural transition zone, rural community, suburban), 

presence and type of edge line and centerline markings, and presence of shoulder and/or 

centerline rumble strips.

Table 101 shows a summary of the dataset by the presence of no-passing zone (solid centerline), 

one-directional passing zone (one-sided solid centerline), and the presence of shoulder rumble 

strips. Rumble strip information was initially included in the model. However, most of the 

segments with shoulder rumble strips are in Minnesota so the rumble strip variable is correlated 

with the State indicator. Therefore, the research team dropped rumble strips from the model, and 

the State indicator likely captured its effects.

∑

∑

i

i

L

I

∑

∑

i

i

L

(DC)

∑

∑

i

i

L

(CL)

n

∑ R i ( )

n

∑ TL i ( )

252
Table 101. Number of segments with no-passing zone, one-sided passing zone, and shoulder 

rumble strip.

Segment Characteristics

State

Illinois Minnesota Total

No Passing

(Solid centerline)

No 382 272 654

Yes 159 73 232

Total 541 345 886

One-Sided Passing

(One-sided solid 

centerline)

No 246 164 410

Yes 295 181 476

Total 541 345 886

Shoulder Rumble Strip

No 536 180 716

Yes 5 165 170

Total 541 345 886

TRAFFIC DATA

The team collected traffic volumes from the HSIS database. Traffic volume was one of the 

variables used to define a homogenous roadway segment. The team defined traffic volume for

each roadway segment for each of the three analysis years (2007, 2008, 2009).

Table 102 provides descriptive statistics for the geometric, traffic control, and traffic variables 

that describe the 886 rural, two-lane highway segments observed for this study. Ultimately, the 

approximately 1 percent of segments (a total of 9 segments) with lane widths equal to 13 ft were 

deleted from the database used for model estimation, resulting in 877 total segments. 

253
Table 102. Descriptive statistics for geometric, traffic control, and traffic variables.

Variablea

Number of 

Observation Mean

Standard 

Deviation Minimum Maximum

aadt 886 3,436.54 2,353.04 450 19,190

ln_aadt 886 7.93 0.67 6.11 9.86

seglen 886 0.82 0.41 0.11 2.92

illinois 886 0.61 0.49 0 1

Lane10 886 0.07 0.25 0 1

Lane11 886 0.39 0.49 0 1

Lane12 886 0.53 0.50 0 1

Lane13 886 0.01 0.10 0 1

shoulder 886 5.29 2.78 0 12.00

ln10shld 886 0.22 1.02 0 9.00

ln11shld 886 1.84 2.79 0 12.00

barrier 886 0.01 0.02 0 0.36

drvwy_den 886 3.93 5.40 0 63.41

solid_CL 886 0.07 0.17 0 1.13

dash1_CL 886 0.10 0.12 0 0.50

curve 886 0.30 0.46 0 1 a

The following are the variable definitions:

aadt = Average annual daily traffic (vehicles/day)

ln_aadt = Natural logarithm of aadt 

seglen = Segment length (mi)

illinois = Indicator for State in which the road segment is located (=1 if the data is from Illinois; =0 if the data is 

from Minnesota)

Lane10 = Indicator for 10-ft lane width (=1 if the segment has a 10-ft lane width; =0 otherwise)

Lane11 = Indicator for 11-ft lane width (=1 if the segment has a 11-ft lane width; =0 otherwise)

Lane12 = Indicator for 12-ft lane width (=1 if the segment has a 12-ft lane width; =0 otherwise)

Lane13 = Indicator for 13-ft lane width (=1 if the segment has a 1-ft lane width; =0 otherwise)

shoulder = Total shoulder width, both paved and unpaved shoulders (ft)

ln10shld = Interaction between 10-ft lane and shoulder width (=Lane10*Shoulder)

ln11shld = Interaction between 11-ft lane and shoulder width (=Lane11*Shoulder); 

barrier = Length and offset of roadside barrier (=barrier_length/(barrier_offset*total_segment_length)

drwy_den = Driveway density (=number_of_driveways/total_segment_length)

solid_CL = Variable representing the proportion of no-passing zone (=

total_length_of_solid_center_line/total_segment_length)

dash1_CL = Variable representing the proportion of one-sided passing zone (=total_length_of_onesided_solid_center_line/total_segment_length)

curve = Indicator variable representing the horizontal alignment (=1 if the total sum of (radius/deflection angle) 

falls between 10 and 1,000; =0 otherwise).

CRASH DATA

The team collected crash data from the HSIS crash databases. After defining all study segments 

and determining their beginning and ending mileposts, the team counted the number of crashes 

that occurred within each segment. The team used 3 years of crash data (2007, 2008, 2009) for 

the safety analysis in this study. The team also counted the following crash types on each road 

segment:

254
• Total crashes (all types and severities).

• Fatal-plus-injury crashes (all types).

• Single-vehicle crashes (all severities).

• Multiple-vehicle crashes (all severities).

• Key lane width/shoulder with crashes (all severities) that include single-vehicle-runoff-road and multiple-vehicle head-on, sideswipe opposite direction, and sideswipe 

same direction.

• Single-vehicle crashes (fatal-plus-injury).

• Multiple-vehicle crashes (fatal-plus-injury).

• Key lane width/shoulder with crashes (fatal-plus-injury).

• Single-vehicle crashes (property damage only (PDO)).

• Multiple-vehicle crashes (PDO).

• Key lane width/shoulder with crashes (PDO).

Table 103 provides descriptive statistics for the crash variables.

Within the total and fatal-plus injury crash levels, the team explored crash severity in greater 

detail because of the expected interaction among lane width, shoulder width, and speed discussed 

in the background section. The team estimated SDFs for the total and fatal-plus-injury crashes

using multinomial logit models (discussed at greater depth in the following section). The 

databases used to estimate the severity models consisted of the same crashes, road segments, and 

variables as the frequency model databases, but were restructured so the basic observation unit 

(i.e., database row) is the crash instead of the road segment. 

255
Table 103. Descriptive statistics for crash variables.

Variable

Number of 

Observation Mean

Standard 

Deviation Minimum Maximum

tot_all 886 2.71 3.55 0 32

sv_all 886 2.27 3.21 0 31

mv_all 886 0.44 0.94 0 10

key_kabco 886 2.94 4.01 0 35

sv_fi 886 0.31 0.66 0 6

mv_fi 886 0.17 0.47 0 4

key_kabc 886 0.57 1.14 0 10

sv_o 886 1.95 2.96 0 28

mv_o 886 0.27 0.71 0 7

key_o 886 2.38 3.49 0 30

The following are the variable definitions:

tot_all = Total crashes (all types and severities)

sv_all = Single-vehicle crashes (all severities)

mv_all = Multiple-vehicle crashes (all severities) 

key_kabco = Key lane width/shoulder with crashes (all severities) that include single-vehicle-run-off-road 

and multiple vehicle head-on, sideswipe opposite direction, and sideswipe same direction

sv_fi = Single-vehicle crashes (fatal-plus-injury)

mv_fi = Multiple-vehicle crashes (fatal-plus-injury)

key_kabc = Key lane width/shoulder with crashes (fatal-plus-injury)

sv_o = Single-vehicle crashes (property damage only (PDO))

mv_o = Multiple-vehicle crashes (PDO)

key_o = Key lane width/shoulder with crashes (PDO)

SAFETY DATA ANALYSIS METHODOLOGIES

Analysis of Expected Crash Frequency

The team used negative binomial regression modeling to explore the effects of lane-width–

shoulder-width combinations on expected crash frequency. The team estimated the full

regression models that consider all the variables collected, in addition to lane width and shoulder 

width, to reduce the possibility of omitted variable bias. In the negative binomial model, the 

expected number of crashes of type i on segment j is typically expressed using the equation 

shown in figure 136.

Figure 136. Equation. Expected number of crashes of type i on segment j.

Where: 

μij = E(Yij) = the expected number of crashes of type i on segment j

Xj = a set of traffic and geometric variables characterizing segment j

= regression coefficients estimated with maximum likelihood that quantify the relationship 

between E(Yij) and variables in X

β

256
Lj = length of segment j

Ln(Lj) = the natural logarithm of segment length

The mean-variance relationship of the negative binomial regression model is expressed using the 

equation shown in figure 137.

Figure 137. Equation. Variance of crashes of type i on segment j.

Where: 

VAR(Yij) = variance of crashes of type i on segment j

E(Yij) = the expected number of crashes of type i on segment j

α = overdispersion parameter

The research team explored both constant overdispersion parameters as well as overdispersion 

parameters that apply to a unit length of road when estimating the lane-width and shoulder-width 

models. Ultimately, they selected models with a constant overdispersion parameter.

The research team explored variations of the negative binomial model to address crashinfluencing factors that may be common to groups of road segments, but that are not captured by 

the models. Failure to address these factors during model estimation may result in biased 

parameter estimates and underestimated standard errors. Hauer classified these factors as 

“unrecognized, or not understood, or unmeasured.”(92)

Examples include terrain type, weather, 

and crash-reporting thresholds of the agency overseeing a particular area. The latter can be 

particularly important in estimating safety performance functions for less severe (e.g., PDO) 

crashes. 

Negative binomial models with identification variables for counties, districts, regions, or States 

treated as fixed or random effects are modeling alternatives to address these “shared 

unobservables.” The fixed effects estimator has less restrictive assumptions, but it is not always 

useful if the independent variables of interest do not vary within the fixed effects (e.g., if a 

particular county had the same lane width throughout, then the fixed effects for that county and 

lane width could not both be included in the model). The random effects estimator addresses this 

challenge, but is only appropriate if the random effects are not correlated with the independent 

variables in the model. This assumption can be investigated with a Hausman test.

(93)

The models 

reported in this report ultimately implemented a fixed effects approach with indicator variables 

representing State (i.e., 1 = Illinois, 0 = Minnesota). 

The research team tested the effects of lane-width–shoulder-width combinations through a 

number of variable specifications. It has been common to include lane width and shoulder width 

in a linear specification. However, the team also explored the inverse of lane width and shoulder 

width in an attempt to capture an increased effect of lane width and shoulder width on safety 

when widths are narrow. As the widths become wider and wider, the safety effects diminish. The 

team also tested indicator variables for lane-width–shoulder-width combinations. Indicator 

variables capture possible nonlinear or noncontinuous relationships. In the end, the research team 

257
settled on specifications of indicator variables for lane widths, shoulder width as a continuous 

variable in a linear specification, and interactions between the lane-width indicator variables and 

shoulder width to capture the varying effects of lane-width–shoulder-width combinations. 

Analysis of Crash Severity

Accurate predictions of crash severity are important when looking at combinations of lane 

widths and shoulder widths. Severity distributions may change significantly with cross-section 

allocation through a resulting increase or decrease in operating speeds. Severity distributions are 

likely to vary differently with traffic volumes and design decisions depending on crash type (e.g., 

single vehicle or multiple vehicle). The research team used logit models to estimate an SDF to 

address these issues. The logit models produce the probabilities (or proportions) of crash severity 

outcomes as a function of traffic volume, geometry, and other road characteristics. The 

multinomial logit, nested logit, and ordered outcome models are possible model 

alternatives.

(94,95,96) The databases used to estimate the severity models consist of the same 

crashes road segments and variables as the frequency model databases, but restructured so that 

the basic observation unit (i.e., database row) is the crash instead of the road segment. The 

frequency models and SDFs can be combined to estimate the number of accidents of different 

severity levels.

(97)

For this research, the research team used the multinomial logit model to estimate SDFs within 

the total and fatal-plus-injury crash levels. In the multinomial logit model, the probability that 

accident n will have severity i is expressed using the equation shown in figure 138.

Figure 138. Equation. Probability of accident n with severity i.

Where Xn is a set of variables that will determine the crash severity, and is a vector of 

parameters to be estimated. The same factors specified in the frequency models were also 

specified in the severity models, including variables for different lane-width–shoulder-width 

combinations at the crash location.

MODEL ESTIMATION RESULTS AND DISCUSSION

All models were estimated using STATA® 12.1, created by StataCorp, located in College 

Station, TX. Table 104 and table 105 provide negative binomial regression model estimation 

results for total crashes (all types and severities) fatal-plus-injury crashes (all types), 

respectively. Appendix C provides model estimation results for other crash types (as outlined in 

the Crash Data section).

β i

258
Table 104. Negative binomial regression model estimation results for total crashes (all types 

and severities).

Variable Coefficient

Standard 

Error z P > z

95-Percent 

Confidence Interval

ln_aadt 0.652 0.053 12.25 < 0.001 0.547 0.756

illinois 0.994 0.092 10.78 < 0.001 0.813 1.175

Lane10 0.985 0.201 4.89 < 0.001 0.590 1.380

Lane11 0.489 0.146 3.34 0.001 0.202 0.775

shoulder -0.042 0.021 -1.97 0.048 -0.083 0.000

ln10shld -0.119 0.053 -2.25 0.024 -0.222 -0.016

ln11shld -0.052 0.028 -1.88 0.060 -0.106 0.002

barrier 3.925 1.593 2.46 0.014 0.803 7.047

drvwy_den 0.014 0.006 2.32 0.020 0.002 0.025

solid_CL 0.517 0.188 2.75 0.006 0.149 0.886

dash1_CL 0.862 0.293 2.94 0.003 0.288 1.437

curve 0.224 0.067 3.35 0.001 0.093 0.355

_cons -5.041 0.424 -11.89 < 0.001 -5.872 -4.210

ln(Length) 1 (exposure) N/A N/A N/A

/lnalpha -1.129 0.117 N/A N/A -1.358 -0.900

alpha 0.323 0.038 N/A N/A 0.257 0.406

Log Likelihood = -1608.0603

Number of Observations = 877

LR chi2(12) = 443.79

Prob > chi2 = 0

Pseudo R2 = 0.1213

Likelihood-ratio test of alpha=0: chibar2(01) = 239.90 Prob>=chibar2 = 0.000

N/A = Not Available

259
Table 105. Negative binomial regression model estimation results for fatal-plus-injury 

crashes (All types).

