Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

Photographic Data Extraction Feasibility

and Pilot Study in Support of Roadside

Safety and Roadway Departure Research

PUBLICATION NO. FHWA-HRT-13-088 MAY 2014
FOREWORD

The Federal Highway Administration (FHWA) has identified roadway departure as a focus area 

because roadway departure crashes consistently contribute to more than half of the fatal crashes 

on U.S. roadways. Access to relevant data is critical to understanding the causes of roadway 

departure and mitigating the consequences. This study seeks to maximize available vehicle and 

infrastructure crashworthiness data sources and repurpose them to answer questions of interest to 

FHWA, such as the identification of barrier types and end treatments subjected to specific crash 

conditions previously unreported in the crashworthiness datasets. 

This study is part of a series of low-cost in-house efforts to make full use of existing data 

resources to understand the roadway departure problem. Existing data will be extrapolated and 

interpolated to determine reliable results and identify missing data. This report represents an 

ongoing effort in roadway departure analysis.

Monique R. 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. 

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-13-088

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

4. Title and Subtitle

Photographic Data Extraction Feasibility and Pilot Study in Support of 

Roadside Safety and Roadway Departure Research

5. Report Date

May 2014

6. Performing Organization Code

HRDS-20

7. Author(s)

Ana Maria Eigen, D.Sc., Rafael Olarte Valdivieso, Ph.D., and 

Amir Ahrari, Ph.D.

8. Performing Organization Report No.

9. Performing Organization Name and Address

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101-2296

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

12 Sponsoring Agency Name and Address

Office of Safety Research and Development

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101-2296

13. Type of Report and Period Covered

Technical Report

14. Sponsoring Agency Code

15. Supplementary Notes

Special thanks to the Highway Safety Information System Laboratory, operated under Contract DTFH61-11- 

C-00050, for making the services of Dr. Olarte Valdivieso and Dr. Ahrari available for this study.

16. Abstract

This work represents the first phase of an ongoing low-cost in-house effort to perform data analysis, optimize 

internal data gathering in an informed fashion, make data requests to organizations, and obtain needed information. 

The work also calls on the definition of “roadway departure” prepared by a 2008 working group assembled by the 

Federal Highway Administration (FHWA) Office of Safety. The group provided a verbal and data definition in order

to extract data and relate the data to the fatal crash population.

Many applications exist for crashworthiness data and untapped resources from previously unqueried sources.(1) The 

FHWA roadway departure definition provided a Fatality Analysis Reporting System data approach; however, other 

National Highway Traffic Safety Administration datasets exist with real-time or near real-time data.

(2) One such 

dataset is the National Motor Vehicle Crash Causation Study (NMVCCS).

(3,4) The present work pursues 

photographic data extracted from the NMVCCS. This report provides further discussion regarding the surrogates 

adopted in framing roadway departure. 

17. Key Words

Roadway Departure, FARS, NASS CDS, GES, 

NMVCCS, Panoramic view software

18. Distribution Statement

No restrictions. This document is available to the public 

through the National Technical Information Service, 

Springfield, VA 22161

19. Security Classif.(of this report)

Unclassified

20. Security Classif.(of this page)

Unclassified

21. No. of Pages

71

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
* SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380.

(Revised March 2003)

SI* (MODERN METRIC) CONVERSION FACTORS 

APPROXIMATE CONVERSIONS TO SI UNITS

Symbol When You Know Multiply By To Find Symbol 

LENGTH 

in inches 25.4 millimeters mm 

ft feet 0.305 meters m 

yd yards 0.914 meters m 

mi miles 1.61 kilometers km 

AREA 

in2 square inches 645.2 square millimeters mm2

ft2 square feet 0.093 square meters m2

yd2 square yard 0.836 square meters m2

ac acres 0.405 hectares ha 

mi2 square miles 2.59 square kilometers km2

VOLUME 

fl oz fluid ounces 29.57 milliliters mL 

gal gallons 3.785 liters L 

ft3 cubic feet 0.028 cubic meters m3 

yd3 cubic yards 0.765 cubic meters m3 

NOTE: volumes greater than 1000 L shall be shown in m3

MASS oz ounces 28.35 grams g

lb pounds 0.454 kilograms kg

T short tons (2000 lb) 0.907 megagrams (or "metric ton") Mg (or "t") 

TEMPERATURE (exact degrees) o

F Fahrenheit 5 (F-32)/9 Celsius o

C 

or (F-32)/1.8 

ILLUMINATION 

fc foot-candles 10.76 lux lx 

fl foot-Lamberts 3.426 candela/m2 cd/m2

FORCE and PRESSURE or STRESS 

lbf poundforce 4.45 newtons N 

lbf/in2 poundforce per square inch 6.89 kilopascals kPa 

APPROXIMATE CONVERSIONS FROM SI UNITS 

Symbol When You Know Multiply By To Find Symbol 

LENGTH mm millimeters 0.039 inches in 

m meters 3.28 feet ft 

m meters 1.09 yards yd 

km kilometers 0.621 miles mi 

AREA mm2 square millimeters 0.0016 square inches in2 

m2 square meters 10.764 square feet ft2 

m2 square meters 1.195 square yards yd2 

ha hectares 2.47 acres ac 

km2 square kilometers 0.386 square miles mi2 

VOLUME 

mL milliliters 0.034 fluid ounces fl oz 

L liters 0.264 gallons gal 

m3 cubic meters 35.314 cubic feet ft3 

m3 cubic meters 1.307 cubic yards yd3 

MASS 

g grams 0.035 ounces oz

kg kilograms 2.202 pounds lb

Mg (or "t") megagrams (or "metric ton") 1.103 short tons (2000 lb) T 

TEMPERATURE (exact degrees) o

C Celsius 1.8C+32 Fahrenheit oF 

ILLUMINATION 

lx lux 0.0929 foot-candles fc 

cd/m2 candela/m2 0.2919 foot-Lamberts fl

FORCE and PRESSURE or STRESS 

N newtons 0.225 poundforce lbf 

kPa kilopascals 0.145 poundforce per square inch lbf/in2

 

 

ii
TABLE OF CONTENTS

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

BACKGROUND ..................................................................................................................... 1

OBJECTIVES ......................................................................................................................... 2

CHAPTER 2: RESULTS OF THE PHOTOGRAPHIC DATA EXTRACTION 

FEASIBILITY STUDY ................................................................................................................ 3

CANDIDATE DATASETS .................................................................................................... 3

OPERATIVE ASSUMPTIONS ............................................................................................. 4

EXAMPLES OF CANDIDATE CRASH SELECTION FINDINGS ................................. 4

FARS Dataset...................................................................................................................... 4

NMVCCS Dataset ............................................................................................................... 6

NASS CDS Dataset............................................................................................................. 6

FEASIBILITY STUDY DATASET SELECTION .............................................................. 7

FINDINGS OF THE FEASIBILITY STUDY ...................................................................... 9

CHAPTER 3: RESULTS OF THE PHOTOGRAPHIC DATA EXTRACTION 

FEASIBILITY PILOT STUDY ................................................................................................. 11

DESCRIPTIVE SUMMARY STATISTICS ...................................................................... 11

General Data Extraction Process ...................................................................................... 11

Variables and Attributes ................................................................................................... 12

SUMMARY STATISTICS ................................................................................................... 18

PHOTOGRAPHIC EXAMPLES ........................................................................................ 19

Typical Case...................................................................................................................... 20

Examples of Other Road Elements Presented in the Crash Cases .................................... 23

Challenging Aspects ......................................................................................................... 25

DISCUSSION ........................................................................................................................ 28

Data Enhancements Sought .............................................................................................. 29

Future Refinements ........................................................................................................... 30

CHAPTER 4: FUTURE CONSIDERATION AND PILOT STUDY 

SUMMARIZATION ................................................................................................................... 31

FUTURE REVIEWS: IMPACT AND LIMITATIONS ................................................... 31

FARS Crashes ................................................................................................................... 31

NASS CDS Dataset........................................................................................................... 31

NMVCCS Dataset ............................................................................................................. 31

Data Collection via Photographic Reviews ...................................................................... 32

Future Technologies.......................................................................................................... 32

Planned Future Activities .................................................................................................. 32

PILOT STUDY SUMMARIZATION ................................................................................. 32

Findings of the Photographic Data Extraction Feasibility Study...................................... 33

Findings of the Photographic Data Extraction Pilot Study To Date ................................. 33

Recommendations for the Future of the Photographic Data Extraction Efforts ............... 33

APPENDIX A: PHOTOGRAPHIC CATALOG OF ROADSIDE ELEMENTS ................. 35

APPENDIX B: DATA EXTRACTION SPREADSHEET ...................................................... 47

APPENDIX C: COMPLETE SUMMARY STATISTICS ...................................................... 51

iii
ACKNOWLEDGEMENTS ....................................................................................................... 57

REFERENCES ............................................................................................................................ 59

BIBLIOGRAPHY ....................................................................................................................... 63

iv
LIST OF FIGURES

Figure 1. Illustration. FARS data acquisition example showing possible vehicle trajectory ......... 5

Figure 2. Illustration. NMVCCS photographic data acquisition example ...................................... 6

Figure 3. Illustration. NASS CDS data acquisition example showing damaged roadside 

elements (left, W-beam strong post) and vehicle damage (center, back/left oblique and right, 

front with measurement rods) ......................................................................................................... 7

Figure 4. Graph. Attributes observed in the roadway to paved shoulder drop-off variable ......... 18

Figure 5. Graph. Attributes observed in the roadway pavement type variable ............................. 18

Figure 6. Graph. Attributes observed in the location of the first compromised barrier variable .. 19

Figure 7. Graph. Attributes observed in the barrier post material variable .................................. 19

Figure 8. Photo. First view of Case No. 2005079486822 showing the point of impact ............... 21

Figure 9. Photo. Second view of Case No. 2005079486822 showing the point of impact .......... 21

Figure 10. Photo. Case No. 2005079486822 look back from point of impact ............................. 22

Figure 11. Photo. Case No. 2005049602183 post-crash W-beam strong post (left) contrasted 

with comparative catalog image (right) ........................................................................................ 23

Figure 12. Photo. Case No. 2005049602183 post-crash W-beam strong post highlighting 

energy absorbing end treatment .................................................................................................... 24

Figure 13. Photo. Case No. 2005049602403 post-crash high-tension cable guardrail systems 

(left) contrasted with comparative catalog image (right) .............................................................. 24

Figure 14. Photo. Case No. 2005012696122 post-crash Thrie beam strong post (left) 

contrasted with comparative catalog image (right) ....................................................................... 24

Figure 15. Photo. Case No. 2005012696122 post-crash Thrie beam strong post (left) 

highlighting non-energy absorbing slotted rail terminal contrasted with comparative 

catalog image (right) ..................................................................................................................... 25

Figure 16. Photo. Case No. 2005082626081 post-crash impact attenuator (left) in advance 

of W-beam strong post (center) contrasted with comparative catalog image (right) ................... 25

Figure 17. Photo. Photograph 1 used for identifying macrotexture in Case No. 