Variable Coefficient

Standard 

Error z P > z

95-Percent 

Confidence Interval

ln_aadt 0.736 0.092 7.980 < 0.001 0.555 0.917

illinois 0.426 0.151 2.830 0.005 0.131 0.721

Lane10 0.315 0.384 0.820 0.412 -0.437 1.066

Lane11 0.424 0.259 1.640 0.101 -0.083 0.932

shoulder -0.016 0.035 -0.450 0.650 -0.085 0.053

ln10shld -0.047 0.093 -0.500 0.615 -0.228 0.135

ln11shld -0.063 0.047 -1.330 0.183 -0.156 0.030

barrier 2.370 2.552 0.930 0.353 -2.631 7.372

drvwy_den 0.002 0.010 0.170 0.866 -0.019 0.022

solid_CL 0.453 0.311 1.460 0.145 -0.156 1.062

dash1_CL 0.404 0.499 0.810 0.419 -0.575 1.383

curve 0.113 0.113 1.000 0.316 -0.108 0.335

_cons -6.856 0.738 -9.290 < 0.001 -8.303 -5.409

ln(Length) 1 (exposure) N/A N/A N/A N/A

/lnalpha -1.49881 0.464812 N/A N/A -2.40983 -0.5878

alpha 0.223396 0.103837 N/A N/A 0.089831 0.55555

Log Likelihood = -744.43799

Number of Observations = 877

LR chi2(12) = 94.08

Prob > chi2 = 0.000

Pseudo R2 = 0.059

Likelihood-ratio test of alpha=0: chibar2(01) = 6.69 Prob>=chibar2 = 0.005

N/A = Not Available

For the total crash model, all model parameters except one were statistically significant at a 

95-percent confidence level (i.e., with a probability of a Type I error less than 5 percent). The 

p-value for the interaction of the 11-ft lane width indicator and shoulder width indicated a 

6-percent chance of a Type I error. Parameter signs were all generally in the direction expected. 

Parameters for lane width indicators showed that, with shoulder width ignored, the expected 

number of total (i.e., all types and severities) crashes increases as lane width decreases. The main 

effect of shoulder width was a decrease in the expected number of crashes as shoulder width 

increased. In addition, the interaction of the lane width indicator and shoulder width showed that 

shoulder width has the greatest effect on safety when the lane width equals 10-ft. Shoulder width 

also has a greater effect on safety when the lane width is 11-ft than when the lane width is 12-ft. 

Figure 139 shows these findings are demonstrated in the form of CMFs. 

260
Figure 139. Graph. CMFs for lane-width–shoulder-width combinations developed directly 

from regression model parameters, total crashes (all types and severities) 

on rural, two-lane roads (developed from model estimation results in table 104).

For the fatal-plus-injury crashes, only the 11-ft lane width indicator, the 11-ft lane width, and 

shoulder width interaction were statistically significant at a level higher than 80 percent among 

the cross-section variables. Parameter signs were all generally in the direction expected, with the 

same signs as the total crash model parameters. Parameters for lane width indicators showed that, 

with shoulder width ignored, the expected number of fatal-plus-injury crashes (all types) 

increases as lane width decreases, but it is difficult to distinguish the performance of an 11-ft 

lane width from a 12-ft lane width. The main effect of shoulder width was a decrease in the 

expected number of fatal-plus-injury crashes as shoulder width increased, but the probability of a 

Type I error was quite high (near 65 percent). The interaction of the lane width indicator and 

shoulder width showed that shoulder width has additional, positive effects on safety when the 

lane width is less than 12 ft. Figure 140 shows that these findings are demonstrated in the form 

of CMFs.

0

1

2

3

4

0 2 4 6 8 10

Crash Modification Factor

Shoulder Width (ft)

10 ft lane widths

11 ft lane widths

12 ft lane widths

Base Condition: 12 ft lane, 6 ft 

261
Figure 140. Graph. CMFs for lane-width–shoulder-width combinations developed directly 

from regression model parameters, fatal-plus-injury crashes (all types) on rural, two-lane 

roads (developed from model estimation results in table 105).

The results discussed above show more complex (but intuitive) interactions between expected 

crash frequency, lane width, and shoulder width than what is currently reflected in the Highway 

Safety Manual CMFs. For any given pavement width, there are combinations of lane width and 

shoulder width that result in the lowest expected crash frequency (for all crash types and 

severities as well as for fatal-plus-injury crashes). For narrower total paved widths, the optimal 

lane width appears to be 12 ft. This general conclusion is consistent with conclusions from Gross 

et al.(48) As total paved widths become larger, there is not necessarily a safety benefit from using 

a wider lane, and in some cases, using a narrower lane appears to result in lower than expected 

crash frequencies.

One possible explanation continues to be likely differences in operating speeds for different lanewidth–shoulder width combinations. Initially, these safety results were to be linked with 

observational speed studies conducted along selected Illinois and Minnesota segments to confirm 

this hypothesis. However, FHWA officials decided to focus on a more general safety study of 

lane-width–shoulder-width combinations and spend the remaining resources on more extensive 

field data collection for other treatments studied as part of this research effort (OSBs and highfriction surfaces). 

Appendix C provides the multinomial logit model estimation results for total crashes (all types 

and severities) with property damage only set as the base outcome, and fatal-plus-injury crashes 

(all types) with possible injury crashes set as the base outcome. This was done in an effort to 

estimate SDFs in addition to estimating different crash frequency models for various severity

0

1

2

3

4

0 2 4 6 8 10

Crash Modification Factor

Shoulder Width (ft)

10 ft lane widths

11 ft lane widths

12 ft lane widths

Base condition: 12 lane, 6 ft shoulder

262
levels. The databases used to estimate the severity models consisted of the same crashes and road 

segments as the frequency model databases, but restructured so the basic observation unit (i.e., 

database row) is the crash instead of the road segment. The newest Highway Safety Manual

proposes SDFs in methodologies on freeways and interchanges. 

The SDFs do not show statistically significant and consistent results in terms of the geometric 

effects on crash severity defined in this way. This is not necessarily surprising, given that the 

interpretation of these models is “the probability of a severity outcome, given that a crash has 

occurred.” The geometric features are not expected to directly influence the severity outcome 

given that the crash has occurred; geometric features are likely to influence the likelihood of the 

crash occurring. Vehicle- and occupant-related characteristics, as well as the characteristics of a 

given collision, are much more likely to influence this conditional severity outcome. The finding 

indicates the need for additional exploration of SDFs and their sensitivity to road design and 

traffic control features.

263

7. SUMMARY, CONCLUSIONS, AND CONSIDERATIONS

This section summarizes project findings, conclusions, and general considerations for future 

research. 

HIGH FRICTION SURFACE TREATMENT EVALUATION FINDINGS

The research team used observational before–after studies to evaluate HFST at four treatment 

sites and three control sites in West Virginia. The HFST was applied in June 2012 with the first 

after period data collection in August 2012 and the second after period data collection in June 

2013. The research team performed operational, driver behavior, and friction evaluations. The 

following is a summary of the evaluation findings:

• Operating Speed Evaluation Results

o Mean Operating Speed—The research team compared the mean operating speed 

for passenger cars and trucks before and at two different time periods after

installing the HFST. The mean speeds were compared at a location on the 

approach tangent, curve PC location, and the midpoint of the horizontal curve. 

The analysis included only daytime and unopposed free-flow vehicle mean 

speeds. The results of the mean speed analysis indicate that the HFST did not 

significantly affect vehicle mean operating speeds in a consistent manner across 

all four treatment sites. Few of the independent samples t-tests showed that the 

mean passenger car and heavy truck operating speeds differed between the before

and first or second after periods at the treatment sites. A multifactor ANOVA 

found that the data collection time period–treatment site interaction was not 

statistically significant (F2, 4160 = 0.49, p > 0.05) at the approach speed location, 

when including observations of free-flow vehicles only and controlling for the 

presence of vehicles in the opposing lane, time of day, and vehicle type. Similar 

results were found at the PC (F2,4160 = 1.51, p > 0.05) and midcurve locations 

(F2,4160 = 0.56, p > 0.05).

o Change in Mean Operating Speed—The change in speed from the entry of the 

curve (PC) to the midpoint of the horizontal curve (referred to as delta speed

hereafter) was also considered in the analysis. There is no consistent trend in the 

delta speed for passenger cars from the before to the second after period. There 

was a significant increase at two treatment sites, but there was also a very 

significant decrease at another treatment site. A multifactor ANOVA found that 

the treatment site–time period interaction was not statistically significant (F2,4160 = 

0.51, p > 0.05) when including observations of free-flow vehicles only and 

controlling for the presence of vehicles in the opposing lane, time of day, and 

vehicle type. This suggests that the HFST did not affect the change in vehicle 

speeds between the PC and midcurve locations in the current study.

o Vehicles Exceeding PSL—The research team calculated and compared the 

percentage of vehicles exceeding the PSL and the advisory speed at the treatment 

and control sites. There were no visible trends from the before period to after

265
treatment application in the number of passenger cars and heavy trucks observed 

to exceed the PSL. Alternatively, there appeared to be a slight reduction in the 

number of trucks exceeding the advisory speed, but there does not appear to be a 

strong effect on the number of passenger vehicles exceeding the advisory speed.

o Speed Variance Analysis—A two-sided F-test was used to compare the variance 

of vehicle operating speed in the before and after periods for passenger cars and 

heavy trucks. The effects of the HFST on the speed deviation was considered for 

the PC and curve midpoint locations because the surface was applied starting at 

the PC, or just before it, and it was assumed that the surface would have no effect 

on the speed deviation at the approach data-collection location. There was no 

consistent trend in the effects of the HFST on the speed deviation of passenger 

cars. In the first after period, the speed deviation increased at the PC for two sites, 

but also decreased at two other sites. In the second after period, the speed 

deviation decreased at the PC for two sites. In the first after period, the speed 

deviation increased at the curve midpoint at one site, but the decreased at another 

site. In the second after period, the speed deviation increased at the curve 

midpoint for two sites, but also decreased at two sites. For trucks, the speed 

deviation decreased at the PC at one site in both after periods, and also decreased 

at one site in both after periods. There was no change in speed deviation at the 

curve midpoint for trucks at any site.

• Encroachment Evaluation Results

o The purpose of the encroachment evaluation was to determine whether the HFST 

changed the proportion of vehicles that crossed either the edge line or centerline. 

There was no significant change in the braking and encroachment data that lasted 

throughout the treatment period except for an increase in the proportion of 

vehicles exiting the curve that encroached onto the shoulder at the U.S. 33 

treatment site and also a decrease in the proportion of vehicles entering the curve 

that encroached onto the shoulder at the WV Route 32 treatment site. These 

results show the HFST does not have a consistent effect on the braking and 

encroachment behavior of vehicles.

• Friction Evaluation Results

o The research team used the DF tester and CT meter to evaluate skid resistance of 

the HFST and comparison site locations. The friction level increased significantly 

from the before to the after period at the treatment sites, ranging from an increase 

of 0.21 to 0.30 in the SN65 value. At all four treatment sites, the second after

period produced friction levels that were statistically higher than the before

period, indicating the higher friction levels produced by the treatment were 

maintained for at least 1 year. For the margin of safety analysis, the research team 

estimated the available side (lateral) friction. While the available side friction is 

inconsistent from before to after at some comparison locations, the change in 

available side friction at 40 mph is quite substantial at the treatment sites.

266
o In addition to the friction curves, speed data collected were also used to compute 

the difference in friction supply and the friction demanded by vehicles traversing 

horizontal curves at the treatment and control locations. The mean friction 

demand at all sites, for all time periods, is lower than the mean side friction 

supply. The 85th percentile friction demand at all treatment sites, for all time 

periods, except the before time period of the U.S. 33 treatment site, is lower than 

the mean side friction supply. The 85th percentile friction demand for all time 

periods of the U.S. 33 comparison site is greater than the side friction supply. The 

95th percentile friction demand at all treatment sites, for all time periods, except 

the before time period of the U.S. 33 treatment site, is lower than the mean side 

friction supply. The 95th percentile friction demand for all time periods of the 

U.S. 33 comparison site is greater than the side friction supply. The only 

additional site where the friction demand at the 95th percentile exceeded the 

friction supply was at the U.S. Route 219 treatment MM 5.81 site in the before

period.

HFST Conclusions

In summary, the operational and driver behavior analyses generally found no consistent 

differences at the treatment sites between the before and after time periods based on the data 

collected in the current study. The friction analysis, however, clearly demonstrated that the 

friction supply increased considerably at the four horizontal curve treatment locations in West 

Virginia. The friction levels generally remained high for a period of 1 year after the treatment 

was applied. A safety analysis, currently being completed under a separate FHWA contract, will 

reveal further information about the safety effects of the HFST.

HFST Considerations for Future Research

The current study collected speed, driver behavior, and friction data at several HFST 

countermeasure and control sites in West Virginia. An observational before–after safety 

evaluation is being completed under a separate FHWA project, “Evaluations of Low-Cost Safety 

Improvements Pooled Fund Study (ELCSI–PFS).” Phase VI of this effort, Safety Performance 

Evaluation, includes the HFST safety evaluation. Future research is recommended to determine 

the long-term durability of the HFST by continually assessing the friction supply at the 

pavement–tire interface. The friction supply should be considered in future safety performance 

evaluations of this treatment, by considering the time-varying nature of the HFST 

countermeasure.

OPTICAL SPEED BAR EVALUATION FINDINGS

OSBs were implemented and evaluated at four sites in Arizona, eight sites in Alabama, and 

seven sites in Massachusetts. Two different designs were tested as part of this research, and a 

robust data collection and analysis was undertaken to individually track each vehicle thus 

enabling the determination of speed changes for individual vehicles. After applying the OSBs, 

the research team collected the first after period data in Arizona in November 2012 and the 

second after period data in April 2013. In Massachusetts, the research team collected after period 

data in December 2012. There was no second after period in Massachusetts. In Alabama, the 

267
research team collected the first after period data in October 2013 and the second after period 

data in December 2013. The findings of the evaluation study are as follows: 

• Mean Operating Speeds—The mean operating speeds at each sensor location for all 

sites and all data-collection periods was calculated. An initial comparison was made

between corresponding speed parameters at each site for each data-collection period 

by calculating the numerical differences in these speed parameters. The OSBs did not 

have an effect on the mean operating speeds at any of sites. There were no changes in 

speeds that were consistent across all of the sites. 

• Speed Difference Analysis—This measure computed the change in speed (delta

speed) from the approach to PC and the change in speed from the control point to the 

midpoint of the horizontal curve.

o Arizona Sites—Overall, delta speed did not change in the first after period. Delta 

speeds were significantly different at all sites in the second after period; however, 

there was no clear trend in the change in delta speed. The change in delta speed 

varied both in direction and magnitude across the different Arizona sites, with no 

strong trend present. 

o Massachusetts Sites—Unlike the Arizona sites, there was a weak trend in the 

change of delta speed at the Massachusetts sites. The OSBs may have contributed 

to a small decrease on both the delta speeds between the approach and PC and 

between the control point and curve midpoint.

o Alabama Sites—There were many changes in delta speed, but there was no clear 

trend in the change. Delta speed increased at several sites but also decreased at 

other sites. Many of the speed changes were a result of control point speeds 

changing from the before to after periods. These changes at the control point 

make it difficult to determine whether the OSBs had an effect on delta speed. The 

change in delta speed varied both in direction and magnitude across the different 

Alabama sites, with no strong trend present. 

• Analysis of Variance for Speed Differences—The research team used an ANOVA

to compare speed differences in the before and after periods. There was much 

variability in the speed changes at the different sites in Massachusetts, with the speed 

differences increasing at some sites, while decreasing at other sites.

• Vehicles Exceeding the PSL—The research team calculated the percentage of 

vehicles exceeding the PSL and the advisory speed at the treatment and control sites 

and compared between data-collection periods. There was no consistent trend in the 

change of the proportion of vehicles exceeding the speed limit, meaning the OSBs 

had no effect.

• Speed Variance Analysis—A two-sided F-test was used to compare the variances of 

vehicle operating speeds in the before and after periods for passenger cars and heavy 

268
trucks. There was no consistent trend in the change of the SD of speeds at most sites,

meaning the OSBs had no effect.

• Speed Threshold Analysis—The research team calculated the change in percentage

of vehicles traveling a certain threshold over the PSL and compared between datacollection periods. The number of drivers traveling 10 and 15 mph or more over the 

PSL were compared before and after installation of the treatment. The data did not 

indicate a consistent reduction in high-end speeding for vehicles traveling over the 

PSL.

OSB Conclusions

The results of this evaluation yielded inconsistent speed reductions at all the test sites. Based on 

the results, the following conclusions can be drawn:

• The experimental MCPW design used at seven sites in Massachusetts and four sites 

in Arizona did not show a consistent trend in speed reductions. Previously, MCPW 

used a similar design at one site and reported mean speed reductions of 2 mph during 

daytime and almost 4 mph during nighttime. However, the MCPW study did not track 

individual vehicles, and only one data collection point was used.

• The design used at eight sites in Alabama did not show reductions in speed. Previous 

studies that used this design reported minor reductions (1 to 2 mph). However, it is 

not known whether previous studies employed the same rigorous data collection and 

analysis as was undertaken by this study (i.e., tracking free-flow vehicles).

Based on the results, it can be concluded that the OSB designs used in this research were 

unsuccessful in reducing vehicle speeds. The effectiveness of OSBs depends on the bar spacing 

and marking type, and for this reason, the results of this study cannot be generalized to confirm 

the ineffectiveness of OSBs. 

OSB Considerations for Future Research

From the results of the field trials and previous OSB evaluations, it can be concluded that OSB 

treatments have little or no influence driver speeds. However, if further studies are undertaken, 

the following modifications should be considered: 

• Marking Type

o Consider evaluating non-MUTCD (2009 MUTCD, Part 3B.22, recommended 

markings to be 12 inches in width by 18 inches in length) experimental marking 

types. For instance, MCPW bar design contained two transverse markings spaced 

8 inches apart, and each marking had a 24-inch length by 8-inch width to establish 

an overall speed bar dimension of 2 ft by 2 ft. Similarly, Iowa State University 

modified the MUTCD design to include a third bar (in the middle) for more visual 

effect. The middle bar provides additional visual contrast for the driver and also 

encourages drivers to place their vehicle between the bars, which is expected to 

cause drivers to slow as they concentrate on the driving task.

269
• Evaluate the influence of the OSBs on drivers of different vehicle classes (e.g.,

trucks).

• Because the beginning of the curve is the most crucial location for influencing driver 

speeds, consider extending the treatment length such that the OSBs end at the 

midpoint of the curve.

• Conduct a review of the crash history every 2 to 5 years after installing the markings. 

This would provide sufficient time to assess the true effects of the OSB on crash 

performance. In such cases the OSBs must be refreshed to maintain visibility 

(thermoplastics is preferred over paint).

LANE-WIDTH–SHOULDER-WIDTH COMBINATION EVALUATION FINDINGS 

The study also estimated the safety effects of lane-width–shoulder-width combinations on rural 

two-lane, two-way road segments. Information was collected on 886 segments (minimum length 

of 0.5 mi) in Illinois (541) and Minnesota (345) with varying lane-width–shoulder-width 

combinations. Parameters for lane-width indicators showed that, with shoulder width ignored, 

the expected number of total (i.e., all types and severities) crashes increases as lane width 

decreases, but it is difficult to distinguish the performance of an 11-ft-lane width from a 12-ft

lane width. The main effect of shoulder width was a decrease in the expected number of crashes 

as shoulder width increased. In addition, the interaction of the lane width indicator and shoulder 

width showed that shoulder width has the greatest effect on safety when the lane width equals 

10 ft. Shoulder width also has a greater effect on safety when the lane width is 11 ft than when 

the lane width is 12 ft.

Lane-Width–Shoulder-Width Combination Conclusions

The results of the lane-width–shoulder-width safety evaluations show more complex (but 

intuitive) interactions between expected crash frequency, lane width, and shoulder width than 

what is currently reflected in the Highway Safety Manual CMFs for rural, two-lane roads. For 

any given pavement width, there are combinations of lane width and shoulder width that result in 

the lowest expected crash frequency (for all crash types and severities as well as for fatal-plusinjury crashes). For narrower total paved widths, the optimal lane width appears to be 12 ft. This 

general conclusion is consistent with conclusions from Gross et al.(48) As total paved widths 

become larger, there is not necessarily a safety benefit from using a wider lane, and in some 

cases, using a narrower lane appears to result in lower expected crash frequencies.

Lane-Width–Shoulder-Width Combination Considerations for Future Research

FHWA’s A Guide to Developing Quality Crash Modification Factors indicates that similar 

conclusions from different cross-sectional studies may be one way to increase confidence in 

CMFs derived from regression models.(81) Two separate studies, this effort together with Gross et 

al., have come to similar conclusions regarding lane-width–shoulder-width interactions on rural, 

two-lane roads using data from different States and different statistical analysis methods.(48)

The 

findings for a safety optimal lane width for a given total paved width imply an underlying 

interaction between roadway cross-section dimensions, speed, and safety. No study has been able 

270
to quantify this interaction to date, although the need to consider users’ speed adaptation in 

safety evaluations is recognized as a high-priority research topic.

(98) A before–after safety 

evaluation, with participating agencies willing to reallocate pavement width to different lanewidth–shoulder-width combinations, may offer additional insight. Ideally, this study would also 

track driver adaptation over time to the lane width and shoulder width changes, specifically with 

respect to driver speed. This additional piece of information would enhance the interpretation of 

the safety findings. Increasingly robust cross-sectional studies (e.g., larger samples, additional 

States) are recommended in the absence of such a before–after study. Supplementing the crosssectional safety data with a speed data-collection effort across a variety of lane-width–shoulderwidth combinations would again strengthen the interpretation of the safety findings. 

271

APPENDIX A. CRASH MODIFICATION FACTORS FOR GEOMETRIC DESIGN

FEATURES

Information for table 106 was gathered from the AASHTO Highway Safety Manual (2010).(37)

Table 106. CMFs for Geometric Design Features

CMF

Area 

Type

Facility 

Type Notes

Expected CMF 

(standard error)

Modify Lane Width Rural Two lane None See figure 13-1 in HSM

Modify Lane Width Rural Undivided 

multilane None See figure 13-2 in HSM

Modify Lane Width Rural Divided 

multilane None See figure 13-3 from HSM

Modify Lane Width Rural Frontage 

road None See figure 13-4 in HSM

Add or Widen 

Paved Shoulder Rural Two lane None See figure 13-5 from HSM

Add or Widen 

Paved Shoulder Rural Multilane

8- to 6-ft shoulder 1.04 (N/A)

8- to 4-ft shoulder 1.09 (N/A)

8- to 2-ft shoulder 1.13 (N/A)

8- to 0-ft shoulder 1.18 (N/A)

Add or Widen 

Paved Shoulder Rural Frontage Road None See figure 13-6 in HSM

Provide a Raised 

Median Rural Multilane Injury crashes 0.88 (0.03)

Non-injury crashes 0.82 (0.03)

Change the Width 

of an Existing 

Median

Rural Four Lane

Full access control See table 13-12 in HSM

Partial or no access control See table 13-13 in HSM

Increase the 

Distance to 

Roadside Features

Rural

Two Lane 

and 

Freeways

3.3- to 16.7-ft offset 0.78 (0.02)

16.7- to 30.0-ft offset 0.56 (0.01)

Reduce Roadside 

Hazard Rating Rural Two Lane See figure 13-8 in HSM

Modify Horizontal 

Curve Radius Rural Two lane See figure 13-9 in HSM

Improve 

Superelevation Rural Two lane

Improve superelevation variance < 0.01 1.00 (N/A)

Improve SV 0.01≤ SV < 0.02 1.00 + 6 (SV – 0.01)

Improve SV > 0.02 1.06 + 3 (SV – 0.02)

Change Vertical 

Grade Rural Two lane Increase vertical grade by 1 % (SVROR) 1.04 (0.02)

CMF = Crash modification factor

HSM = Highway Safety Manual

N/A = Not applicable

CCCCCC = ee(−0.6869+0.0668∗RRRRRR)

ee(−0.4865)

CCCCCC =

(1.55LLcc ) + �

80.2

RR � − (0.012SS)

1.55LLcc

273

APPENDIX B. CATALOG OF TRAFFIC ENGINEERING TREATMENTS

The technical information sheets in this appendix describe traffic engineering treatments shown 

to affect speed or speeding-related crashes on rural or suburban roadways. They describe each 

treatment and, along with a photograph, show the deployment condition. Design and 

construction specifications, safety and operational effectiveness, and cost are also described for 

each treatment. For ease of reference the treatments are presented in the following order:

• Speed table.

• Lateral shift.

• Speed kidney.

• Tubular channelizers.

• Transverse rumble strips.

• Longitudinal rumble strips.

• Converging chevron marking 

pattern.

• Transverse markings.

• Optical speed bars.

• Speed limit pavement legend.

• Enhanced speed limit legend 

with colored surfacing.

• SLOW pavement legend.

• Zigzag pavement markings.

• Painted medians.

• Add shoulder markings to narrow 

lane.

• Add centerline and edge line.

• Speed feedback sign.

• Speed-activated warning sign.

• Speed-activated speed limit 

reminder sign.

• Variable speed limit sign.

• Transverse pavement markings 

with speed feedback sign. 

• Advisory speed limit sign.

• Red border speed limit sign.

• One-direction large arrow (W1-

6) sign.

• Flashers to existing curve 

warning sign.

• Flags to existing curve warning 

sign.

• Combination horizontal 

alignment/advisory sign.

• Chevron sign.

• Curve warning sign and chevron 

sign and flashing beacons.

• Curve warning sign and chevron 

sign.

• Delineator post.

• Median barriers.

• Roadside barriers.

• Lane widening.

• Two-way left-turn lane.

• Additional lane (or road 

duplication).

• Paving shoulders.

• Road surface upgrades.

• Gateway treatment.

275
SPEED TABLE

Source: FHWA

Figure 141. Photo. Speed table.(53)

Description

Speed tables are midblock traffic calming devices that raise the entire wheelbase of a vehicle to 

reduce its traffic speed. Where applied, speed tables may be designed as raised midblock 

crossings, often in conjunction with curb extensions.

(99)

Design Details

Speed tables are longer than speed humps and flat-topped, with a typical height of 3 to 3.5 inches 

and a length of 22 ft. Vehicle operating speeds for streets with speed tables range from 25 to 

45 mph.(99)

Safety Effectiveness

No published safety evaluation for speed tables was identified. 

Speed Reduction Effectiveness

Speed tables have been shown to reduce 85th percentile speeds by 4 mph (-14 percent) in small, 

rural towns and 9 mph (-24 percent) on rural, residential streets.(52,54)

Cost

The cost to construct a speed table ranges from $2,000 to $15,000.(100)

276
LATERAL SHIFT

Source: City of Sparks Public Works: 

Traffic Division, Reno, NV

Figure 142. Photo. Lateral shift.(101)

Description 

A lateral shift is a curb extension that shifts travel lanes to one side of the road for an extended 

distance and then back to the other side.(102)

Design Details

A lateral shift generally includes a center island with curbing, which prohibits vehicles from 

entering the opposing lane. They may also incorporate landscaping the in center island.(101) The 

curb can be constructed from different materials, such as concrete, granite, or asphalt, depending 

on the desired appearance.