2005012695244............................................................................................................................. 26

Figure 18. Photo. Photograph 2 used for identifying macrotexture in Case No. 

2005012695244............................................................................................................................. 26

Figure 19. Photo. Photograph 3 used for identifying macrotexture in Case No. 

2005012695244............................................................................................................................. 26

Figure 20. Photo. Photograph 1 used for identifying macrotexture in Case No. 

2007075702347............................................................................................................................. 27

Figure 21. Photo. Photograph 2 used for identifying macrotexture in Case No. 

2007075702347............................................................................................................................. 27

Figure 22. Photo. Photograph used for identifying rutting in Case No. 2007075702347 ............ 28

Figure 23. Photo. Photograph from Case No. 2005073438121 in which measurements 

were obtained using rods .............................................................................................................. 28

Figure 24. Photo. Barrier type 1—aesthetic timber barrier/wood guardrail ................................. 35 

Figure 25. Photo. Second image of barrier type 1—aesthetic timber barrier/wood guardrail ...... 35 

Figure 26. Photo. Barrier type 2—box beam ................................................................................ 36

Figure 27. Photo. Barrier type 3—bridge rail ............................................................................... 36

Figure 28. Photo. Second image of barrier type 3—bridge rail .................................................... 36

Figure 29. Photo. Third image of barrier type 3—bridge rail ....................................................... 37

v 
Figure 30. Illustration. Barrier type 4—constant slope barrier ..................................................... 37

Figure 31. Photo. Barrier type 5—F-shaped barrier ..................................................................... 37

Figure 32. Photo. Barrier type 7—high-tension cable guardrail system....................................... 38

Figure 33. Photo. Barrier type 8—Jersey barrier .......................................................................... 38

Figure 34. Photo. Second image of barrier type 8—Jersey barrier ............................................... 38

Figure 35. Photo. Barrier type 9—low-tension cable guardrail .................................................... 39

Figure 36. Photo. Barrier type 10—median barrier steel guardrail .............................................. 39

Figure 37. Photo. Barrier type 11—median strip .......................................................................... 39

Figure 38. Photo. Barrier type 12—steel-backed timber guardrail ............................................... 40

Figure 39. Photo. Barrier type 13—Thrie beam ........................................................................... 40

Figure 40. Photo. Barrier type 14—Thrie beam strong post......................................................... 40

Figure 41. Photo. Barrier type 15—W-beam strong post ............................................................. 41

Figure 42. Photo. Barrier type 16—W-beam weak post ............................................................... 41

Figure 43. Photo. Barrier type 17—weak post box beam ............................................................. 41

Figure 44. Photo. Barrier type 18—weathering steel (Corten®) guardrail ................................... 41

Figure 45. Photo. Barrier type 19—impact attenuator .................................................................. 42

Figure 46. Photo. Second image of barrier type 19—impact attenuator ...................................... 42

Figure 47. Photo. Third image of barrier type 19—impact attenuator ......................................... 42

Figure 48. Photo. Fourth image of barrier type 19—impact attenuator ........................................ 43

Figure 49. Photo. Barrier end treatment type 1—bull nose end treatment ................................... 43

Figure 50. Photo. Barrier end treatment type 2—guardrail bridge attachment ............................ 43

Figure 51. Photo. Barrier end treatment type 3—rock fence ........................................................ 44

Figure 52. Photo. Barrier end treatment type 4—rounded terminal buffer (“question mark”) .... 44

Figure 53. Photo. Barrier end treatment type 6— “turndown” roll-over end section ................... 44

Figure 54. Photo. Barrier end treatment type 7—terminal end sections (boxing glove) .............. 45

Figure 55. Photo. Barrier end treatment type 8—Thrie beam terminal connector shoe 

(“end shoe”) .................................................................................................................................. 45

Figure 56. Photo. Barrier end treatment type 10—W-beam terminal connector shoe ................. 45

Figure 57. Photo. Barrier end treatment type 12—impact attenuators ......................................... 45

Figure 58. Photo. Barrier end treatment type 12—temporary impact attenuators ........................ 46

Figure 59. Illustration. Spreadsheet employed for data extraction (first 15 columns) ................. 48

Figure 60. Illustration. Spreadsheet employed for data extraction (last 18 columns) .................. 49

vi 
LIST OF TABLES

Table 1. Traditional and supplemental data acquisition approaches .............................................. 2

Table 2. Extraction of photographic data by dataset....................................................................... 4

Table 3. FARS crash panoramic view image classification ........................................................... 8

Table 4. FARS candidate crashes by frequency and usability ........................................................ 8

Table 5. NMVCCS candidate crashes by frequency and usability ................................................. 9

Table 6. Supplementary variables and their attributes .................................................................. 12

Table 7. Identification of road elements in some cases ................................................................ 23

Table 8. Reported precipitation..................................................................................................... 51

Table 9. Location of the first shoulder involved ........................................................................... 51

Table 10. Representative paved shoulder width ........................................................................... 51

Table 11. Representative unpaved shoulder width ....................................................................... 51

Table 12. Major variations in paved shoulder width .................................................................... 52

Table 13. Major variations in unpaved shoulder width ................................................................ 52

Table 14. Roadway to paved shoulder drop-off............................................................................ 52

Table 15. Presence of rumble strips .............................................................................................. 52

Table 16. Roadway pavement type ............................................................................................... 52

Table 17. Pavement marking quality ............................................................................................ 53

Table 18. Location of the first compromised barrier .................................................................... 53

Table 19. Barrier type ................................................................................................................... 53

Table 20. Barrier end treatment type ............................................................................................ 54

Table 21. Barrier post material ..................................................................................................... 54

Table 22. Barrier block-out material ............................................................................................. 54

Table 23. Location of crash with respect to barrier ...................................................................... 54

Table 24. Location of crash with respect to guardrail .................................................................. 55

Table 25. Barrier condition ........................................................................................................... 55

vii 
LIST OF ABBREVIATIONS 

CDS Crashworthiness Data System

EAR Exploratory Advanced Research

FARS Fatality Analysis Reporting System

FHWA Federal Highway Administration 

GM® General Motors®

HBA Hinged breakaway

LBSS Longitudinal Barrier Special Study 

NASS National Automotive Sampling System

NCHRP National Cooperative Highway Research Program

NHTSA National Highway Traffic Safety Administration

NMVCCS National Motor Vehicle Crash Causation Study 

SGT Single guardrail terminal

SKT Sequential kinking terminal 

TAS Terminal anchor section 

viii
CHAPTER 1: INTRODUCTION

BACKGROUND

The research team undertook the photographic data extraction pilot study in response to the 2008 

revision of the Fatality Analysis Reporting System (FARS), releasing geographical positioning 

system coordinates.

(2) Subsequently, the National Highway Traffic Safety Administration

(NHTSA) released the geographical coordinates for previous crash years in an independent file 

format for 1999 and 2000 and revision of the FARS files from 2001 through 2007. Using the 

Federal Highway Administration (FHWA) roadway departure definition to filter crashes of 

interest, events involving guardrails, concrete barriers, and impact attenuators were reviewed

from 2004 to 2009.(5) From the pilot study, it was determined that barrier type and placement 

might provide useful information at low acquisition costs. The missing element, however, was 

post-crash condition. To obtain that information, it was necessary to review on-scene crash data.

The current study considered the on-scene photography captured through the National Motor 

Vehicle Crash Causation Study (NMVCCS).(4) NMVCCS was a congressionally mandated 

special study compiled under the National Automotive Sampling System (NASS) architecture

from 2005 through 2007, with a primary objective to provide pre-crash and crash 

causation information.(3,4)

In 2008, the NASS Crashworthiness Data System (CDS), providing a sample of tow-away 

crashes occurring on public roadways in the United States, showed marked improvement in 

roadside crash photography, possibly modeled after NMVCCS photography.(6) Data collection 

for these crashes, however, continued to be near-crash time, with NASS researchers arriving to 

the crash scene within days or weeks. Prior NASS CDS efforts included the 1982 Longitudinal 

Barrier Special Study (LBSS), which was a collaborative effort with NHTSA.

(7) However, the 

photographs and crash data were filed in paper medium and electronic records unavailable to 

FHWA. To date, no NHTSA crashworthiness dataset has provided a suitable level of coded 

roadway environment data for FHWA analysis. 

This study sought to complement the coded datasets by extracting new information from 

photographic images. NMVCCS data were selected owing to their temporal association with the 

crash and quality of photographs taken. Further, the pilot study initially attempted to classify 

the types of barriers involved, but the lack of temporal association limited the data extraction 

to an inventory confirming coded FARS attributes. The ability for researchers to assess the 

types of damage was considered useful as data inputs for future modeling tasks, thereby 

validating the immediate use of NMVCCS to feed the codification of a supplementary 

roadside element dataset.