Safety Effectiveness

No published safety evaluation for a lateral shift was found. 

Speed Reduction Effectiveness

Lateral shifts from the installation of raised traffic islands have been shown to reduce 85thpercentile speeds by 11 mph (-25 percent).(102)

Cost

The cost to construct a lateral shift can vary significantly, which is mainly dependent on the type 

of material (i.e., concrete or granite), size of the offset, and the length of the transition.(101)

277
SPEED KIDNEY

Source: Alfredo Garcia

Figure 143. Photo. Speed kidney.(103)

Description

A speed kidney is a longitudinal speed bump that takes the shape of a kidney that lowers vehicle 

speeds by forcing the driver to choose one of two slow vehicle paths.(103)

Design Details

The design consists of a curved speed bump in the middle-right of the travel lane and is 

complemented by an oval speed bump with the centerline as the long axis. This design forces the 

driver to take one of two vehicle trajectories. One is to continue in a straight line, causing lower 

speeds through mounting the speed bump with either one or two wheels. The other is following 

the curved path to avoid mounting the bump. This curved path leads to lower speeds as well.(103)

Safety Effectiveness

No published safety evaluation for this treatment was found.

Speed Reduction Effectiveness

The safety kidney has been found to reduce 85th percentile speeds by 11.2 mph in urban and 

rural areas.(103)

Cost

Costs are similar to those of speed humps and speed tables and are between $2,000 and 

$15,000.(103,100)

278
TUBULAR CHANNELIZERS

Source: FHWA 

Figure 144. Photo. Tubular channelizers.(53)

Description

Tubular channelizers are 3-ft tall yellow markers placed on either side of the centerline to create

an island. These can reduce lane width.(53)

Design Details

The 3-ft tall channelizers, mounted on either side of the centerline, are spaced at 4 ft within the 

tapers, while the rest of the markers are spaced at 8 ft. A speed limit sign can be mounted to 

indicate the desired speed for this portion of the roadway.(53)

Safety Effectiveness

No published safety evaluation for this treatment was found. 

Speed Reduction Effectiveness

Channelizers have been shown to reduce 85th percentile speeds by 1 mph on main rural roads.(53)

Cost

The cost to construct tubular channelizers is estimated to be between $5,000 and $12,000. The 

reason for the high cost is that the tubes are often struck by vehicles and must be replaced.(53)

279
TRANSVERSE RUMBLE STRIPS

Source: FHWA 

Figure 145. Photo. Transverse rumble strips.(104)

Description

Transverse rumble strips are raised or grooved patterns installed perpendicular to the direction of 

travel on the roadway travel lane or shoulder pavements.(105) Typically installed on rural 

roadways that have low volume and infrequent traffic control devices, rumble strips provide an

audible and tactile warning of a downstream decision point.(106) They are different than centerline 

and edge-line rumble strips, which are located off the travel lanes. 

Design Details

Designs for transverse rumble strips can vary greatly from site to site. Grooved rumble strips are 

typically 0.5 inches deep and 4 inches wide. Raised rumble strips typically range from 0.38 to 

0.75 inches high and 4 inches wide.(107) They can either be placed as continuously or 

intermittently spaced sets of strips; spacing can vary based on operating speeds.(108)

Safety Effectiveness

Elvik and Vaa estimated the following CMFs for transverse rumble strips(109):

• 0.66 for all crash types of all severities on urban and suburban roads.

• 0.64 for all crash types of serious and minor injuries on urban and suburban roads.

Effectiveness to Reduce Speed 

Transverse rumble strips are shown to reduce speeds between 0.6 and 2.0 mph on rural 

highways.(105,106)

Cost 

The cost estimate to install transverse rumble strips ranged from $0.10 to $0.60 per linear ft. The 

cost varies based on the length of the project, whether the surface is concrete or asphalt, and if 

they are installed as a standalone project or part of a larger project.

(110)

280
LONGITUDINAL RUMBLE STRIPS

Source: FHWA 

Figure 146. Photo. Longitudinal rumble strips.(111)

Description 

Longitudinal rumble strips are raised or grooved patterns on the inside edge of the normal travel 

lane. These rumble strips have the ability to narrow effective lane width.(111)

Design Details 

Longitudinal rumble strips can be placed on both the centerline and shoulder. Typical 

dimensions of rumble strips are 7 by 16 by 5⁄8 inches. The spacing is 12 inches center to center. 

The rumble strips should be milled, but can also be rolled in.(111)

Safety Effectiveness 

Numerous safety studies prove the effectiveness of longitudinal rumble strips. Some studies have 

found that the treatment can reduce injury crashes by 14 percent, severe crashes by 18 percent, 

fatal and serious crashes by 67 percent, and overall crashes by 20 percent. (See references 112

through 115.)

Speed Reduction Effectiveness 

Longitudinal rumble strips have been found to reduce 85th percentile speeds by 4.5 mph.(63)

Cost 

The cost to install rumble strips ranges between $500 and $3,000 per mi).(111)

281
CONVERGING CHEVRON MARKING PATTERN

This pattern is not MUTCD compliant and requires FHWA experimental permission.

Source: Iowa State University 

Figure 147. Photo. Converging chevron marking pattern.(52)

Description

The converging chevron pavement marking pattern involves installing a series of white chevrons 

on the road surface. The spacing width of the chevrons and the space between them decreases as 

the driver travels through the pattern. This pattern creates the illusion that the vehicle is traveling 

faster than the vehicle’s actual speed and that the road is narrowing, which causes the driver to 

slow down.

Design Details 

Use the decreasing velocity linear equation shown in to determine spacing between each pair of 

bars:

Figure 148. Equation. Decreasing velocity linear equation

Where:

L = distance between successive pair of transverse bar pairs pair1 and pair2 (ft)

v1 = speed at pair 1 (ft/s) (speed at the first pair is the transition zone speed; speed at the last pair 

is the entrance posted speed limit)

v2 = speed at pair 2

tb = perception reaction time (0.5 s)

a = deceleration rate (ft/s2

)

LL = vv1 ∗ ttbb + (vv1

2 − vv22)

2aa

282
Safety Effectiveness 

Converging chevron pavement markings were shown to reduce crashes by as much as 

43 percent.

(116)

Speed Reduction Effectiveness

Studies of the effectiveness of converging chevron pavement marking patterns show the potential

to reduce 85th percentile speeds by 11 to 24 percent.

(116) An FHWA study reported a 3-mph 

reduction in 85th percentile speeds.(53)

Cost 

The cost to implement chevron pavement markings can range between $100 and $200 per 

marking.(117) Maintenance of converging chevrons involves regular repainting of the markings to 

maintain visibility.(53)

283
TRANSVERSE MARKINGS

Source: Virginia Center for Transportation 

Innovation and Research 

Figure 149. Photo. Transverse markings.(75)

Description

Transverse markings are a series of white transverse bars―either flat or raised―placed across 

the center of the lane and spaced progressively closer together to create the illusion that driver 

speed is increasing.(118)

Design Details

The design for transverse markings can vary from site to site. Meyer tested three different 

layouts of transverse markings.(119) One involved installing 20 bars of consistent width and 

spacing intended to warn drivers. The next layout had varied width and spacing to create the 

illusion of traveling faster. The third, for work zones, installed four sets of six bars.

Safety Effectiveness

Although there are estimates of CMFs for transverse markings on roundabout approaches, no 

high-quality safety evaluation of transverse markings was found. 

Speed Reduction Effectiveness

Transverse marking have been shown to marginally reduce 85th percentile speeds, 0.2 mph (0.3) 

on rural, horizontal curves.(118) Their application on rural highways has shown a decrease in 85th

percentile speeds by the following amounts:

• 1.4 and 3.9 mph.(120)

• 3 to 10 mph.

(75)

• 4 mph (-11 percent) in work zones.(119)

284
Cost

The cost to construct or install transverse pavement marking varies based on the material (i.e., 

paint or thermoplastics), the number of transverse bars, and the width of each bar. Traffic paint 

can be as low as $0.10/ft, and the price of wet reflective tape can range between $1 and $2/ft.(121)

Generally, the cost of a single installation will be less than $2,500.(53) The maintenance needed 

for transverse markings is regular painting of the markings to maintain visibility.(53)

285
OPTICAL SPEED BARS

Source: Virginia Center for Transportation 

Innovation and Research 

Figure 150. Photo. Optical speed bars.(75)

Description

OSBs are transverse markings with progressively reduced spacing installed on the roadway 

within a lane in a pattern to give drivers the impression that their speed is increasing. OSB can be 

used on the whole roadway (transverse) or just on the edges (peripheral). 

Design Details

Peripheral optical bars, 12 by 18 inches in size, must be installed on both sides of the lane 

perpendicular to the centerline, edge line, or lane line. Peripheral optical bars cannot be used in 

lanes that do not have a longitudinal line (centerline, edge line, or lane line) on both sides of the 

lane (in accordance with 2009 MUTCD, Part 3B. 22).

(122) The spacing of the bars decreases to 

maintain a 4-bar/s spacing. The length of the segment also needs to provide a minimum of 4 s of 

driving time within the OSBs.

(104) Mohave County, AZ, used a variation of the MUTCD design . 

In this design, two 24- by 8-inch bars, spaced 8 inches apart, were placed perpendicular to the 

centerline.

Source: FHWA

Figure 151. Illustration. Peripheral Design (2009 MUTCD, Part 3B. 22).(122)

286
Source: Mohave County Public Works, Arizona

Figure 152. Illustration. Peripheral Design Variation, Mohave County, AZ.

A variation to the typical transverse bars was used by Iowa.(123) This design consisted of three 

horizontal bars spaced at intervals so that drivers can position their vehicles within the wheel 

paths. 

Spacing between each pair of bars is determined using a decreasing velocity linear equation.

(76)

Source: Iowa State University

Figure 153. Photo. OSB Variation, Iowa State University.(124)

Safety Effectiveness

No published safety evaluation for OSBs was found.

Speed Reduction Effectiveness

Peripheral Speed Bars have been shown to reduce 85th percentile speeds by the following 

amounts:

• 0 mph.

(125)

• 0 to 2 mph.(55)

• 1 to 3 mph.(77,53,57)

• 4 to 5 mph—variation from MUTCD design.(58)

287
Cost 

The cost to implement is approximately $8/ft2. The maintenance for transverse markings requires

regular painting of the markings to maintain visibility.(53)

288
SPEED LIMIT PAVEMENT LEGEND

Source: Iowa State University 

Figure 154. Photo. Speed limit pavement legend.(126)

Description

A speed limit pavement legend places pavement markings at regularly spaced intervals to remind 

drivers of the speed limit. The speed limit pavement legend can be placed as a standalone 

treatment, at the end of converging chevrons, or in combination with lane-narrowing 

measures.

(53)

Design Details

No specific design details (i.e., width and height) were found for the speed limit pavement 

legend.

Safety Effectiveness 

No published safety evaluation for speed limit pavement legends was found. 

Speed Reduction Effectiveness 

Studies indicate that speed limit pavement legends can reduce 85th percentile speeds by 1 mph 

(-1 percent) on rural, main roadways.(53)

Cost 

The cost to install speed limit pavement legends varies based on how often the legend is applied 

but generally is less than $2,500. The maintenance needed for speed limit pavement legends is 

regular repainting of the legend to maintain visibility.(53)

289
ENHANCED SPEED LIMIT LEGEND WITH COLORED SURFACING

The colored outline is not MUTCD compliant and requires FHWA experimental permission.

Source: Iowa State University 

Figure 155. Photo. Enhanced speed limit legend with colored surfacing.(123)

Description

An enhanced speed limit legend with colored surfacing involves the same treatment as the speed 

limit pavement legend, except the legend is surrounded by an additional colored box. The

legends are spaced at regular intervals to remind drivers of the speed limit.(53)

Design Details

The red-colored surface was used to evaluate the effectiveness of enhanced speed limit legends. 

A large red rectangle (9.5 by 12 ft) was placed around the on-pavement speed limit markings, 

which were 35 mph at the test sites. The edge line was also widened to 8 inches along the 

treatment to enhance visibility.(53)

Safety Effectiveness

No published safety evaluation for enhanced speed limit legends with colored surfacing was 

found. 

Speed Reduction Effectiveness

Studies show that enhanced speed limit legends with colored surfacing can reduce 85thpercentile speeds by 2 mph (-4 percent) on rural, main roadways.(53)

Cost

The cost to enhanced speed limit legends with colored surfacing varies based on how often the 

legend is applied, but generally is less than $2,500. The maintenance required is regular 

repainting of the legend to maintain visibility; the red background has been shown to fade 

quickly, so there may need to be an accelerated repainting cycle.(53)

290
SLOW PAVEMENT LEGEND

Source: Iowa State University

Figure 156. Photo. Slow pavement legend.(52)

Description 

A pavement marking legend is installed in the travel lane to indicate SLOW—the driver should 

reduce speed.

Design Details 

One study installed the SLOW pavement marking prior to a horizontal curve. The word SLOW 

was installed approximately 220 ft upstream of the PC of a horizontal curve. The marking 

consisted of the word SLOW in 8-ft-high white letters. There was also an 8-ft-high arrow 

installed above the word SLOW. In addition to these two markings, an 18-inch-wide white line 

was installed perpendicular to the road, at the beginning and end of the marking.(127)

Safety Effectiveness 

No published safety evaluation for installing SLOW pavement legends was found. 