National Cooperative Highway Research Program (NCHRP) projects have used photographic 

analysis to expand the understanding of uncoded elements, specifically NCHRP projects 17-11, 

17-22, and 22-15.(8–10) NCHRP projects 17-11 and 17-22 sought to identify impact conditions for 

run-off-road crashes, while project 22-15 considered the compatibility of the vehicle fleet with 

existing barrier types. The three studies compiled previously unavailable data from photographs 

and synthesized relevant test and real-world data. 

1 
Table 1 summarizes the means of harmonizing the coded and uncoded data. Historically, 

two broad types of data have existed: basic and crash. Basic data provided basic vehicle 

characteristics (e.g., make, model, and assessment of components) and occupant demography 

(e.g., observational and hospital discharge data). Crash data have generally provided 

post-crash vehicle disposition (e.g., tow away status and full deformation measurements) 

and geographical location (e.g., explicitly stated or sanitized scene photographs absent of 

geographical location information serving as a surrogate). Codified details have depended on the 

collection mandate of the dataset. It has been understood that in the absence of naturalistic data on 

each crash occurring, precise vehicle trajectory will be unavailable. However, the identification 

of roadside elements and descriptions of roadside environment have been available in crash 

photographs for several years. Currently, photographic data extraction is a labor-intensive task; 

however, in the future, roadside element extraction might benefit from automated data extraction 

based on the work of the FHWA Exploratory Advanced Research (EAR) Program. 

Table 1. Traditional and supplemental data acquisition approaches. 

Data Type

Data Elements

Codified Unavailable

Uncodified 

Photographic

Basic

Basic vehicle data

Basic occupant 

demography

Crash

General vehicle 

contacts

Precise vehicle 

trajectory

Specific type of 

element

Geographical location Roadway and

roadside description

Note: Blank cells indicate data elements outside the scope of the data types.

The authors of this report advocate additional roadside element acquisition from the NMVCCS 

dataset. For FARS, a means of digitally extracting roadside element information from panoramic 

view software images is being assessed separately in tandem with findings of concurrent and 

related EAR projects. If NMVCCS and FARS data extraction methodologies are found to be 

acceptable for safety research, then a combination of these techniques will be applied to extract 

data from NASS CDS images.

OBJECTIVES

This study seeks to enhance the understanding of roadway element data from collected but 

uncodified information. This report seeks to perform the following tasks: 

• Outline the findings of the photographic data extraction feasibility study. 

• Describe the findings of the photographic data extraction pilot study to date. 

• Provide recommendations for future photographic data extraction efforts. 

2 
CHAPTER 2: RESULTS OF THE PHOTOGRAPHIC DATA EXTRACTION 

FEASIBILITY STUDY

Geographical coordinates found in FARS are a valuable resource to the roadside safety 

researcher. The limited roadway environment data were able to be assessed using panoramic 

view software, which provided an image of the crash scene according to geographical 

coordinates. Although the crash scene images were temporally discontinuous, they provided 

insight into the type and placement of the barrier cited in the crash data.

Traditional data acquisition has been inadequate to address the needs of FHWA. The 

photographic analysis sought to enhance the few relevant coded variables and limited attributes 

for those variables. However, issues exist in photographic analysis, such as unknown crash 

locations and inconsistent levels of detail, which require the activation of several 

operative assumptions. 

CANDIDATE DATASETS

During the course of the pilot study, the researchers considered all relevant NHTSA datasets for 

supplementary data acquisition. FARS provided secondary access to crash scene images. The 

geographical coordinates were supplied to third-party panoramic view software, yielding images 

that were temporally discontinuous with the crash. NASS CDS provided near-crash time 

photographs, while NMVCCS provided on-scene crash photography. 

The research team summarized the process for data filtering, photographic capture, and possible 

data codification parameters in table 2. The principal difference in filtering rested with the 

FHWA roadway departure definition applicable only to FARS. Owing to privacy protocol 

observed in NASS CDS and NMVCCS, variables and attributes necessary to apply the roadway 

departure definition were not reported. As a surrogate for the proper roadway departure 

definition, impacts occurring in the first event involving guardrails, concrete barriers, and impact 

attenuators were accepted as quasi-roadway departure crashes. FARS required a two-step process 

for extracting the geographical coordinates from the data files and then inputting the coordinates 

into panoramic view software to observe the crash location during some point in time not 

coinciding with the crash. NMVCCS provided the photographs linking the vehicle to the crash 

scene and final disposition, suggesting trajectory after impacting the roadside element. Finally, 

NASS CDS provided crash location photographs within days or weeks of the crash as well as 

post-crash vehicle conditions for vehicles accessible at the tow yard.

3 
Table 2. Extraction of photographic data by dataset. 

Dataset Relevant Attributes Parameters of Extracted Data

FARS Temporally non-concurrent first 

event roadway departure

• Panoramic view software interface

• Crash location

NVMCCS On-scene first event roadside 

element impact

• Post-crash

• Vehicle final rest serving as

geographical coordinate surrogate

NASS CDS Near crash time first event roadside 

element impact

• Days or weeks after crash

• Crash location images serving as 

geographical coordinate surrogate

• Vehicle towed from scene

OPERATIVE ASSUMPTIONS 

For the initial review of FARS images, the research team adopted the following assumptions to 

facilitate image review: 

• If the image pre-dated the crash, the barrier would be the one found at the time of 

the crash.

• If the image was taken after the crash, the barrier would have been replaced with a 

similar barrier. 

• In obvious cases of miscoded geographical coordinates, the following hierarchy would be 

applied to ascertain the crash location: 

1. Review of all vehicle crash events by scrolling along roadway segments. 

2. Consult street, cross street, and mile post information, especially in the case 

of elevation. 

EXAMPLES OF CANDIDATE CRASH SELECTION FINDINGS

The research team filtered FARS, NASS CDS, and NMVCCS to compile a roadway departure 

dataset. They also entered the geographical coordinates into panoramic view software while 

using crash scene photographs as geographical coordinate surrogates for the datasets governed 

by privacy protocols. 

FARS Dataset

With the publication of geographical coordinates in 2008 and retroactive provision for prior 

crash years by NHTSA, possible crash trajectories could be conceived. Starting in 2004, FARS 

started to disaggregate the crash into vehicle event units, which was previously only done in 

NASS CDS.(6,11) With the coded vehicle events and the crash locations, it became possible for 

researchers to envision at least one crash trajectory, whereas previously, the crash scene was 

unknown to data analysts.

4 
Figure 1 provides one possibility with respect to crash progression. From similar images, it 

became possible for practitioners and researchers to have a discussion relevant to roadway 

vernacular. For example, a police accident report may cite the involvement of a ditch, but a 

roadway designer may have posited the presence of an embankment. Additionally, questions 

with the coded data existed regarding the application of a jackknife condition to a pickup truck. 

Unknowns also existed, with respect to the precise location of impact and Terhune scale 

rollover classification, but the general environment in which the vehicle was operating was 

better described. 

Original image: ©Google Earth®. (See Acknowledgements section for trajectory overlay.)

Figure 1. Illustration. FARS data acquisition example showing possible vehicle 

trajectory.

(2,12)

LATITUDE +46.0647

LONGITUDE-112.773

1

3

Vehicle 

Event Attribute

1 Guardrail Face

2 Jackknife*

3 Bridge Rail

4 Overturn

5 Veh Airborne

6 Ditch**

5

2*

4

Ford F

Rollover Crash

-Series Pickup ?

Vehicle Fatalities, 2

5 
NMVCCS Dataset 

Although NHTSA did not provide geographical coordinates in the NMVCCS dataset, the 

on-scene photography generally superseded the need for such flexibility, as seen in figure 2. 

Generally, from using one photograph, researchers were able to extract information relevant 

to the vehicle final disposition, vehicle damage, and roadside element damage. From this 

information, it was possible to postulate the path and interactions leading to post-crash vehicle

final resting position. As the photographs were taken on scene, the roadside damage, if present, 

was readily evident and could be linked to specific coded elements like vehicle paint color and 

paint transfers to the roadside element. An additional boon to the study was the presence of 

measurement rods, which were used previously in NASS CDS to quantify vehicle damage. In 

NMVCCS, the measurement rods were used to highlight elements in photographs and

unintentionally provided the barrier height, damage height, and damage width. This emphasis 

had a secondary effect of providing much needed roadside element measurement details. As this 

was not mandated in the NMVCCS photography protocols, these measurements were available 

inconsistently throughout the dataset. The other available attribute was the damage to the 

barrier and its components, seen visually and generally created by those unaware of roadside 

design precepts. 

Figure 2. Illustration. NMVCCS photographic data acquisition example.(1,4)

NASS CDS Dataset 

NASS CDS data were the final dataset considered.(6,11)

 The photographic image capture had the 

unintended benefit of improvement after the publication of the NMVCCS data. NASS CDS 

images before NMVCCS focused on the vehicle and the occupant interaction with the vehicle, 

but after the on-scene NMVCCS experience, the crash environment images improved markedly 

Improved coding and photographic 

substantiation with regard to paint transfer 

and vehicle interactions with barrier

Supplemental detail to coding with 

regard to barrier type & 

installation features (e.g., height) 

“The Role of a National Motor Vehicle Crash Causation

Study-Style Dataset in Analysis of Rollover Crashes “ (Eigen, 2010)

Example 1 Example 2

~ 70 cm

~ 35 cm

6 
from an FHWA perspective. Although the photographs were taken within days or weeks of the 

crash, a benefit existed in knowing the precise crash location. Based on the vehicle events 

recorded, the crash location and vehicle damage photographs might provide information relevant 

to possible trajectory.

NASS CDS photographic analysis required a two-step process to understand the crash scene 

and infrastructure as well as the vehicle damage and its possible interaction with the roadside 

environment. Most vehicles carried quantitative damage measurements conforming to Society of 

Automotive Engineering standards. These were also the same type of measurement rods that 

were repurposed in the NMVCCS dataset.

Figure 3 provides a summary of data relevant to the roadside element study extracted from 

NASS CDS Case 2007-09-013.(6) The left image provides the roadside element, the deformed 

metal guardrail. The vehicle damage can be discerned from the center and right images. In this 

case, the front of the vehicle made contact with the barrier, followed by a subsequent impact with 

the barrier, culminating in a one-quarter turn driver-side rollover. The rollover was identified as a 

climb-over probably associated with the guardrail damage shown in the left image. In this case, 

the vehicle scaled the barrier, causing the vehicle to roll to the opposite side of the barrier. 

Figure 3. Illustration. NASS CDS data acquisition example showing damaged roadside 

elements (left, W-beam strong post) and vehicle damage (center, back/left oblique and 

right, front with measurement rods).

(6)

FEASIBILITY STUDY DATASET SELECTION

FARS was the first dataset considered because the availability of geographical coordinates 

allowed for a wide range of panoramic view image options. 

FHWA has been a limited user of the NHTSA dataset, especially in problem identification, as in 

the case of the roadway departure data definition.

(5) Details relevant to developing crash testing 

protocols and roadside design parameters have been unavailable. It is believed that at minimum, 

the photographic data might provide valuable modeling inputs associated with different crash 

types. The supplemental data acquisition was developed based on the initial inventory style 

identification through FARS and was refined to include roadside element damage, vehicle 

damage, and vehicle trajectory.

For purposes of this current study, FARS and NMVCCS crashes were selected for consideration

from a pool of crashes filtered using the FHWA roadway departure definition for FARS and the 

first event roadside element impact surrogate for NMVCCS. The images were reviewed per 

7 
table 3. The case review process was outlined in Leveraging New Technologies to Capture 

Infrastructure Data to Supplement Roadside Crash Analyses.(13)

Table 3. FARS crash panoramic view image classification. 

Major Classification

Rubric Photographic Classification

Generally useable Accurate identification

Possible supplementation to accurately coded data

Possibly useable Absence of elevation data

Contact found at proximate geographical coordinates

Miscoded Attribute absent from geographical coordinates image

Coded misidentification

External to codification Geographical location could not be resolved

Unresolved photographic quality

Missing data Coordinates not provided

The FARS photographs fell into five major classification rubrics, translating into the 

photographic classification (see table 3). Upon reviewing the NMVCCS crashes, these were 

further simplified into a color usability classification system (green, yellow, and red). 

The FARS green category included the generally useable classification, the yellow category

contained the possibly useable classification, and the red category comprised the remaining 

rubrics (see table 4). Additionally, green was merited if the coded roadway element was 

confirmed by crash scene image, with at least one scenario emerging for modeling. Yellow was 

assigned if the coded roadway element was confirmed at proximate coordinates or confirmed by 

traffic way identifiers permitting the update of a coded roadway element, thereby improving the 

roadside element description based on coded location information or suggesting at least one 

scenario for modeling. Finally, red was assigned if geographical coordinates were unpublished, 

images were overexposed, or the street view was unavailable, as in the case of international 

border crossings. 

Table 4. FARS candidate crashes by frequency and usability. 

Usability 

Classification

FARS Usability by:

2004 2005 2006 2007 2008 2009 Classification Acceptability

Green 131 90 66 57 55 36 53 percent 71 percent Yellow 12 25 32 25 22 30 18 percent

Red 61 38 35 30 46 26 29 percent

Note: The blank cell indicates that the data were deemed unusable.

The same categories were applied when assessing NMVCCS crashes (see table 5). It was found 

that 71 percent of the first event roadway departure FARS crashes were classified as green and 

yellow collectively (table 4), and 100 percent of the NMVCCS crashes were classified as green 

(table 5). The FARS green and yellow aggregation and the NMVCCS green crashes were 

deemed suitable for consideration in the photographic data extraction pilot study as candidate 

results for the supplementary dataset. 

8 
Table 5. NMVCCS candidate crashes by frequency and usability. 

Usability 

Classification

NMVCCS Usability by:

2004 2005 2006 2007 2008 2009 Classification Acceptability

Green 0 101 139 147 0 0 100 percent 100 percent

Yellow 0 0 0 0 0 0 0 percent

Red 0 0 0 0 0 0 0 percent

Note: Blank cells indicate absence of cases. No cases were classified as yellow or red. 

FINDINGS OF THE FEASIBILITY STUDY

The goal of this study was to confirm the presence of coded roadside elements and determine 

their placement. It provided greater detail for the limited coded attributes, including uncoded 

roadside element type, and related them to the coded crash events. Finally, it provided insight 

into uncoded data with external images with full panoramic scene views for crashes with 

geographical location as well as NHTSA images with damage detail as a surrogate for datasets 

disallowing the provision of precise crash scene locations. These findings suggested the efficacy 

of the feasibility study and warranted continuation in the form of a pilot study. 

9 

CHAPTER 3: RESULTS OF THE PHOTOGRAPHIC DATA EXTRACTION 

FEASIBILITY PILOT STUDY

DESCRIPTIVE SUMMARY STATISTICS

For each case, through visual observation of the photographs, different pieces of information 

were collected and stored as variables. This section provides the general procedure of how these 

variables were collected and a brief explanation of the variables used. It also provides some 

statistics that summarize the data collected in those variables. 

General Data Extraction Process

The NMVCCS database groups all of its information by crash case. Each crash case has a 

narrative that explains how the crash happened and its possible causes. The analyst must review 

this narrative and answer the following questions to obtain a general idea of how the crash

happened: 

• If several vehicles experienced any type of collision, which vehicle was the first to 

present abnormal behavior (such as skidding, departing abruptly from its lane, etc.)? 

(The answer indicates the vehicle that will be selected for consideration in the analysis.) 

• In which direction was the vehicle driving and on which part of the roadway? 

• Did the vehicle depart from the roadway and run into a shoulder or barrier? (If this is the 

case, the analyst only considers the first time this event happens and on which side of the 

road (left or right).) 

• Were there one or several physical elements on the roadway that were presumed to be 

factors in the occurrence of the crash? 

• What were precipitation conditions at the moment of the crash? 

The second and third questions are especially important to understand the location of the barrier 

and the shoulder that might have been involved in the crash. The location information is stored 

as variables, allowing readers to better understand how the crash happened by just consulting the 

information from the variables. 

After answering the questions, the analyst must observe the crash photographs and try to draw all 

the necessary information from the photographs. The fourth question helps the analyst avoid 

missing other important aspects in the road. With this help and with an element of discretion, the 

analyst assumes that most of the characteristics of the roadway that appear in the photographs, 

such as contamination and surface anomalies, should be stored in the variables. 

The fifth question is directly stored in the variables. There is a variable labeled “Reported 

Precipitation” that is used to indicate the precipitation conditions at the moment of the crash. 

11 
Lastly, the analyst must determine if the photograph was taken at the moment of the crash or 

after the crash. Information such as contamination and the damage caused to the road should 

only be used from photographs taken at the moment of the crash. However, geometric 

characteristics can be obtained from photographs that happened after the crash. While 

NMVCCS provides some indication on when the photograph was taken, the analyst must make 

that determination, either on-scene or sometime after the crash. Although NMVCCS was 

conceived as on-scene data, some crash scenes might have been complicated by roadway traffic, 

in the absence of closure, limited closure time, or some such access impediment. In these cases, 

the researcher might have opted to review less time-critical aspects of the crash scene within 

hours of the crash once crash victims had been transported and vehicles towed from scene.

After following the approach, the analyst must describe the crash using the elements in table 6

and store the corresponding information.

Variables and Attributes

The variables used to capture the information are classified into four groups according to what 

part of the road they describe: shoulder; roadway, barrier, and precipitation. They can also be 

classified into four groups according to the type of technical expertise needed to identify the 

information: pavement characteristics and contamination, geometric characteristics, damage 

caused, and precipitation. Most of the variables contain information associated to pre-specified 

attributes. The variables are explained in table 6. 

Table 6. Supplementary variables and their attributes. 

Part of the 

Road 

Described

Type of 

Information # Variable Attributes Observations

Shoulder

Geometry and 

physical 

elements

1 Location of the 

first shoulder 

involved

• No shoulder involved.

• Left side of road. 

• Right side of road. 

• Other. 

• Unknown.

“No shoulder involved” indicates 

that either the road has no shoulders 

or the vehicle did not leave the 

roadway during the crash.

2 Representative 

paved shoulder 

width

• No shoulder involved.

• No paved shoulder. 

• Less than 4 ft. 

• 4 to 8 ft. 

• More than 8 ft. 

• Indistinguishable from photos. 

• Unknown location of first

shoulder involved.

The observation of the first variable 

also applies here. “Unknown 

location of first shoulder involved” 

should be selected if the value of the 

first variable is unknown.

3 Representative 

unpaved shoulder 

width

• No shoulder involved.

• No unpaved shoulder. 

• Less than 4 ft. 

• 4 to 8 ft. 

• More than 8 ft. 

• Indistinguishable from photos. 

• Unknown location of first

shoulder involved.

The observations of the first and 

second variables apply here.

12 
Part of the 

Road 

Described

Type of 

Information # Variable Attributes Observations

4 Major variations 

in paved shoulder 

width

• No shoulder involved.

• No paved shoulder. 

• Yes. 

• No. 

• Indistinguishable from photos or 

other sources. 

• Unknown location of first

shoulder involved.

If the length in the second variable 

varies significantly, then the 

attribute “yes” should be selected 

here. The observations of the first 

and second variables apply here.

5 Major variations 

in unpaved 

shoulder width

• No shoulder involved.