Speed Reduction Effectiveness 

SLOW pavement legends have been shown to increase 85th percentile speeds by 1 mph, but they 

have also been shown to decrease 85th percentile speeds by 2 mph.(53,129)

Cost 

The cost to install a SLOW pavement legend is less than $2,500. The maintenance needed for the 

pavement legend is regular repainting to maintain visibility.(53)

291
ZIGZAG PAVEMENT MARKINGS

Zigzag pavement markings are not included in MUTCD.

Source: Virginia Center for Transportation 

Innovation and Research 

Figure 157. Photo. Zigzag pavement markings.(61)

Description 

A painted zigzag line in the center of the travel lane is used to indicate upcoming pedestrian 

crossings or horizontal curves.(61)

Design Details 

The zigzag extends 500 ft from the crosswalk or beginning of the curve. The width of the painted 

line should be larger than the centerline and edge lines, meaning 6 inches should suffice for 

4-inch edge and centerline markings. The lateral width of the zigzag is 4 ft, smaller than typical 

vehicle track widths to avoid paint wear from traffic. The length of one line in the zigzag is 12 ft. 

The zigzag should be painted white.(61)

Safety Effectiveness 

No published safety evaluation for this treatment was found.

Speed Reduction Effectiveness 

The zigzag markings have been found to reduce 85th percentile speeds by up to 1.3 mph in 

suburban areas.(61)

Cost 

Initial costs for the pavement markings are estimated to be $2,850, including labor and materials. 

The total cost over 5 years should be expected to be $5,700, assuming reapplication of the lines 

in 2 to 3 years.(61)

292
PAINTED MEDIANS

Source: FHWA 

Figure 158. Photo. Painted medians.(128)

Description 

Typically used at intersections, painted medians are flush medians marked with painting that 

separate opposing traffic lanes.(122)

Design Details 

Widths of painted medians vary depending on available right-of-way. Markings consist of edge

lines and cross hatching and should be implemented in accordance with Section 3B.03 of the 

MUTCD.(122)

Safety Effectiveness 

This treatment has been found to reduce fatal crashes on rural and urban roads by 20 percent.

(129)

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost 

Costs are typically between $10,000 and $30,000 per intersection, but they can range as high as 

$70,000.(130)

293
ADD SHOULDER MARKINGS TO NARROW LANE

Source: FHWA

Figure 159. Photo. Add shoulder markings to narrow lane.(53)

Description 

Installing wide edge line and crosshatch markings creates a shoulder on both sides of the 

roadway to reduce lane widths.

Design Details 

In the study that evaluated this treatment, an existing two-lane roadway that was 36 ft wide from 

curb to curb was reduced to single 10.5-ft lanes in both directions. This was accomplished by 

using wide edge line and crosshatching. The study suggested that it may be more effective to 

reduce the lane width even more, or it may be necessary to install physical barriers because there 

are no consequences for crossing the pavement markings.(53)

Safety Effectiveness 

No published safety evaluation for adding shoulder markings to narrow lanes was found. 

Speed Reduction Effectiveness 

Adding shoulder markings to narrow lanes has had minimal effects on 85th percentile speeds, 

with an increase of 0.5 mph.(53)

Cost 

Traffic paint can be as low as $0.10/ft and the price of wet reflective tape can range between 

$1 and $2/ft.(121) Generally, the cost will be less than $2,500.(53) The maintenance needed for 

shoulder markings is regular repainting of the markings to maintain visibility.(53)

294
ADD CENTERLINE AND EDGE LINE

Source: FHWA

Figure 160. Photo. Add centerline and edge line.(53)

Description

Installation of median and shoulder pavement markings reduces lane widths. 

Design Details 

The pavement markings can vary from site to site, based on the characteristics of each site and 

the intended purpose. One study added a 10-ft-wide painted center island and added a 6-inch 

edge line to separate the travel lane from the 8-ft parking lane. The lane widths decreased from 

approximately 16 to 11 ft in each direction).(53)

Safety Effectiveness 

Studies show that adding centerline and edge line pavement markings can reduce fatal and injury 

crashes by 8.6 percent.(48) There are many CMFs for different edge line and shoulder treatments. 

Installing edge lines on tangents and curves has the following CMFs:

(131)

• 0.921 for all crash types of all severities.

• 0.888 for all run-off-road crashes of all severities.

Speed Reduction Effectiveness 

Adding a centerline and edge line have been shown to reduce 85th percentile speeds by the 

following amounts:

• 1 mph on rural, main roads.(53)

• 2 mph during the day on rural, two-lane roads.(132)

• 1 mph during the night on rural, two-lane roads.(132)

• 3.5 mph at rural, two-way, stop-controlled intersections.(48)

295
Cost 

The cost to install centerline and edge line pavement markings can be as low as $0.10/ft for 

paint, but the price of wet reflective tape can range between $1 and $2/ft.(121) Generally, the cost 

will be less than $2,500.(53) The maintenance needed for shoulder markings is regular painting of 

the markings to maintain visibility.(53)

296
SPEED FEEDBACK SIGN

Source: Iowa State University 

Figure 161. Photo. Speed feedback sign.(126)

Description 

A speed feedback sign is a dynamic sign that displays the speed of approaching vehicles.(53)

Design Details 

Speed feedback signs vary based on the site. Most signs display the text, YOUR SPEED along 

with the measured speed of the approaching vehicle.

(53)

Safety Effectiveness 

No published safety evaluation for speed feedback signs was found. 

Speed Reduction Effectiveness 

Studies indicate that speed feedback signs can reduce 85th percentile speeds by the following 

amounts:

• 7 mph.(53)

• 2 mph.(62)

• 3 mph.(63)

• 4 mph.(64)

• 2 mph.(65)

• 6.3 mph.(66)

• 2 to 3 mph.(67)

Cost 

The cost to install a speed feedback sign can range from $5,000 to $12,000.(53)

297
SPEED-ACTIVATED WARNING SIGN

Source: Clemson University

Figure 162. Photo. Speed-activated warning sign. (133)

Description 

A speed-activated warning sign consists of a fixed-message, speed-activated sign that triggers a 

flashing beacon when a predetermined speed threshold is exceeded. The speed-activated sign is a 

4- by 4-ft corrugated plastic reflective sign with 6-inch lettering reading “YOU ARE SPEEDING IF 

FLASHING.” To increase the speed-activated sign’s visibility, two 1- by 1-ft orange plastic flags were 

added.

Design Details 

The design of speed-activated warning signs can vary from one site to another, depending on the 

intended purpose of the sign. The sign shown above and the one used by Mattox et al. was a 

4- by 4-ft corrugated plastic reflective sign with 6-in lettering reading YOU ARE SPEEDING IF 

FLASHING.(131) A beacon atop the sign flashes when a vehicle exceeds a certain threshold.(133)

This is a temporary sign; however, there are also permanent speed-activated signs.

Safety Effectiveness 

No published safety evaluation for speed-activated warning signs was found. 

Speed Reduction Effectiveness 

Speed-activated warning signs are shown to reduce 85th percentile speeds by the following 

amounts:

• 1.6 to 4.7 mph on multilane highways.(133)

• 4 mph on rural, four-lane-divided highways.(134)

• 1 mph on rural curves on Interstates.(135)

Cost 

The cost to install the sign used by Mattox et al. was approximately $1,500.(133) Other, more 

permanent installations can cost between $5,000 and $12,000.(53)

298
SPEED-ACTIVATED SPEED LIMIT REMINDER SIGN

Source: SWARCO Traffic Ltd

Figure 163. Photo. Speed-activated speed limit reminder sign.

Description 

A speed-activated-speed limit reminder sign is an electronic speed-limit sign activated by an 

approaching vehicle.

Design Details 

The vehicle-actuated fiber-optic 30-mph sign was installed 624 meters (680 yd) prior to a 

20-mph zone.(136)

Safety Effectiveness 

No published safety evaluation for speed-activated speed limit reminder signs was found. 

Speed Reduction Effectiveness 

Studies show that speed-activated speed limit reminder signs can reduce 85th percentile speeds 

by 5 mph on major roads.(136)

Cost 

The cost to install a speed-activated speed limit reminder sign is comparable to other electronic 

signs with radar, which can range between $2,000 and $12,000.(53)

299
VARIABLE SPEED LIMIT SIGN

Source: FHWA

Figure 164. Photo. Variable speed limit sign.(137)

Description 

A variable speed limit sign is an electronic message sign that displays dynamic information 

related to the speed limit. These signs can indicate a reduced speed limit during wet or low-light 

weather conditions, which may improve safety by decreasing the risks associated with vehicles 

traveling at speeds higher than appropriate for the conditions.(137)

Design Details 

Variable speed limit signs can be used in place of static speed limit signs placed to the right of 

the shoulder, or they can be mounted over the individual lanes of a multilane highway and 

individual lanes can have varying speed limits. A variable speed limit for wet conditions is 

justified when adverse weather conditions cause traffic problems, when there is a higher crash 

rate than expected for similar segments, the regular occurring safe speed limit is at least 10 mph 

less than the normal speed limit, or there are conditions when stopping distance exceeds 

available sight distance.

Safety Effectiveness 

The following CMF for variable speed limit signs has been estimated:

• 0.92 for all crash types of all severities in urban areas (four star).

(138)

Speed Reduction Effectiveness 

Variable speed limit signs have been shown to reduce 85th percentile speeds by the following 

amounts:

• 4.7 to 8 mph.

(139)

• 5 mph.(140)

• 0.47 to 0.75 mph per 1-mph reduction in the PSL.

(141)

300
Cost 

The cost to install a single variable speed limit sign is between $5,000 and $12,000, similar to 

speed feedback signs.(53) The cost to install variable speed limits on a multilane highway is 

significantly higher than the cost of the overhead structure.

301
TRANSVERSE PAVEMENT MARKINGS WITH SPEED FEEDBACK SIGN

Source: FHWA

Figure 165. Photo. Transverse pavement markings with speed feedback sign.(53)

Description

Transverse pavement markings are placed at the entrance to a community. Speed feedback signs 

were placed immediately downstream of the transverse pavement markings.(53)

Design Details

The markings are 12 inches wide by 18 inches long (perpendicular to roadway edge). Spacing 

between the bars decreases approaching the neighborhood, which can cause the driver to slow 

down because the visual sense is one of speeding up. A static speed feedback sign is placed at 

the end of the markings. These signs display YOUR SPEED and show the current vehicle 

speed.(53)

Safety Effectiveness

No published safety evaluation for this treatment was found. 

Speed Reduction Effectiveness

This combination of treatments has been found to reduce 85th percentile speeds by 4 mph.(53)

Cost

The cost of this treatment is estimated to range between $5,000 and $12,000, with regular 

painting being the most significant maintenance concern.(53)

302
ADVISORY SPEED LIMIT SIGN

Source: FHWA

Figure 166. Photo. Advisory speed limit sign.(122)

Description 

This treatment entails installing a static yellow advisory speed limit sign to provide drivers with 

advisory speeds for less than ideal roadway conditions.(122)

Design Details 

Use the sign as a supplement to another advisory sign, such as for a turn or horizontal curve. Size 

is typically either 18 by18 inches or 24 by 24 inches. Install the sign following the guidelines set 

forth for the advisory speed limit sign (W13-1P) and the following signs: W13-2, W13-3, W13-

6, and W13-7, in the MUTCD.(122)

Safety Effectiveness 

Published CMFs indicate that advisory speed limit signs installed in combination with horizontal 

alignment warning signs can affect safety as follows(109)

:

• 13-percent reduction (CMF = 0.87) in injury crashes.

• 29-percent reduction (CMF = 0.71) in PDO crashes.

Speed Reduction Effectiveness 

Installing an advisory speed limit sign has been found to reduce 85th percentile speeds by 

15 percent.

(142)

Cost 

A 30-inch advisory speed limit sign with engineer-grade reflective sheeting costs approximately 

$50.

(143)

303
RED BORDER SPEED LIMIT SIGN

Colored border is not MUTCD compliant and requires FHWA experimental permission.

Source: Texas Transportation 

Institute

Figure 167. Photo. Red border speed limit sign.(144)

Description 

A red border speed limit sign is a standard speed limit sign with an added red border. The red 

border is designed to increase the visibility of the sign, and drivers may recognize an increased 

sense of importance because of the enhanced red border.(59)

Design Details 

Two different red border signs have been used. The first is a standard speed limit sign (R2-1) that 

adds 6 inches to the height and width that allows for a 3-inch red border to be added around the 

existing speed limit sign. The second red border sign removed the black border from the standard 

speed limit sign and replaced it with a 1-inch red border along with the 3-inch border from the 

first red border sign. This sign had a 4-inch red border.(58)

Safety Effectiveness 

No published safety evaluation for installing red border speed limit signs was found. 

Speed Reduction Effectiveness 

Red border speed limit signs have been shown to reduce 85th percentile speeds by 3 mph on 

two-lane highways.

Cost 

The cost to install a red border speed limit sign is similar to a standard speed limit sign plus the 

cost to modify the sign.

304
ONE-DIRECTION LARGE ARROW (W1-6) SIGN

Source: KLS Engineering, LLC

Figure 168. Photo. One-direction large arrow (W1-6) sign.

Description 

A one-direction large arrow sign (W1-6) is placed on a horizontal curve to alert drivers that they 

are approaching a horizontal curve and its direction.

Design Details 

A one-direction large arrow sign (W1-6) is designed in accordance with the MUTCD. For a 

single lane or multilane road, a W1-6 sign is 48 by 24 inches. On an expressway or freeway, a 

W1-6 sign is 60 by 30 inches. A one-direction large arrow sign is placed on the outside of a 

curve at a right angle to oncoming traffic. As with any warning sign, a W1-6 sign has a yellow 

background with a black arrow.(122)

Safety Effectiveness 

No published safety evaluation for installing a one-direction large arrow was found.