• No unpaved shoulder. 

• Yes. 

• No. 

• Indistinguishable from photos or 

other sources. 

• Unknown location of first

shoulder involved.

If the length in the third variable 

varies significantly, then the 

attribute “yes” should be selected 

here. The observations of the first 

and second variables apply here.

6 Roadway to 

paved shoulder 

drop-off

• No shoulder involved.

• No paved shoulder. 

• Yes. 

• No. 

• Indistinguishable from photos. 

• Unknown location of first

shoulder involved.

The observations of the first and 

second variables apply here.

7 Presence of 

rumble strips

• No shoulder involved.

• No paved shoulder. 

• Yes. 

• No. 

• Indistinguishable from photos. 

• Unknown location of first

shoulder involved.

The observations of the first and 

second variables apply here.

Pavement 

properties and 

contamination

8 Paved shoulder 

contamination

• No shoulder involved.

• No paved shoulder. 

• Ice or slush. 

• Snow. 

• Mud. 

• Loose sand or stone. 

• Grass, leaves, or sticks. 

• Water. 

• Oil. 

• Other. 

• Several of the above. 

• Indistinguishable from photos. 

• None. 

• Unknown location of first

shoulder involved.

The observations of the first and 

second variables apply here.

Roadway

Geometry and 

physical 

elements

9 Pavement 

marking quality

• Visible.

• Decayed. 

• Indistinguishable from photos. 

“No shoulder involved” indicates 

that either the road has no shoulders 

or the vehicle did not leave the 

roadway during the crash.

13 
Part of the 

Road 

Described

Type of 

Information # Variable Attributes Observations

Pavement 

properties and 

contamination

10 Roadway 

pavement type

• Asphalt

• Concrete

• Other: specify

• Indistinguishable from photos

11 Apparent macrotexture

• Yes, due to visible coarse texture 

from tining or grooves in concrete 

surface or exposed surface or 

exposed coarse aggregate in 

asphalt or concrete surface. 

• No. 

• Indistinguishable from photos.

Selecting “yes” requires having a 

very good photograph that 

effectively indicates that the road 

has an apparent macrotexture. 

12 Rutting • Yes, per puddled or other surface 

water in ruts, low spots, or flat 

areas. 

• No. 

• Indistinguishable from photos.

Selecting “yes” requires having a 

very good photograph that 

effectively indicates that the road 

has rutting.

13 Pavement 

contamination

• Ice or slush.

• Snow. 

• Mud. 

• Sand. 

• Gravel. 

• Water. 

• Oil. 

• Other. 

• Several of the above. 

• Indistinguishable from photos. 

• None.

14 Gross pavement 

irregularities

• None.

• Very rough. 

• Big pothole(s). 

• Large dips or bumps. 

• Concrete pavement blow-up. 

• Excessive patching/settlement. 

• Large cracks. 

• Large longitudinal gaps pavement 

to shoulder or between lanes. 

• Under construction conditions. 

• Drop-off between lanes during 

construction of overlays. 

• Other. 

• Indistinguishable from photos.

Barrier Geometry and 

physical 

elements

15 Location of the 

first compromised 

barrier

• No barrier compromised.

• Left side of road. 

• Right side of road. 

• Other. 

• Indistinguishable from photos. 

• Unknown location.

14 
Part of the 

Road 

Described

Type of 

Information # Variable Attributes Observations

16 Barrier type • No barrier compromised. 

• Aesthetic timber barrier/wood 

guardrail. 

• Box beam. 

• Bridge rail. 

• Constant slope barrier (UK 

equivalent, concrete step barrier). 

• F-shaped barrier. 

• General Motors® (GM®) barrier 

shape. 

• High-tension cable guardrail 

systems. 

• Impact attenuators. 

• Jersey barrier. 

• Low-tension cable guardrail. 

• Median barrier steel guardrail.

• Median strip. 

• Steel-backed timber guardrail. 

• Temporary impact attenuators. 

• Thrie beam. 

• Thrie beam strong post. 

• Water- and sand-filled barriers. 

• W-beam strong post. 

• W-beam weak post. 

• Weak post box beam. 

• Weathering steel (Corten®) 

guardrail. 

• Other: specify. 

• Indistinguishable from photos. 

• Unknown location of first barrier 

compromised. 

15 
Part of the 

Road 

Described

Type of 

Information # Variable Attributes Observations

Barrier

Geometry and 

physical 

elements

17 Barrier end 

treatment type

• Outside the road segment of 

analysis. 

• Bull nose end treatment. 

• Guardrail bridge attachment. 

• Rock fence. 

• Rounded terminal buffer (shape 

of a question mark). 

• Single guardrail terminal (SGT) 

(sequential kinking terminal 

(SKT)-350) types I, II, and III, 

hinged breakaway (HBA) 

(installation instructions 

drawing). 

• Terminal anchor section (TAS or

“turndown” roll-over end 

section).

• Terminal end sections (boxing 

glove). 

• Thrie beam terminal connector 

shoe (end shoe). 

• Trail end guardrail sections. 

• W-beam terminal connector shoe. 

• Jersey barrier end treatment 

type F. 

• Impact attenuators. 

• Other. 

• Indistinguishable from photos.

18 Barrier post 

material

• No barrier compromised.

• Wood. 

• Metal. 

• Indistinguishable from photos. 

• N/A (i.e., Jersey barrier). 

• Unknown location of first barrier 

compromised.

19 Barrier block-out 

material

• No barrier compromised.

• Wood. 

• Plastic. 

• Metal. 

• Indistinguishable from photos. 

• No block-out material. 

• N/A (i.e., Jersey barrier). 

• Unknown location of first barrier 

compromised.

20 Location of crash 

with respect to 

barrier

• Along the barrier.

• At the end of the barrier. 

• No barrier involved.

21 Location of crash 

with respect to 

guardrail

• Along the guardrail.

• At the end of the guardrail. 

• No guardrail involved.

16 
Part of the 

Road 

Described

Type of 

Information # Variable Attributes Observations

Damage 

caused

22 Ground to barrier 

face, measurement rods

N/A Sometimes the people in charge of 

the photographs put a rod in front of 

the barrier. This rod has very visible 

marks that allow an approximate 

measurement of the distance 

between the ground and the 

beginning of the barrier face.

23 Vertical barrier 

face, measurement rods

N/A The observation of the 20th variable 

also applies here.

24 Horizontal 

damage barrier 

face, measurement rods

N/A Although the expectation was that 

the people on the ground would put 

a rod for measuring this length on 

the damage, there were no 

photographs with this aiding rod.

25 Damage height 

from ground, 

measurement rods 

N/A The observation of the 21st variable 

also applies here.

26 Ground to barrier, 

Google Earth®

N/A These variables are analogous to 

variables 20–23. Nonetheless, the 

measurement would not be taken by 

looking at a possible rod on the 

picture but by using Google Earth®. 

These variables were not actually 

used for the NMVCCS database but 

for another database (i.e., this was a 

flexible data entry meant to 

accommodate FARS as well as 

NMVCCS data as well). 

27 Vertical barrier 

face, Google 

Earth®

N/A

28 Horizontal 

damage barrier 

face, Google 

Earth®

N/A

29 Damage height 

from ground, 

Google Earth®

N/A

30 Barrier condition • No barrier compromised.

• No visible damage. 

• Scuffing and scraping. 

• Breakage barrier face. 

• Breakage component. 

• Compromised location. 

• Indistinguishable from photos. 

• Unknown location of first barrier 

compromised. 

• Unknown since photos were 

taken before crash. 

• Unknown since photos were 

taken more than 1 month after 

crash.

Precipitation Precipitation 31 Reported 

precipitation

• Liquid.

• Freezing.

• Frozen. 

• None. 

• Not reported.

As mentioned previously, this 

variable did not come from the 

photographs but from the narrative 

of the NMVCCS database.

Note: Blank cells in observations denote an absence of special instructions for the referenced rubric.

N/A = Not applicable.

17 
SUMMARY STATISTICS

Figure 4 through figure 7 summarize some of the information captured in the variables in 

table 6. A comprehensive count of the information obtained can be found in appendix C. 

Figure 4. Graph. Attributes observed in the roadway to paved shoulder drop-off variable. 

Figure 5. Graph. Attributes observed in the roadway pavement type variable. 

18 
Figure 6. Graph. Attributes observed in the location of the first compromised barrier

variable. 

Figure 7. Graph. Attributes observed in the barrier post material variable. 

PHOTOGRAPHIC EXAMPLES 

The previous section presented the procedure that should be followed to perform data extraction. 

This section illustrates that procedure followed by an explanation of how a catalog was used to 

identify different road elements in the case studies. These road elements include types of barriers 

and barrier end treatment types. Finally, cases in which difficulties were experienced are 

presented for capturing information from the photographs. 

19 
Typical Case 

The example presented here corresponds to Case No. 2005079486822 from the NMVCCS 

database and follows the procedure explained in the previous section. The following 

variables are not mentioned in this example: paved shoulder contamination (8), apparent 

macrotexture (11), rutting (12), pavement contamination (13), and gross pavement irregularities 

(14). Those variables presented challenges for the analyst and are mentioned in the subsection 

“Challenging Aspects.” 

The narrative presented in NMVCCS provides the following information (hereafter referred to 

as observations): 

1. It was a single-vehicle crash. 

2. The vehicle was heading northbound. 

3. The driver drove off the roadway into the left shoulder and then hit the barrier. 

4. The main factor for the vehicle’s departure did not seem to be caused by a feature in the road 

or pavement but by the behavior of another vehicle. 

5. There was no precipitation at the time of the crash. 

Observations 2, 3, and 5 provide an immediate answer to the question of which attributes assign 

to the following variables: 

• Location of the first shoulder involved: Left side (1).

• Location of the first compromised barrier: Left side (15).