Speed Reduction Effectiveness 

One-direction large arrows have been shown to have no effect (0 mph speed reduction) on 85th

percentile speeds of vehicles on rural, horizontal curves.(118)

Cost 

The cost to install a one-direction large arrow sign is less than $500.(145)

305
ADD FLASHERS TO EXISTING CURVE WARNING SIGN

Source: KLS Engineering, LLC

Figure 169. Photo. Add flashers to existing curve warning sign.

Description 

Six-inch flashing amber lights are added to an existing curve warning sign.(118)

Design Details 

Two flashing amber lights are added to an existing curve warning sign. 

Safety Effectiveness

No published safety evaluation for adding flashers to an existing curve warning signs was found. 

Speed Reduction Effectiveness 

Adding flashers to an existing curve warning sign has been shown to increase 85th percentile 

speeds by 1 mph.(118)

Cost 

The cost to add flashing lights to an existing sign is less than $500.(145)

306
ADD FLAGS TO EXISTING CURVE WARNING SIGN

Source: University of Kentucky

Figure 170. Photo. Curve warning sign with flags.(118)

Description 

Red flags are added to an existing curve warning sign to attract driver attention. 

Design Details 

Two red flags are added to an existing curve warning sign. 

Safety Effectiveness 

No published safety evaluation for adding flags to an existing curve warning signs was found. 

Speed Reduction Effectiveness 

Adding flags to an existing curve warning sign has been shown to reduce 85th percentile speeds 

by 0.3 mph.(118)

Cost 

The cost to add flags to an existing sign is less than $500.

307
COMBINATION HORIZONTAL ALIGNMENT/ADVISORY SIGN

Source: FHWA

Figure 171. Photo. Combination horizontal alignment/advisory sign.(122)

Description

A sign containing both a curve or turn ahead and advisory speed is installed prior to a horizontal 

curve. 

Design Details

A combination Turn/Advisory Speed (W1-1a) and a combination Curve/Advisory Speed (W1-

2a) are designed in accordance with the MUTCD. These signs can used to supplement the 

advanced horizontal alignment warning sign and advisory speed plaque, but they should not be 

used alone or used as a substitute for a horizontal alignment warning sign and advisory speed 

plaque. Install the W1-1a and W1-2a sign at the beginning (PC) of the turn or curve, if installed. 

For a single lane or multilane road, W1-1a and W1-2a signs are 36 by 36 inches. On an 

expressway or freeway, W1-1a and W1-2a signs are 48 by 48 inches. As with any warning sign, 

W1-1a and W1-2a signs have a yellow background and black arrows/text.(122)

Safety Effectiveness

The following CMFs for combination Turn/Advisory Speed and combination Curve/Advisory 

Speed signs have been estimated:

(109)

• 0.87 for all crash types that are serious and minor injuries.

• 0.71 for all crash types that are PDO.

Speed Reduction Effectiveness:

Installing a combination Turn/Advisory Speed or combination Curve/Advisory Speed sign has 

been shown to increase 85th percentile speeds by 0.2 mph.(146)

308
Cost

The cost to install a combination Turn/Advisory Speed or combination Curve/Advisory Speed 

sign is less than $500.

(145)

309
CHEVRON SIGN

Source: Iowa State University

Figure 172. Photo. Chevron sign.(52)

Description 

Installing chevron alignment signs (W1-8) on a horizontal curve provides additional guidance 

and emphasis for a change in horizontal alignment.

Design Details 

Install chevron alignment signs in accordance with the MUTCD. For a single lane or multilane 

road, a W1-8 sign is 18 by 24 inches. On an expressway, a W1-8 sign is 30 by 36 inches. On an 

expressway, a W1-8 sign is 36 by 48 inches. Install chevron alignment signs at a minimum 

height of 4 ft. The spacing of the signs depends on the curve radius and is guided by Table 2C-6 

in the MUTCD. As with any warning sign, a W1-8 sign has a yellow background with a black 

arrow.(122)

Safety Effectiveness 

The following CMFs for chevrons have been estimated (all four-star):

(147)

• 0.96 for non-intersection crashes of all severities.

• 0.94 for head on, non-intersection, run-off-road, and sideswipe crashes of all 

severities.

• 0.84 for non-intersection, fatal, serious injury, and minor injury crashes.

• 0.75 for nighttime, non-intersection crashes of all severities.

• 0.78 for head on, nighttime, non-intersection, run off road, and sideswipe crashes of 

all severities.

Speed Reduction Effectiveness 

Chevron alignment signs have been shown to reduce 85th percentile speeds on rural horizontal 

curves by the following amounts:

• 0.7 mph.(118)

310
• 2.4 to 5.28 km/h.(148)

• 1.28 mph.(149)

Cost 

The cost to install a chevron alignment sign is less than $500.(145)

311
CURVE WARNING SIGN AND CHEVRON SIGN AND FLASHING BEACONS

Source: Michigan Department of Transportation

Figure 173. Curve warning sign and chevron sign and flashing beacons.

Description

Curve warnings signs are placed on the approach to a horizontal curve. These are supplemented 

with flashing beacons to attract the driver’s attention and chevrons to delineate the curve.(104)

Design Details 

Refer to MUTCD guidelines for Curve Warning Signs (W1-1, W1-2) and Chevron Alignment 

Signs (W1-8). Also refer to MUTCD, Chapter 4L, for proper use of flashing warning 

beacons.(104,122)

Safety Effectiveness 

There are many safety benefits of this signage combination, including numerous crash 

modification factors. Some published CMFs indicate a reduction of 40 percent in all types of 

crashes on rural roads. The treatment was also found to reduce all types of crashes under wet 

conditions by 47 percent.

(150)

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost 

Costs for this treatment vary depending on the number of chevron signs (W1-8) installed―

10 chevron signs typically cost $500. The cost of the curve warning sign (W1-2) can vary based 

on size and quality but should not exceed $500. A solar-powered yellow beacon should cost 

about $2,200, more if solar power is not used.

(104,117)

312
CURVE WARNING SIGN AND CHEVRON SIGN

Source: Tom Welch

Figure 174. Photo. Curve warning sign and chevron sign.

Description 

Curve warnings signs are placed on the approach to a horizontal curve. These are supplemented 

with chevrons placed along the curve.(104)

Design Details 

Refer to 2009 MUTCD Section 2C.10 for Curve Warning Signs (W1-1, W1-2) and Chevron 

Alignment Signs (W1-8) guidelines. 

Safety Effectiveness 

There are many safety benefits of this signage combination. In general, this treatment has a CMF

of 0.60, indicating a 40-percent reduction in all crashes on rural roads. This combination of 

signage can also reduce nighttime crashes on rural horizontal curves by 40.8 percent (CMF = 

0.592).(150)

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost 

Costs for this treatment vary depending on the number of chevron signs (W1-8) installed. Ten

chevron signs typically cost $500. The curve warning sign (W1-1, W1-2) can vary based on size 

and quality. In total, the cost (including the chevrons) should be less than $1,000.(104,117)

313
DELINEATOR POST

Source: Texas Transportation Institute

Figure 175. Photo. Delineator post.(151)

Description

Delineator posts are retroreflective devices mounted above the roadway surface and along the 

side of the roadway in a series to emphasis the roadway alignment and guide drivers. They 

provide the benefit that they remain visible when the road is wet.(122)

Design Details

The retroreflective element of a delineator has a minimum 3-inch height. On mainline tangent 

sections, the distance between delineators should be between 200 and 530 ft. The distance 

between delineators on horizontal curves is determined by the radius of the curve, which Table 

3F-1 in the MUTCD shows. Delineators are typically placed between 2 and 8 ft beyond the 

shoulder edge.(122)

Safety Effectiveness

The following CMFs are estimated for delineator posts:

(109)

• 1.04 for all crash types for serious and minor injuries in rural areas.

• 1.05 for all crash types for property damage only that are in rural areas (PDO).

• 0.55 for all crash types for serious and minor injuries.

There are also reports of a 30-percent reduction in crash after installing delineator posts.

(38)

Speed Reduction Effectiveness

Delineator posts have been shown to slightly increase 85th percentile speeds by 0.5 mph on 

rural, horizontal curves.(118) They have also been shown to reduce 85th percentile speeds by 

7 percent.

(142)

314
Cost

The cost to install a delineator post is approximately $30−$50 per delineator.(145)

315
MEDIAN BARRIERS

Source: KLS Engineering, LLC

Figure 176. Photo. Median barriers.

Description 

A median barrier is a physical barrier used to separate opposing traffic.(152)

Design Details 

Many types of barriers can be used in this setting, including tubular channelizers, cable barriers, 

guiderail, and concrete barriers. These barriers are placed along the centerline of the roadway to 

separate traffic. Refer to AASHTO roadside design guidance for complete specific design 

details.(153)

Safety Effectiveness 

Median barriers have been found to reduce fatal crashes by 50 percent in both urban and rural 

settings.(152) There are numerous CMFs regarding median barriers that depend on the type of 

barrier used. In general, simply adding a median barrier reduces fatal crashes on rural roadways 

by 43 percent (CMF = 0.57) and injury crashes by 30 percent (CMF = 0.70).(109)

Speed Reduction Effectiveness 

No published speed evaluation for this treatment has been found.

Cost 

Costs vary based on barrier used. Typical costs range from $50,000 to $300,000 for cable 

barriers, $83,000 to $600,000 for guardrail, and $120,000 to $2.7 million for concrete 

barriers.(153)

316
ROADSIDE BARRIERS

Source: KLS Engineering, LLC

Figure 177. Photo. Roadside barriers.

Description 

Roadside barriers are placed along the side of the road to safely redirect vehicles from roadside 

hazards.(154)

Design Details 

Multiple types of roadside barriers can be used. These include flexible barriers such as cable 

barriers, semi-rigid barriers such as guardrail, and rigid barriers such as concrete barriers. Design 

should conform to AASHTO design guidance.

(28)

Safety Effectiveness 

This treatment is found to reduce crashes by 40 percent in both urban and rural areas.(155) The 

following CMFs related to roadside barriers have been published:

(109)

• 0.53 (47-percent reduction) for minor and serious injury run-off-road crashes.

• 0.56 (44-percent reduction) for fatal run-off-road crashes.

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost 

Costs vary based on barrier used. Typical costs range from $50,000 to $300,000 for cable 

barriers, $83,000 to $600,000 for guardrail, and $120,000 to $2.7 million for concrete 

barriers.(153)

317
LANE WIDENING

Source: FHWA

Figure 178. Photo. Lane widening.(48)

Description

Lane widening, as indicated, increased the width of a travel lane.

Design Details

Lanes can be widened by adding paved width to the cross section.

Safety Effectiveness 

The safety effectiveness of lane widening is based on original and new lane width. Research 

shows that in urban and rural environments, increases in lane width from 9 to 10 ft result in a 13-

percent reduction in crashes. A change from 10 to 11 ft results in a 19-percent reduction in 

crashes. Finally, an increase from 11 to 12 ft only results in a 5-percent reduction.(129) Published

CMFs exist but are not listed here because they are contingent on original and modified lane 

width.

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost

Costs vary significantly based on right-of-way acquisition, pavement design, etc. Refer to the 

local transportation agency for more accurate cost estimation for road construction and 

modification in the area. 

318
TWO-WAY LEFT-TURN LANE

Source: FHWA

Figure 179. Photo. Two-way left-turn lane.(156)

Description 

A TWLTL is a wide, painted center turning lane that also functions as a median.(156)

Design Details 

A TWLTL ranges between 10 and 16 ft wide. The edges are marked by a solid yellow line on the 

side of traffic and a broken yellow line on the inside. Opposing left-turn arrows are also painted 

at regular intervals along the length of the lane.(28)

Safety Effectiveness 

TWLTLs have been found to reduce crashes on rural two-lane roads by 29 percent.

(156) The 

following are estimated CMFs for TWLTL:

(157)

• 0.69 (31-percent reduction) in all crashes on approaches to unsignalized three-legged 

intersections.

• 0.66 (34-percent reduction) in all crashes on approaches to unsignalized four-legged 

intersections.

Speed Reduction Effectiveness 

TWLTLs have been found to reduce 85th percentile speeds by 12.6 km/h (7.8 mph) on rural and 

suburban roads.(71)

Cost 

Costs vary depending on State, with Arkansas, North Carolina, and California finding costs 

between $425,000 and $500,000 per mi to build, while the cost in Illinois was $1.78 million per 

mi. Maintenance costs are negligible compared with these prices.(156)

319
ADDITIONAL LANE (OR ROAD DUPLICATION)

Source: KLS Engineering, LLC

Figure 180. Photo. Additional lane.

Description

Adding an extra lane in one (or both) directions to provide an opportunity for fast-moving 

vehicles to pass slower moving ones. These can be classified as climbing lanes or passing 

lanes.(28)

Design Details

The additional travel lane should have the same characteristics of the existing travel lanes. If the 

intended function of the travel lane is as a truck climbing lane, the design should be based on 

guidelines in the AASHTO Green Book. Similarly, the Green Book can provide guidance if the 

lane’s intended function is as a passing lane.(28)

Safety Effectiveness

This treatment has been found to reduce crashes on rural roads by between 25 and 

50 percent.

(152,129)

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost 

Costs vary significantly based on right-of-way acquisition, pavement design, etc. Refer to the

local transportation agency for accurate cost estimation for road construction in the area.

320
PAVING SHOULDERS

Source: FHWA 

Figure 181. Photo. Paving shoulder.(158)

Description 

The addition of a paved shoulder provides a paved surface for an errant vehicle to recover and 

return to the roadway.(155)

Design Details 

The preferred width of a paved shoulder is between 6 and 8 ft at a slope steeper than the travel 

lane. For example, if a travel lane has a 2-percent cross slope, then the shoulder should be at least 

4 percent. Delineate the shoulder with a painted edge line.(28)

Safety Effectiveness 

A paved shoulder has been found to reduce crashes on urban and rural roadways by 

30 percent.

(155) Published CMFs exist for this treatment. These factors vary based on the previous 

shoulder before paving and the dimensions of the new shoulder.

Speed Reduction Effectiveness 

No published speed evaluation for this treatment was found.

Cost 

The cost to construct a paved shoulder ranges from $18.47/yd2 to $111.19/yd2

. This price range 

is so diverse because the cost is based on materials used and pavement depth.(159)

321
ROAD SURFACE UPGRADES

Source: KLS Engineering, LLC

Figure 182. Photo. Road surface.

Description 

Road surface upgrades are pavement resurfacing projects, mainly performed to support the 

structural strength of the roadway.(160)

Design Details 

Designs for roadway resurfacing projects are context sensitive. Depth and material should be 

based on traffic loading, environment, local and state agency guidelines, etc. Refer to the local 

transportation agency for specific pavement resurfacing guidelines.

Safety Effectiveness 

Multiple studies have quantified the safety effect of roadway surface upgrades. One study found 

the surface upgrades can reduce crashes by 35 percent on urban and rural roads.(155) Another 

study has found a 33-percent reduction in crashes on rural roads.(160)

Speed Reduction Effectiveness 

No published speed evaluations for this treatment have been found.

Cost 

Costs for roadway surface upgrades are extremely variable. The cost is based on depth of 

resurfacing, material, whether or not the old surface is to be milled, etc. 

322
GATEWAY TREATMENT

Source: Iowa State University

Figure 183. Photo. Gateway treatment.

Description 

Gateway treatments are a combination of signage and aesthetics that convey entrance to a 

community.(126,53)

Design Details 

Common tools used in gateway treatments include welcome signs, textured pavements, and 

pavement markings. Most are placed on the roadside, but some can span over the roadway.(126,53)

Safety Effectiveness 

Published CMFs indicate a 2-percent reduction in crashes (CMF = 0.98) resulting from gateway 

treatments.(161)

Speed Reduction Effectiveness 

Gateway treatments have been shown to reduce 85th percentile speeds by 2 mph.(53)

Cost 

The cost to construct a gateway treatment can vary greatly, depending on the design of the sign. 

For example, an intricate gateway treatment may cost almost $10,000, including labor and 

materials.(55)

323

APPENDIX C. SAFETY EFFECTS OF LANE-WIDTH AND SHOULDER-WIDTH 

COMBINATIONS 

ON RURAL, TWO-LANE ROADS (ADDITIONAL MODELING RESULTS)

Table 107. Negative binomial regression model estimation results for property damage only

crashes (all severities).

Variable Coefficient

Standard 

Error z P > z

95-Percent Confidence

Interval

ln_aadt 0.649 0.061 10.700 < 0.001 0.530 0.768

illinois 1.195 0.108 11.080 < 0.001 0.984 1.407

Lane10 1.047 0.227 4.610 < 0.001 0.602 1.493

Lane11 0.431 0.166 2.610 0.009 0.107 0.756

shoulder -0.052 0.024 -2.140 0.032 -0.100 -0.004

ln10shld -0.119 0.060 -1.980 0.048 -0.238 -0.001

ln11shld -0.037 0.032 -1.160 0.246 -0.099 0.025

barrier 4.346 1.807 2.400 0.016 0.804 7.889

drvwy_den 0.016 0.007 2.340 0.019 0.003 0.029

solid_CL 0.563 0.215 2.620 0.009 0.143 0.984

dash1_CL 0.992 0.334 2.970 0.003 0.338 1.646

curve 0.253 0.076 3.340 0.001 0.105 0.402

_cons -5.401 0.486 -11.120 < 0.001 -6.352 -4.449

ln(Length) 1 (exposure) — — —

/lnalpha -0.86727 0.117387 — — -1.09734 -0.63719

alpha 0.420098 0.049314 — — 0.333757 0.528774

Log likelihood = -1473.751

Number of Observations = 877

LR chi2(12) = 425.44

Prob > chi2 = 0

Pseudo R2 = 0.1261

Likelihood-ratio test of alpha=0: chibar2(01) = 254.30 Prob>=chibar2 = 0.000

— Indicates Not Available

325
Table 108. Negative binomial regression model estimation results for single-vehicle crashes 

(all severities).

sv_all Coefficient

Standard 

Error z P > z

95-percent Confidence 

Interval

ln_aadt 0.514 0.059 8.67 < 0.001 0.398 0.631

illinois 1.128 0.103 10.9 < 0.001 0.925 1.331

Lane10 0.896 0.219 4.08 < 0.001 0.466 1.326

Lane11 0.413 0.160 2.58 0.010 0.099 0.727

shoulder -0.064 0.024 -2.71 0.007 -0.111 -0.018

ln10shld -0.090 0.058 -1.56 0.120 -0.202 0.023

ln11shld -0.030 0.031 -0.99 0.323 -0.091 0.030

barrier 3.597 1.760 2.04 0.041 0.147 7.046

drvwy_den 0.017 0.007 2.630 0.009 0.004 0.030

solid_CL 0.478 0.208 2.300 0.022 0.070 0.886

dash1_CL 0.923 0.324 2.850 0.004 0.288 1.559

curve 0.246 0.074 3.330 0.001 0.101 0.391

_cons -4.174 0.469 -8.890 < 0.001 -5.094 -3.254

ln(Length) 1 (exposure) — — —

/lnalpha -0.94318 0.120937 — — -1.180212 -0.7061473

alpha 0.389388 0.047092 — — 0.3072135 0.493542

Log likelihood = -1493.2046

Number of Observations = 877

LR chi2(12) = 408.55

Prob > chi2 = 0

Pseudo R2 = 0.1203

Likelihood-ratio test of alpha=0: chibar2(01) = 229.65 Prob>=chibar2 = 0.000

— Indicates Not Available 

326
Table 109. Negative binomial regression model estimation results for multiple-vehicle

crashes (all severities).

mv_all Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

ln_aadt 1.482 0.110 13.430 < 0.001 1.266 1.698

illinois 0.628 0.171 3.680 < 0.001 0.294 0.962

Lane10 0.769 0.470 1.640 0.102 -0.153 1.690

Lane11 0.199 0.306 0.650 0.515 -0.400 0.798

shoulder 0.007 0.040 0.160 0.872 -0.073 0.086

ln10shld -0.223 0.132 -1.690 0.092 -0.481 0.036

ln11shld -0.006 0.053 -0.110 0.910 -0.110 0.098

barrier 5.690 2.653 2.150 0.032 0.491 10.889

drvwy_den -0.002 0.012 -0.160 0.875 -0.024 0.021

solid_CL 0.422 0.343 1.230 0.218 -0.250 1.094

dash1_CL 0.641 0.542 1.180 0.237 -0.421 1.703

curve -0.013 0.126 -0.100 0.921 -0.259 0.234

_cons -13.401 0.909 -14.750 < 0.001 -15.182 -11.620

ln(Length) 1 (exposure) — — —

/lnalpha -1.1353 0.372991 — — -1.866348 -0.4042488

alpha 0.321326 0.119852 — — 0.1546876 0.667478

Log likelihood = -649.6117

Number of Observations = 877

LR chi2(12) = 213.52

Prob > chi2 = 0

Pseudo R2 = 0.1411

Likelihood-ratio test of alpha=0: chibar2(01) = 12.89 Prob>=chibar2 = 0.000

— Indicates Not Available

327
Table 110. Negative binomial regression model estimation results for key lane 

width/shoulder width crashes (all severities).

key_kabco Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

ln_aadt 0.606 0.059 10.27 < 0.001 0.490 0.721

illinois 1.083 0.099 10.98 < 0.001 0.890 1.277

Lane10 0.903 0.223 4.04 < 0.001 0.465 1.341

Lane11 0.519 0.161 3.23 0.001 0.205 0.834

shoulder -0.052 0.023 -2.26 0.024 -0.097 -0.007

ln10shld -0.076 0.056 -1.37 0.172 -0.185 0.033

ln11shld -0.060 0.030 -1.97 0.049 -0.119 0.000

barrier 4.305 1.888 2.28 0.023 0.604 8.006

drvwy_den 0.012 0.007 1.88 0.060 -0.001 0.025

solid_CL 0.471 0.209 2.26 0.024 0.062 0.880

dash1_CL 0.800 0.323 2.47 0.013 0.166 1.433

curve 0.231 0.074 3.14 0.002 0.087 0.376

_cons -4.613 0.466 -9.9 <0.001 -5.527 -3.700

ln(Length) 1 (exposure) — — —

/lnalpha -0.72081 0.102919 — — -0.92253 -0.5191

alpha 0.486356 0.050055 — — 0.397512 0.595057

Log likelihood = -1684.8577

Number of Observations = 877

LR chi2(12) = 395.990

Prob > chi2 = 0.000

Pseudo R2 = 0.105

Likelihood-ratio test of alpha=0: chibar2(01) = 395.21 Prob>=chibar2 = 0.000

— Indicates Not Available 

328
Table 111. Negative binomial regression model estimation results for single-vehicle crashes 

(fatal-plus-injury).

sv_fi Coefficient

Standard. 

Error z P > z

95-Percent Confidence 

Interval

ln_aadt 0.562 0.112 5.01 < 0.001 0.342 0.783

illinois 0.427 0.189 2.26 0.024 0.057 0.798

Lane10 -0.035 0.428 -0.08 0.935 -0.874 0.804

Lane11 0.193 0.305 0.63 0.528 -0.406 0.791

shoulder -0.116 0.045 -2.58 0.010 -0.203 -0.028

ln10shld 0.063 0.106 0.6 0.551 -0.144 0.271

ln11shld -0.023 0.061 -0.39 0.699 -0.142 0.095

barrier 0.576 3.244 0.18 0.859 -5.783 6.934

drvwy_den 0.007 0.013 0.590 0.553 -0.017 0.032

solid_CL 0.530 0.369 1.440 0.151 -0.194 1.253

dash1_CL 0.345 0.615 0.560 0.575 -0.860 1.550

curve 0.081 0.141 0.580 0.563 -0.194 0.357

_cons -5.385 0.882 -6.100 <0.001 -7.114 -3.656

ln(Length) 1 (exposure) — — —

/lnalpha -1.10368 0.491638 — — -2.06727 -0.1400852

alpha 0.331649 0.163051 — — 0.1265307 0.8692842

Log likelihood = -579.36383

Number of Observations = 877

LR chi2(12) = 64.28

Prob > chi2 = 0

Pseudo R2 = 0.0526

Likelihood-ratio test of alpha=0: chibar2(01) = 6.35 Prob>=chibar2 = 0.006

— Indicates Not Available

329
Table 112. Negative binomial regression model estimation results for multiple-vehicle

crashes (fatal-plus-injury).

mv_fi Coefficient

Standard 

Error z P > z

95-percent Confidence 

Interval

ln_aadt 1.142 0.162 7.060 < 0.001 0.825 1.459

illinois 0.557 0.248 2.240 0.025 0.071 1.043

Lane10 0.427 0.992 0.430 0.667 -1.517 2.371

Lane11 0.762 0.481 1.580 0.114 -0.182 1.705

shoulder 0.146 0.059 2.470 0.013 0.030 0.262

ln10shld -0.185 0.219 -0.840 0.398 -0.613 0.244

ln11shld -0.100 0.078 -1.290 0.196 -0.252 0.052

barrier 5.476 4.069 1.350 0.178 -2.498 13.450

drvwy_den -0.011 0.019 -0.570 0.570 -0.048 0.026

solid_CL 0.129 0.559 0.230 0.817 -0.966 1.225

dash1_CL 0.533 0.836 0.640 0.524 -1.106 2.173

curve 0.126 0.186 0.680 0.498 -0.238 0.490

_cons -12.279 1.343 -9.140 <0.001 -14.911 -9.646

ln(Length) 1 (exposure) — — —

/lnalpha -1.18079 0.886305 — — -2.917915 0.5563366

alpha 0.307036 0.272128 — — 0.0540463 1.744271

Log likelihood = -374.64352

Number of Observations = 877

LR chi2(12) = 79.46

Prob > chi2 = 0

Pseudo R2 = 0.0959

Likelihood-ratio test of alpha=0: chibar2(01) = 1.73 Prob>=chibar2 = 0.094

— Indicates Not Available

330
Table 113. Negative binomial regression model estimation results for key lanewidth/shoulder-width crashes (fatal-plus-injury).

key_kabc Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

ln_aadt 0.598 0.114 5.27 < 0.001 0.376 0.821

illinois 0.523 0.180 2.9 0.004 0.170 0.875

Lane10 0.080 0.458 0.17 0.862 -0.819 0.978

Lane11 0.552 0.319 1.73 0.084 -0.073 1.178

shoulder -0.070 0.044 -1.6 0.109 -0.155 0.015

ln10shld 0.068 0.105 0.65 0.518 -0.138 0.274

ln11shld -0.093 0.060 -1.55 0.121 -0.211 0.025

barrier 0.314 3.738 0.08 0.933 -7.014 7.641

drvwy_den 0.009 0.013 0.67 0.501 -0.017 0.034

solid_CL 0.288 0.397 0.72 0.469 -0.490 1.066

dash1_CL 0.416 0.629 0.66 0.508 -0.815 1.648

curve 0.034 0.147 0.23 0.818 -0.255 0.322

_cons -5.392 0.888 -6.07 <0.001 -7.132 -3.651

ln(Length) 1 (exposure) — — —

/lnalpha 0.481668 0.153744 — 0.180335 0.783001

alpha 1.618773 0.248877 — — 1.197619 2.18803

Log likelihood = -817.20472

Number of Observations = 877

LR chi2(12) = 66

Prob > chi2 = 0.0000

Pseudo R2 = 0.0388

Likelihood-ratio test of alpha=0: chibar2(01) = 144.74 Prob>=chibar2 = 0.000

— Indicates Not Available

331
Table 114. Negative binomial regression model estimation results for single-vehicle crashes 

(PDO).