• Reported precipitation: None (31). 

The photographs in figure 8 and figure 9 from the NMVCCS database indicate the following 

values to the variables corresponding to the shoulder:(4)

• Representative paved shoulder width: More than 8 ft (2).

• Representative unpaved shoulder width: No unpaved shoulder (3).

• Major variations in paved shoulder width: No (4).

• Major variations in unpaved shoulder width: No unpaved shoulder (5).

• Roadway to paved shoulder drop-off: No (6).

• Presence of rumble strips: No (7).

20 
Figure 8. Photo. First view of Case No. 2005079486822 showing the point of impact. 

Figure 9. Photo. Second view of Case No. 2005079486822 showing the point of impact. 

Variables 2 and 3 require the judgment of the analyst to indicate a length range for the shoulder. 

Figure 8 shows a pickup parked on the shoulder. Since a standard lane has a length of 12 ft, is 

assumed that the shoulder is longer than 8 ft. Variables 4 and 5 have a “yes” value if the shoulder 

varies considerably from the point where the vehicle hits the barrier to upstream. Because the 

photographs in figure 8 and figure 9 do not provide a good perspective for an answer to 

variable 4, the analyst needs to look at other photographs of the case, such as the photograph in 

figure 10 to confirm the “no” value. From figure 8 through figure 10, the analyst can confirm 

that the shoulder has no rumble strips (variable 6). They also allow the analyst to confirm that 

there is no drop-off between the roadway and the shoulder. 

21 
Figure 10. Photo. Case No. 2005079486822 look back from point of impact. 

Regarding characteristics on the roadway, figure 8 through figure 10 indicate the following 

values for the listed variables: 

• Pavement marking quality: Asphalt (9).

• Roadway pavement type: Visible (10).

Regarding characteristics of the barrier, figure 8 through figure 10 indicate the following values 

for the listed variables:

• Barrier type: Jersey barrier (16).

• Barrier end treatment type: Outside the road segment of analysis (17).

• Barrier post material: Not applicable (i.e., Jersey barrier) (18).

• Barrier block-out material: Not applicable (i.e., Jersey barrier) (19).

• Barrier conditions: Breakage of barrier face (30). 

It is important to note that variables 18 and 19 only apply to guardrails such as aesthetic timber 

barrier/wood guardrail, median barrier steel guardrail, Thrie beam, Thrie beam strong post, 

W-beam strong post, W-beam weak post, weak post box beam, and weathering steel (Corten®) 

guardrail. Variable 17 has a value of “outside the road segment of analysis” in this example

because the crash did not happen at the end of a barrier.

An important question to ask is whether the vehicle had a hit along the barrier or at its end. This 

is answered through the photographs and allows determining the value for the location of crash 

with respect to the barrier. A similar variable is “location of crash with respect to guardrail.” This 

variable only looks at those barriers that are guardrails. In this specific example, those 

two variables have the following values:

22 
• Location of crash with respect to barrier: Along the barrier (20). 

• Location of crash with respect to guardrail: No guardrail involved (21). 

Finally, the analyst should consider if there is information in the photographs that provides 

values for the following variables: ground to barrier face, measurement rods; vertical barrier 

face, measurement rods; horizontal damage barrier face, measurement rods; and damage height 

from ground, measurement rods. In the case analyzed in this example, there were no photographs 

that provide an estimate for these measurements. In some few cases, the people in charge of 

collecting the data put a rod next to the scene of the crash. A case with this information is 

provided in the subsection “Challenging Aspects.” 

Examples of Other Road Elements Presented in the Crash Cases

This section presents the original motivation for photographic data extraction feasibility and pilot 

studies with examples of different road elements. These road elements include the variables 

barrier type and barrier end treatment type. The analysts relied on a photograph catalog (shown 

in appendix A) to identify these road elements. Table 7 presents the road element for each 

example, while figure 11 through figure 16 show the corresponding photographs. 

Table 7. Identification of road elements in some cases.

Case No. Barrier Type Element

Barrier End Treatment Type 

Element

2005049602183 W-beam strong post Energy absorbing

2005049602403 High-tension cable guardrail 

systems

Outside the road segment of analysis

2005012696122 Thrie beam strong post Non-energy absorbing (slotted rail 

terminal)

2005082626081 W-beam strong post Impact attenuators

Figure 11. Photo. Case No. 2005049602183 post-crash W-beam strong post (left) contrasted 

with comparative catalog image (right).(4,14)

23 
Figure 12. Photo. Case No. 2005049602183 post-crash W-beam strong post highlighting

energy absorbing end treatment.

(4,14)

Figure 13. Photo. Case No. 2005049602403 post-crash high-tension cable guardrail systems

(left) contrasted with comparative catalog image (right).

(4,15)

Figure 14. Photo. Case No. 2005012696122 post-crash Thrie beam strong post (left)

contrasted with comparative catalog image (right).

(4,16)

24 
Figure 15. Photo. Case No. 2005012696122 post-crash Thrie beam strong post (left)

highlighting non-energy absorbing slotted rail terminal contrasted with comparative 

catalog image (right).(4,14)

Figure 16. Photo. Case No. 2005082626081 post-crash impact attenuator (left) in advance of 

W-beam strong post (center) contrasted with comparative catalog image (right).(4,14)

Challenging Aspects

In response to colleagues studying pavement performance issues, this study was extended to 

identify variables related to pavement properties and contamination (see table 6). A pavement 

pilot study was initiated within the photographic data extraction pilot study. One of these 

variables was the macrotexture (11) of the pavement. The objective of this variable was to 

identify whether the road surface was in optimal condition (case in which the variable would 

have a “no” value) or whether it had features on the surface that highlighted some type of 

macrotexture. Figure 17 through figure 21 present photographs used to identify this variable. 

Experts in the field determined that these pictures are not of high enough quality to establish with 

assurance if the road surfaces present an identifiable macrotexture. For this reason, this variable 

was dropped and does not appear in the statistics of this study. 

25 
Figure 17. Photo. Photograph 1 used for identifying macrotexture in 

Case No. 2005012695244. 

Figure 18. Photo. Photograph 2 used for identifying macrotexture in 

Case No. 2005012695244. 

Figure 19. Photo. Photograph 3 used for identifying macrotexture in 

Case No. 2005012695244. 

26 
Figure 20. Photo. Photograph 1 used for identifying macrotexture in 

Case No. 2007075702347. 

Figure 21. Photo. Photograph 2 used for identifying macrotexture in 

Case No. 2007075702347. 

Another variable that was included at the beginning of the study was rutting (variable 12). 

Figure 22 shows a probable case of rutting. After submitting this photograph to experts in the 

field, it was determined that it could not be used to determine rutting. As a result, this variable 

was dropped from the study. Due to similar reasons, the following other variables were dropped: 

paved shoulder contamination (8), pavement contamination (13), and gross pavement 

irregularities (14). 

27 
Figure 22. Photo. Photograph used for identifying rutting in Case No. 2007075702347. 

Finally, obtaining values for the following variables was challenging: ground to barrier face, 

measurement rods; vertical barrier face, measurement rods; horizontal damage barrier face, 

measurement rods; and damage height from ground, measurement rods. In very few cases, such 

as the one shown in figure 23, these measurements were possible to obtain.

Figure 23. Photo. Photograph from Case No. 2005073438121 in which measurements were 

obtained using rods.

DISCUSSION

Although a great deal of new information has been identified through the study of NMVCCS 

images, several limiting factors must be acknowledged. First, the roadway departure problem 

comprised over half the crash fatalities.

(1) However, the sample size is relatively small for 

researcher-investigated crashes benefitting from on-scene NMVCCS or near-crash time NASS 

28 
CDS photography. FARS, while rich in data, provides limited details. This discussion section

considers the data acquired from NMVCCS on-scene photography. 

Data Enhancements Sought

The supplementary dataset was envisioned to provide more roadside information than previously 

coded. The data were expected to have a uniform core of relevant variables and attributes.

Finally, a systematic approach was to be devised through the feasibility and pilot studies to 

streamline data extraction.

Height of Barrier and Damage 

The pilot study yielded unexpected results. Several roadside elements were highlighted by 

measurement rods that were originally used to take vehicle damage measurements for NASS 

CDS cases. NMVCCS photography protocols did not contemplate the roadside environment, as 

did LBSS in the early 1980s, with only known NASS classification of variables using a limited 

number of attributes. In the model of the NCHRP studies, all photographic data were 

considered.(8–10) The measurement rods, when available, provided insight into the height of the 

barrier from the ground, the height from where the measurement rods were placed in the 

photograph to damaged barrier location, and, occasionally, the width of the damage. It was 

found that most roadside element photographs were absent of measurement rods, leaving very 

small cell sizes from which to draw conclusions. With added sample size, the benefit would 

involve assessing variations in barrier height owing to maintenance and vehicle compatibility 

with barriers.

Damage Location 

Another critical feature involved locating the precise damage location(s) along the roadside 

element. Damage and injury patterns might vary depending on impact with the end terminal, 

post, or length of need (i.e., adequate distance in advance of the hazard to keep the vehicle safe 

from impact and redirected back on the roadway). Even amidst the small sample sizes, this was 

deemed a potentially important data element.

Shoulder Width

Although the data acquisition was meant to be fact-based and require no estimation, pavement 

engineers suggested that estimating the shoulder width might be useful with an assessment of 

pavement type and quality. While the photographs carried insufficient resolution to provide the 

details required for pavement assessments, the shoulder width estimation was retained. The 

photographic data coder estimated in increments of 4 ft. This may be an effective qualitative 

means for understanding the roadway departure and vehicle trajectory before reaching final rest.

Roadside Element Classification 

The purpose of the feasibility study was to assess the viability of viewing photographs, 

confirming the installed hardware coded in a crashworthiness dataset, and supplementing the 

component materials. A catalog of existing barrier technologies was compiled for easy 

comparison by the data coder. Furthermore, the type of barrier, its post, and end treatment were 

29 
identified based on the catalog of photographs. This was intended to provide information missing 

since the LBSS performed by NHTSA for FHWA. Since the LBSS predated the electronic data 

releases, it has been lost to paper archives and potentially of minimal relevance owing to the 

changes in vehicle fleet over the past 30 years.

Through iterations of photographic review, refinements proposed by three reviewers, and 

inclusion of supplemental data sources, a labor-intensive process has been improved by 

developing a review methodology. With improvements in data capture, some of the human 

intervention can be replaced by digital identification of roadside elements. Currently, the military 

has partnered with reality television to improve the processing and screening of drone footage, 

which might benefit the identification of roadside elements in still and video image and facilitate 

extraction of this data into an analysis ready data format. Several more iterations of human 

reviews will be required to determine the conditions, such as lighting, clarity, and element types, 

under which these digital identifications might take place.

Future Refinements

These additional insights will be useful to modelers filling important gaps of understanding as 

well as to roadway designers in understanding how the vehicle and occupant interact with the 

roadside environment. The previously mentioned variables are a small subset of the data 

acquired from the photographic review and deemed important to the pilot study on roadway 

departure. In the way that NMVCCS was originally intended to serve as a behavioral crash 

causation dataset and not envisioned to provide valuable roadside information, other data 

elements extracted from the photographs might be useful to other users. For this reason, 

appendix B outlines the data collected and the relevant attributes, and appendix C contains the 

full data extraction.

30 
CHAPTER 4: FUTURE CONSIDERATION AND PILOT STUDY SUMMARIZATION 

Based on the precedent of successful NCHRP studies, the review of photographs was deemed 

an appropriate means of extending the current understanding of roadway departure crashes. The 

results of using crashworthiness data collected for different purposes were mixed and exceeded 

expectations. Presently, first event roadside element crashes have been reviewed, and the 

photographic data have been extracted. A proposed outline of the remaining datasets with their 

perceived impact and limitations has been compiled in the following sections. 

FUTURE REVIEWS: IMPACT AND LIMITATIONS

Subsequent iterations of this study will continue to focus on FARS, NASS CDS, and NMVCCS. 

The census quality of FARS will provide many panoramic photographs from which to extract 

data but which are less relevant to the crash event. NASS CDS will provide near crash time 

photographic evidence predicated upon the strength of the photography and identification of 

salient roadside elements. Finally, NMVCCS photography has yielded the highest-quality and

most crash-relevant information. 

FARS Crashes

In deference to the on-scene crash photographs, the identified FARS crashes were assessed and 

set aside during the pilot study. During the next phase, it is envisioned that panoramic view 

software will be consulted to provide an image of the crash scene at a temporally discontinuous 

time with the crash. The benefit will be to understand roadside element placement and potential 

crash trajectory. The type of roadside element will be assumed to be static, with damaged 

elements being replaced with the same type of technology. The limitation exists in confirming 

the precise location of impact and forfeiting important post-crash damage condition data. 

NASS CDS Dataset 

This dataset is caught in the middle of FARS and NMVCCS, with rich data but scant roadside 

element detail, captured weeks after the crash scene has been cleared. NASS CDS crashes after 

2008 will be consulted by applying the NMVCCS filter for first event roadside element impacts.

This will be the surrogate for the FARS data definition of roadway departure. As the precise 

crash location will have been photographed by the researcher, location identification has been 

assured. As this will have been near-crash time photography, many damage clues may have 

disappeared or the element might have been replaced by the time of investigation. Although this 

database may be able to provide information on roadside element type and its components, more 

subtle measurements and crash evidence might be lost to the meteorological vagaries of the area.

NMVCCS Dataset 

Beyond the first event roadside element impacts, many secondary events involving roadside 

elements exist. The rationale for excluding secondary impacts is that the most crash sensors were 

designed as first event technologies and are disabled upon first impact, rendering the technology 

inactive, as it cannot be triggered in the absence of a functioning sensor. Premature deployment 

might have been with good reason; however, graduated technologies deploying in stages such as 

31 
airbags would have the most compatibility with reviewing subsequent roadside element events. 

For purposes of enlarging the dataset, additional secondary event crashes will be reviewed to 

determine whether they provide insight into to the roadway departure problem. 

Data Collection via Photographic Reviews 

Based on the success of the pilot study, the Highway Safety Information System Laboratory may 

be asked to supply additional graduate student support. These students are preparing for graduate 

degrees in civil engineering, generally specializing in roadway transportation. This skill set 

makes them aware of design issues and capable of providing insights into matching the case

photographs to the catalog. Even with the most accomplished engineering student, human error, 

limited hardware experience, and photographic clarity might affect proper codification. For 

this reason, the supplemental dataset produced in the pilot study will be reviewed by subjectmatter experts.

As new students will be undertaking this task and learning the data extraction methodology, 

they will be subjected to a learning curve, similar to the one encumbering the early pilot study

data acquisition. Student adaptation was not found to be an impediment to the study. 

Future Technologies

As mentioned previously, adoption of digital data capture is one goal for this project. As a result, 

results of the FHWA EAR Program are being monitored for information exchange. 

Planned Future Activities

Planned future activities include the following: 

• Submit supplemental dataset produced in pilot study to subject-matter expert review.

• Codify geographical locations from FARS cases, 2004 to the present, using panoramic 

view software.

• Codify NASS CDS first event roadside element impact crashes.

• Identify applicable NMVCCS secondary roadside element impact crashes.

• Promote the need for more on-scene data collection. 

PILOT STUDY SUMMARIZATION

Photographic extraction was used to understand the composition and placement of roadway 

elements. As the feasibility study progressed, more elements were found to be extractible from 

the photographs. Similarly, as the pilot study progressed, extended roadway data were collected 

beyond the realm of safety. 

32 
Findings of the Photographic Data Extraction Feasibility Study

The value of the data extraction pilot study was marketed to various stakeholders by means of 

committee briefings, working papers, and conference publications. The pilot study also sought to 

highlight the value of on-scene crash photography. Within this publication, the pilot study 

identification of candidate crashes and the filtering methodology was discussed. The crashes 

deemed suitable for subsequent review were classified with respect to data extraction value.

Findings of the Photographic Data Extraction Pilot Study To Date

The development of the supplementary dataset began with the pilot study. Reviewing NMVCCS 

crash scene photographs, the variables and attributes were refined and augmented. It is 

understood that an on-scene data collector completely versed in roadside element design, 

placement, and construction would be the best data compiler. However, this would be cost 

prohibitive, and uniformity would vary. As a result, a photographic review model was adopted. 

Summary statistics were prepared that illustrated the unexpected types of information available 

from photographic review and highlighted sample size issues. The extracted data are expected 

to benefit modelers in understanding the vehicle interactions with the roadside beyond the 

information acquired to date from vehicle sensors, which are generally disabled after the first 

off-road crash event.

Recommendations for the Future of the Photographic Data Extraction Efforts 

In addition to the cases reviewed in the pilot study, additional subsequent event NMVCCS 

crashes as well as FARS and CDS crashes have been identified for subsequent review. The 

methodology will vary for temporally discontinuous images, but the basic identifying 

information should remain constant. Issues of damage will not be assessed, as damage cannot 

be tied conclusively to the reviewed crash. Consideration will also be given to the synthesis of 

data for on-scene, near crash time, and temporally discontinuous crashes. Finally, continued 

encouragement will be given to data compiling organizations to revive on-scene crash 

data collection.

33 

APPENDIX A: PHOTOGRAPHIC CATALOG OF ROADSIDE ELEMENTS

This appendix presents the photographs that were used as a reference when classifying two types 

of roadside elements: barrier type and barrier end treatment type. 

Figure 24 through figure 48 present the different types of barriers that were used as a reference 

for the variable barrier type. Each type corresponds to one attribute in the variable. Other 

attributes used to describe this variable were no barrier compromised, other: specify, 

indistinguishable from photos, and unknown location of first barrier. 

Figure 24. Photo. Barrier type 1—aesthetic timber barrier/wood guardrail.(17)

Figure 25. Photo. Second image of barrier type 1—aesthetic timber barrier/wood 

guardrail.(18)

35 
Figure 26. Photo. Barrier type 2—box beam.(19)

Figure 27. Photo. Barrier type 3—bridge rail.(20) 

Figure 28. Photo. Second image of barrier type 3—bridge rail.(20) 

36 
Figure 29. Photo. Third image of barrier type 3—bridge rail.(20) 

Figure 30. Illustration. Barrier type 4—constant slope barrier.(20)

Figure 31. Photo. Barrier type 5—F-shaped barrier.(20)

Barrier type 6 is a GM® barrier shape. An image for this barrier shape was not available for the 

publication but can be viewed with an online search. 

37 
Figure 32. Photo. Barrier type 7—high-tension cable guardrail system.(15)

Figure 33. Photo. Barrier type 8—Jersey barrier.(20) 

Figure 34. Photo. Second image of barrier type 8—Jersey barrier.(20) 

38 
Figure 35. Photo. Barrier type 9—low-tension cable guardrail.(21)

Figure 36. Photo. Barrier type 10—median barrier steel guardrail.(15) 

Figure 37. Photo. Barrier type 11—median strip.(22)

39 
Figure 38. Photo. Barrier type 12—steel-backed timber guardrail.(17)

Figure 39. Photo. Barrier type 13—Thrie beam.(20)

Figure 40. Photo. Barrier type 14—Thrie beam strong post.(16)

40 
Figure 41. Photo. Barrier type 15—W-beam strong post.(14)

Figure 42. Photo. Barrier type 16—W-beam weak post.(14)

Figure 43. Photo. Barrier type 17—weak post box beam.(23)

Figure 44. Photo. Barrier type 18—weathering steel (Corten®) guardrail.(14)

41 
Figure 45. Photo. Barrier type 19—impact attenuator.

(4) 

Figure 46. Photo. Second image of barrier type 19—impact attenuator.