sv_o Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

ln_aadt 0.515 0.065 7.9 < 0.001 0.387 0.643

illinois 1.307 0.117 11.17 < 0.001 1.077 1.536

Lane10 1.029 0.240 4.3 < 0.001 0.560 1.499

Lane11 0.427 0.175 2.44 0.015 0.083 0.770

shoulder -0.054 0.026 -2.04 0.041 -0.105 -0.002

ln10shld -0.113 0.064 -1.77 0.077 -0.238 0.012

ln11shld -0.031 0.034 -0.9 0.370 -0.097 0.036

barrier 4.386 1.928 2.27 0.023 0.606 8.166

drvwy_den 0.018 0.007 2.490 0.013 0.004 0.032

solid_CL 0.499 0.230 2.170 0.030 0.048 0.951

dash1_CL 1.031 0.356 2.900 0.004 0.333 1.728

curve 0.288 0.081 3.570 <0.001 0.130 0.447

_cons -4.589 0.519 -8.840 <0.001 -5.606 -3.572

ln(Length) 1 (exposure) — — —

/lnalpha -0.76859 0.121186 — — -1.006113 -0.5310743

alpha 0.463665 0.05619 — — 0.3656375 0.587973

Log likelihood = -1390.4041

Number of Observations = 877

LR chi2(12) = 397.58

Prob > chi2 = 0

Pseudo R2 = 0.1251

Likelihood-ratio test of alpha=0: chibar2(01) = 239.28 Prob>=chibar2 = 0.000

— Indicates Not Available

332
Table 115. Negative binomial regression model estimation results for multiple-vehicle

crashes (PDO).

mv_o Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

ln_aadt 1.727 0.144 12.010 < 0.001 1.445 2.009

illinois 0.671 0.222 3.020 0.003 0.236 1.105

Lane10 0.686 0.542 1.270 0.206 -0.376 1.749

Lane11 -0.198 0.383 -0.520 0.605 -0.948 0.552

shoulder -0.095 0.052 -1.810 0.071 -0.197 0.008

ln10shld -0.186 0.167 -1.120 0.264 -0.514 0.141

ln11shld 0.068 0.070 0.980 0.329 -0.069 0.205

barrier 5.742 3.298 1.740 0.082 -0.722 12.207

drvwy_den 0.004 0.014 0.290 0.775 -0.024 0.032

solid_CL 0.568 0.420 1.350 0.176 -0.254 1.391

dash1_CL 0.653 0.682 0.960 0.338 -0.684 1.991

curve -0.096 0.161 -0.590 0.552 -0.412 0.220

_cons -15.436 1.179 -13.090 <0.001 -17.747 -13.124

ln(Length) 1 (exposure) — — —

/lnalpha -0.79447 0.433001 — — -1.643133 0.0542011

alpha 0.451823 0.19564 — — 0.1933733 1.055697

Log likelihood = -469.42118

Number of Observations = 877

LR chi2(12) = 178.04

Prob > chi2 = 0

Pseudo R2 = 0.1594

Likelihood-ratio test of alpha=0: chibar2(01) = 9.54 Prob>=chibar2 = 0.001

— Indicates Not Available

333
Table 116. Negative binomial regression model estimation results for key lanewidth/shoulder-width crashes (PDO).

key_o Coefficient

Standard 

Error z P > z 95-Percent Confidence Interval

ln_aadt 0.615 0.066 9.37 < 0.001 0.486 0.743

illinois 1.276 0.113 11.25 < 0.001 1.054 1.498

Lane10 1.059 0.245 4.33 < 0.001 0.579 1.539

Lane11 0.494 0.177 2.8 0.005 0.148 0.841

shoulder -0.046 0.026 -1.8 0.072 -0.097 0.004

ln10shld -0.104 0.063 -1.67 0.096 -0.227 0.018

ln11shld -0.049 0.034 -1.45 0.147 -0.115 0.017

barrier 5.253 2.057 2.55 0.011 1.221 9.286

drvwy_den 0.013 0.007 1.85 0.065 -0.001 0.028

solid_CL 0.544 0.232 2.35 0.019 0.090 0.999

dash1_CL 0.913 0.358 2.55 0.011 0.211 1.614

curve 0.292 0.081 3.6 < 0.001 0.133 0.451

_cons -5.167 0.523 -9.88 < 0.001 -6.192 -4.141

ln(Length) 1 (exposure) — — —

/lnalpha -0.5778 0.107196 — — -0.7879 -0.3677

alpha 0.561129 0.060151 — — 0.454797 0.692322

Log likelihood = -1524.6018

Number of Observations = 877

LR chi2(12) = 391.03

Prob > chi2 = 0

Pseudo R2 = 0.1137

Likelihood-ratio test of alpha=0: chibar2(01) = 363.82 Prob>=chibar2 = 0.000

— Indicates Not Available

334
Table 117. Multinomial logit model estimation results for total crashes (all types and 

severities)—base outcome: PDO.

Severity Variable Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

0 (base outcome) — — — — — —

1

ln_aadt 0.103 0.190 0.540 0.588 -0.270 0.476

illinois -2.615 0.301 -8.700 0.000 -3.205 -2.026

Lane10 -0.993 0.914 -1.090 0.277 -2.784 0.797

Lane11 -0.125 0.546 -0.230 0.819 -1.195 0.945

shoulder -0.079 0.071 -1.110 0.267 -0.218 0.060

ln10shld 0.216 0.173 1.250 0.211 -0.123 0.555

ln11shld 0.023 0.088 0.260 0.797 -0.150 0.195

barrier -5.154 7.644 -0.670 0.500 -20.137 9.829

drvway_den -0.008 0.025 -0.330 0.739 -0.058 0.041

solid_CL -0.905 0.767 -1.180 0.238 -2.409 0.599

dash1_CL 0.857 1.031 0.830 0.406 -1.163 2.877

curve -0.377 0.237 -1.590 0.111 -0.842 0.087

_cons -1.450 1.448 -1.000 0.316 -4.288 1.387

2

ln_aadt 0.038 0.134 0.280 0.780 -0.226 0.301

illinois -0.007 0.257 -0.030 0.980 -0.511 0.498

Lane10 -1.107 0.630 -1.760 0.079 -2.341 0.127

Lane11 -0.172 0.368 -0.470 0.641 -0.893 0.550

shoulder 0.082 0.053 1.540 0.124 -0.023 0.186

ln10shld 0.133 0.152 0.880 0.380 -0.164 0.431

ln11shld -0.032 0.070 -0.450 0.650 -0.170 0.106

barrier 1.097 4.403 0.250 0.803 -7.532 9.726

drvway_den -0.022 0.017 -1.300 0.192 -0.054 0.011

solid_CL -0.331 0.495 -0.670 0.504 -1.301 0.639

dash1_CL -0.595 0.771 -0.770 0.441 -2.107 0.917

curve -0.218 0.168 -1.300 0.194 -0.547 0.111

_cons -2.529 1.099 -2.300 0.021 -4.683 -0.375

3

ln_aadt 0.257 0.168 1.530 0.126 -0.073 0.587

illinois 0.613 0.393 1.560 0.119 -0.157 1.383

Lane10 -0.057 0.693 -0.080 0.934 -1.416 1.302

Lane11 0.443 0.481 0.920 0.357 -0.500 1.386

shoulder 0.085 0.073 1.160 0.248 -0.059 0.229

ln10shld -0.069 0.215 -0.320 0.747 -0.491 0.352

ln11shld -0.097 0.096 -1.010 0.312 -0.284 0.091

barrier -1.734 5.888 -0.290 0.768 -13.273 9.806

drvway_den -0.022 0.019 -1.130 0.258 -0.060 0.016

solid_CL 0.884 0.485 1.820 0.068 -0.067 1.836

dash1_CL -1.950 1.012 -1.930 0.054 -3.934 0.034

curve 0.179 0.205 0.870 0.382 -0.222 0.580

_cons -5.679 1.441 -3.940 0.000 -8.503 -2.855

335
Severity Variable Coefficient

Standard 

Error z P > z

95-Percent Confidence 

Interval

4

ln_aadt 0.228 0.351 0.650 0.516 -0.460 0.917

illinois -0.130 0.700 -0.190 0.853 -1.501 1.242

Lane10 1.177 1.687 0.700 0.485 -2.129 4.484

Lane11 1.441 1.082 1.330 0.183 -0.681 3.562

shoulder 0.207 0.156 1.320 0.186 -0.099 0.513

ln10shld -0.671 0.962 -0.700 0.486 -2.557 1.216

ln11shld -0.211 0.189 -1.110 0.265 -0.581 0.160

barrier -3.203 12.442 -0.260 0.797 -27.589 21.183

drvway_den -0.054 0.050 -1.090 0.276 -0.152 0.043

solid_CL 0.672 1.006 0.670 0.504 -1.300 2.644

dash1_CL 0.528 1.968 0.270 0.788 -3.330 4.386

curve 0.403 0.425 0.950 0.343 -0.430 1.236

_cons -7.442 3.027 -2.460 0.014 -13.376 -1.508

Log likelihood = -1543.1747

Number of observation = 2397

LR chi2(48) = 198.440

Prob > chi2 = 0.000

Pseudo R2 = 0.060

— Indicates Not Available

336
Table 118. Multinomial logit model estimation results for fatal-plus-injury crashes (all 

types)—base outcome: possible injury.

severity_rev Variable Coefficient

Standard 

Error z P > z

95-Percent 

Confidence Interval

1 (base outcome) — — — — — —

2

ln_aadt -0.273 0.231 -1.180 0.237 -0.726 0.180

illinois 2.531 0.388 6.530 <0.001 1.771 3.290

Lane10 0.011 1.163 0.010 0.992 -2.267 2.290

Lane11 0.044 0.689 0.060 0.949 -1.305 1.394

shoulder 0.163 0.091 1.780 0.075 -0.016 0.342

ln10shld -0.191 0.250 -0.770 0.444 -0.682 0.299

ln11shld -0.063 0.118 -0.530 0.594 -0.294 0.168

barrier 10.549 9.177 1.150 0.250 -7.438 28.537

drvway_den -0.006 0.031 -0.200 0.840 -0.067 0.054

solid_CL 0.618 0.866 0.710 0.475 -1.079 2.316

dash1_CL -1.659 1.326 -1.250 0.211 -4.258 0.940

curve 0.147 0.304 0.490 0.627 -0.448 0.742

_cons 0.604 1.785 0.340 0.735 -2.895 4.103

3

ln_aadt -0.057 0.263 -0.220 0.829 -0.572 0.459

illinois 3.230 0.505 6.400 <0.001 2.240 4.220

Lane10 1.030 1.226 0.840 0.401 -1.372 3.432

Lane11 0.758 0.781 0.970 0.332 -0.773 2.289

shoulder 0.184 0.111 1.660 0.096 -0.033 0.401

ln10shld -0.389 0.299 -1.300 0.192 -0.974 0.196

ln11shld -0.155 0.141 -1.100 0.273 -0.432 0.122

barrier 7.135 10.398 0.690 0.493 -13.245 27.514

drvway_den -0.005 0.033 -0.150 0.884 -0.069 0.059

solid_CL 1.739 0.882 1.970 0.049 0.010 3.468

dash1_CL -3.028 1.529 -1.980 0.048 -6.025 -0.030

curve 0.542 0.336 1.610 0.107 -0.116 1.199

_cons -2.654 2.127 -1.250 0.212 -6.823 1.515

337
severity_rev Variable Coefficient

Standard 

Error z P > z

95-Percent 

Confidence Interval

4

ln_aadt -0.047 0.406 -0.120 0.907 -0.843 0.748

illinois 2.492 0.779 3.200 0.001 0.966 4.017

Lane10 2.603 2.183 1.190 0.233 -1.676 6.882

Lane11 1.840 1.247 1.480 0.140 -0.604 4.284

shoulder 0.310 0.178 1.740 0.082 -0.039 0.660

ln10shld -1.145 1.307 -0.880 0.381 -3.707 1.417

ln11shld -0.289 0.217 -1.330 0.183 -0.715 0.137

barrier 4.281 15.898 0.270 0.788 -26.879 35.442

drvway_den -0.041 0.057 -0.720 0.472 -0.152 0.070

solid_CL 1.370 1.227 1.120 0.264 -1.035 3.775

dash1_CL -0.305 2.244 -0.140 0.892 -4.702 4.092

curve 0.757 0.496 1.530 0.127 -0.216 1.730

_cons -4.744 3.408 -1.390 0.164 -11.423 1.936

Log likelihood = -464.69741

Number of Observations = 426

LR chi2(36) = 112.18

Prob > chi2 = 0

Pseudo R2 = 0.1077

— Indicates Not Available

338
ACKNOWLEDGMENTS

The authors thank the following agencies that volunteered and participated as pilot study 

locations for the HFST and OSB evaluations, as well as agency staff for their helpful input and 

support of the project:

SRPEDD

• Jim Hadfield, Transportation Planning Manager

• Lisa Estrela-Pedro, Principal Transportation Planner

• Jackie Schmidt, Senior Transportation Planner

MCPW

• Steven P. Latoski, Professional Engineer (P.E.), Professional Traffic Operations 

Engineer (PTOE), Director

• J.T. Casanova, Traffic Control

ALDOT

• Timothy E. Barnett, P.E., PTOE, State Safety Operations Engineer

• Stuart Manson, P.E., Safety Engineering Analyst

WVDOT

• Donna J Hardy, P.E., Safety Programs Engineer

• Tom Hammonds, HSIP Coordinator

• Kyle B. Hall, P.E., Construction Engineer, District 8

The authors also thank Yusuf Mohamedshah for providing crash data through the HSIS and for 

efficiently addressing a number of follow-up questions and requests related to the data.

339

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