(4) 

Figure 47. Photo. Third image of barrier type 19—impact attenuator.

(24) 

42 
Figure 48. Photo. Fourth image of barrier type 19—impact attenuator.

(4) 

Figure 49 through figure 58 present the different types of treatments on the barrier ends that were 

used as a reference for the variable “barrier end treatment type.” Each treatment corresponds to 

one attribute in the variable. Other attributes used to describe this variable were outside the road 

segment of analysis, other, and indistinguishable.

Figure 49. Photo. Barrier end treatment type 1—bull nose end treatment.(25)

Figure 50. Photo. Barrier end treatment type 2—guardrail bridge attachment.(14)

43 
Figure 51. Photo. Barrier end treatment type 3—rock fence.(26) 

Figure 52. Photo. Barrier end treatment type 4—rounded terminal buffer 

(“question mark”).(14)

Barrier end treatment type 5 was SGT (SKT 350) types I, II, and III, HBA. An image for 

this barrier end treatment was not available for the publication but can be viewed with an 

online search.

Figure 53. Photo. Barrier end treatment type 6— “turndown” roll-over end section.

(14)

44 
Figure 54. Photo. Barrier end treatment type 7—terminal end sections (boxing glove).(14)

Figure 55. Photo. Barrier end treatment type 8—Thrie beam terminal connector shoe 

(“end shoe”).(20)

Barrier end treatment type 9 was a trail end guardrail section. An image for this barrier shape 

was not available for the publication but can be viewed with an online search. 

Figure 56. Photo. Barrier end treatment type 10—W-beam terminal connector shoe.

(14)

Barrier end treatment type 11 was a Jersey barrier end treatment type F. An image for this barrier 

shape was not available for the publication but can be viewed with an online search. 

Figure 57. Photo. Barrier end treatment type 12—impact attenuators.(27)

45 
Figure 58. Photo. Barrier end treatment type 12—temporary impact attenuators.

(4)

46 
APPENDIX B: DATA EXTRACTION SPREADSHEET

This appendix presents the spreadsheet that was used to extract the data. The spreadsheet is 

shown in figure 59 and figure 60. The figures allow researchers to determine which variables had 

a limited set of attributes and which ones were not restricted to a set of attributes.

As observed in the figures, each color represents the part of the roadway that is being described. 

In figure 59, the seven center orange columns concern the shoulder, and the six columns in white 

(shown in bottom columns) correspond to the roadway. In figure 60, the 12 columns in purple 

(seven columns in top columns, five columns in center graphic) correspond to the barrier, the 

column in teal (figure 59, top column) corresponds to the precipitation, and the remaining 

columns in white (figure 60, bottom columns) correspond to additional information. 

47 
Figure 59. Illustration. Spreadsheet employed for data extraction (first 15 columns). 

48 
Figure 60. Illustration. Spreadsheet employed for data extraction (last 18 columns).

49 

APPENDIX C: COMPLETE SUMMARY STATISTICS

This appendix presents all the attributes found in the data extraction process, as seen in table 8

through table 25. Due to its completeness, this appendix presents only the number of attributes 

and their percentage for each of the variables. Some of these values were already presented in the 

“Descriptive Summary Statistics” section. 

Table 8. Reported precipitation. 

Attribute Count Percent

Liquid 63 16.3

Freezing 0 0.0

Frozen 20 5.2

None 278 71.8

Not reported 26 6.7

Table 9. Location of the first shoulder involved. 

Attribute Count Percent

No shoulder involved 7 1.8

Left side of road 229 59.2

Right side of road 148 38.2

Other 3 0.8

Unknown 0 0.0

Table 10. Representative paved shoulder width. 

Attribute Count Percent

No shoulder involved 8 2.1

No paved shoulder 21 5.4

Less than 4 ft 104 26.9

4 to 8 ft 98 25.3

More than 8 ft 140 36.2

Indistinguishable from photos 16 4.1

Unknown location of first shoulder involved 0 0.0

Table 11. Representative unpaved shoulder width. 

Attribute Count Percent

No shoulder involved 8 2.1

No unpaved shoulder 285 73.6

Less than 4 ft 54 14.0

4 to 8 ft 13 3.4

More than 8 ft 13 3.4

Indistinguishable from photos 14 3.6

Unknown location of first shoulder involved 0 0.0

51 
Table 12. Major variations in paved shoulder width. 

Attribute Count Percent

No shoulder involved 9 2.3

No paved shoulder 19 4.9

Yes 39 10.1

No 303 78.3

Indistinguishable from photos or other sources 17 4.4

Unknown location of first shoulder involved 0 0.0

Table 13. Major variations in unpaved shoulder width. 

Attribute Count Percent

No shoulder involved 8 2.1

No unpaved shoulder 274 70.8

Yes 34 8.8

No 53 13.7

Indistinguishable from photos or other sources 18 4.7

Unknown location of first shoulder involved 0 0.0

Table 14. Roadway to paved shoulder drop-off. 

Attribute Count Percent

No shoulder involved 9 2.3

No paved shoulder 19 4.9

Yes 72 18.6

No 248 64.1

Indistinguishable from photos 39 10.1

Unknown location of first shoulder involved 0 0.0

Table 15. Presence of rumble strips. 

Attribute Count Percent

No shoulder involved 7 1.8

No paved shoulder 15 3.9

Yes 76 19.6

No 260 67.2

Indistinguishable from photos 29 7.5

Unknown location of first shoulder involved 0 0.0

Table 16. Roadway pavement type. 

Attribute Count Percent

Asphalt 268 69.3

Concrete 104 26.9

Other: specify 6 1.6

Indistinguishable from photos 9 2.3

52 
Table 17. Pavement marking quality. 

Attribute Count Percent

Visible 375 96.9

Decayed 8 2.1

Indistinguishable from photos 4 1.0

Table 18. Location of the first compromised barrier. 

Attribute Count Percent

No barrier compromised 1 0.3

Left side of road 232 59.9

Right side of road 146 37.7

Other 8 2.1

Indistinguishable from photos 0 0.0

Unknown location 0 0.0

Table 19. Barrier type. 

Attribute Count Percent

No barrier compromised 1 0.3

Aesthetic timber barrier/wood guardrail 1 0.3

Box beam 3 0.8

Bridge rail 0 0.0

Constant slope barrier (UK equivalent concrete step barrier) 1 0.3

F-shaped barrier 0 0.0

GM® barrier shape 2 0.5

High-tension cable guardrail systems 4 1.0

Impact attenuators 8 2.1

Jersey barrier 190 49.1

Low-tension cable guardrail 1 0.3

Median barrier steel guardrail 0 0.0

Median strip 1 0.3

Steel-backed timber guardrail 0 0.0

Temporary impact attenuators 0 0.0

Thrie beam 0 0.0

Thrie beam strong post 15 3.9

Water- and sand-filled barriers 1 0.3

W-beam strong post 127 32.8

W-beam weak post 6 6

Weak post box beam 0 0

Weathering steel (Corten®) guardrail 0 0

Other: specify 21 21

Indistinguishable from photos 5 5

Unknown location of first barrier compromised 0 0

53 
Table 20. Barrier end treatment type. 

Attribute Count Percent

Outside the road segment of analysis 270 69.8

Bull nose end treatment 2 0.5

Guardrail bridge attachment 8 2.1

Rock fence 0 0.0

Rounded terminal buffer (“question mark”) 14 3.6

SGT (SKT-350) types I, II, and III, HBA 21 5.4

TAS or “turndown” roll-over end section 3 0.8

Terminal end sections (boxing glove) 10 2.6

Thrie beam terminal connector shoe (“end shoe”) 1 0.3

Trail end guardrail sections 4 1.0

W-beam terminal connector shoe 2 0.5

Jersey barrier end treatment type F 4 1.0

Impact attenuators 11 2.8

Other 22 5.7

Indistinguishable from photos 15 3.9

Table 21. Barrier post material. 

Attribute Count Percent

No barrier compromised 1 0.3

Wood 69 17.8

Metal 91 23.5

Indistinguishable from photos 9 2.3

Not applicable (i.e., Jersey barrier) 217 56.1

Unknown location of first barrier compromised 0 0.0

Table 22. Barrier block-out material. 

Attribute Count Percent

No barrier compromised 2 0.5

Wood 83 21.4

Plastic 12 3.1

Metal 29 7.5

Indistinguishable from photos 29 7.5

No block-out material 7 1.8

Not applicable (i.e., Jersey barrier) 224 57.9

Unknown location of first barrier compromised 0 0.0

None 1 0.3

Table 23. Location of crash with respect to barrier. 

Attribute Count Percent

Along the barrier 270 69.8

At the end of the barrier 116 30.0

No barrier involved 1 0.3

54 
Table 24. Location of crash with respect to guardrail. 

Attribute Count Percent

Along the guardrail 254 65.6

At the end of the guardrail 95 24.5

No guardrail involved 38 9.8

Table 25. Barrier condition. 

Attribute Count Percent

No barrier compromised 2 0.5

No visible damage 23 5.9

Scuffing, scraping 174 45.0

Breakage, barrier face 74 19.1

Breakage, component 35 9.0

Compromised location 35 6.5

Indistinguishable from photos 54 14.0

Unknown location of first barrier compromised 0 0.0

Unknown since photos were taken before crash 0 0.0

Unknown since photos were taken more than 1 month after crash 0 0.0

55 

ACKNOWLEDGEMENTS

The original map image in figure 1 was created using Google Earth®. Google, Inc. owns the 

copyright of the original image. As a part of this study, the Google Earth® image was modified 

with a photo overlay depicting a possible car rollover crash trajectory.

57 

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63 


HRDS-20/05-14(50)E Recycled

Recyclable