A SAFE SYSTEM-BASED FRAMEWORK 

AND ANALYTICAL METHODOLOGY 

FOR ASSESSING INTERSECTIONS
A SAFE SYSTEM-BASED FRAMEWORK AND ANALYTICAL METHODOLOGY FOR ASSESSING INTERSECTIONS

FOREWORD

In the United States, the Safe System approach represents a paradigm shift in how road safety is 

addressed. Foundational to the Safe System approach is that no person should be killed or seriously 

injured when using the road system, and that it is a shared responsibility by all parties involved to 

ensure this becomes reality. From a roadway infrastructure perspective, a Safe System approach 

involves managing the circumstances of crashes such that the kinetic energy imposed on the human 

body be kept at levels that are tolerable in terms of survivability and degree of harm. At an 

intersection, this challenge is characterized through managing speed and crash angles, as well as 

considering risk exposure and complexity. This report proposes a Safe System framework and analytical 

methodology for intersections that can be applied at the project level, and that can be incorporated into

an Intersection Control Evaluation alternatives screening process to provide another metric for safety.

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.
A SAFE SYSTEM-BASED FRAMEWORK AND ANALYTICAL METHODOLOGY FOR ASSESSING INTERSECTIONS

TECHNICAL DOCUMENTATION PAGE

1. Report No.

FHWA-SA-21-008

2. Government Accession

No.

3. Recipient's Catalog No.

4. Title and Subtitle

A Safe System-Based Framework and Analytical Methodology for Assessing

Intersections

5. Report Date

January 2021

6. Performing Organization Code

7.Author(s)

R.J. Porter, Michael Dunn, Jonathan Soika, Ivy Huang, Dylan Coley, Annette

Gross, Wes Kumfer, and Stephen Heiny

8. Performing Organization Report No.

9. Performing Organization Name and Address

Vanasse Hangen Brustlin, Inc (VHB)

940 Main Campus Drive, Suite 500

Raleigh, NC 27606

10. Work Unit No.

11. Contract or Grant No.

DTFH61-05-D-00024 (VHB)

12. Sponsoring Agency Name and Address

Federal Highway Administration Office of Safety

1200 New Jersey Ave., SE

Washington, DC 20590

13. Type of Report and Period

Final Report, April 2018 – January

2021

14. Sponsoring Agency Code

FHWA

15. Supplementary Notes

This report was produced under the direction of Jeffrey Shaw, Intersections Program Manager, FHWA Office of Safety.

16. Abstract

This report presents a Safe System for Intersections (SSI) method that intersection planners and designers can readily

implement, that dovetails with the typical U.S. project development process, and that uses commonly available projectlevel data. The SSI method is presented in the context of a Stage 1 Intersection Control Evaluation (ICE), at the scoping

phase of project development where intersection alternatives are analyzed with respect to whether they meet project needs

and are practical to pursue. The method incorporates concepts of conflict point identification and classification, exposure,

kinetic energy transfer, conflict point severity, and intersection movement complexity. Application of the SSI method

results in multiple measures of effectiveness (MOEs) and a set of SSI scores that characterize the extent to which an

intersection alternative in a given context aligns with the principles of kinetic energy management and a Safe System. The

SSI MOEs and SSI scores can serve as additional safety metrics to inform the process of screening alternatives and

identifying an optimal solution for an intersection. The report includes an overview of Safe System concepts and principles,

a detailed description of the SSI method, example project applications, and a future vision for the method.

17. Key Words:

Safe System, intersection, safety performance,

Intersection Control Evaluation, conflict point

18. Distribution Statement

No restrictions.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this

page) Unclassified

21. No. of Pages

159

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed pages authorized
A SAFE SYSTEM-BASED FRAMEWORK AND ANALYTICAL METHODOLOGY FOR ASSESSING INTERSECTIONS

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TABLE OF CONTENTS

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

CHAPTER 2: SAFE SYSTEM CONCEPTS .................................................................... 5

2.1CHAPTER OBJECTIVE........................................................................................... 5

2.2HISTORY AND BACKGROUND .......................................................................... 5

2.3KINETIC ENERGY MANAGEMENT MODEL ..................................................... 8

2.4WHOLE-SYSTEM APPROACH ............................................................................ 9

CHAPTER 3: SSI METHOD FOR INTERSECTION CONTROL EVALUATION ...17

3.1CHAPTER OBJECTIVE......................................................................................... 17

3.2SSI METHOD OVERVIEW................................................................................... 17

3.3DATA NEEDS ........................................................................................................ 20

3.4CONFLICT POINT INDENTIFICATION AND CLASSIFICATION .............. 21

3.5EXPOSURE ............................................................................................................. 23

3.6CONFLICT POINT SEVERITY ............................................................................ 24

3.7MOVEMENT COMPLEXITY, USER WORKLOAD, AND THE SSI SCORE . 35

3.8EXPANDING THE SSI LIBRARY OF INTERSECTION CONCEPTS ............ 50

3.9SSI EXTENSIONS TO STAGE 2 ICE – ALTERNATIVE SELECTION........... 51

CHAPTER 4: EXAMPLE PROJECT APPLICATIONS................................................53

4.1SCENARIO 1 .......................................................................................................... 54

4.2SCENARIO 2 .......................................................................................................... 62

4.3SCENARIO 3 .......................................................................................................... 70

CHAPTER 5: FUTURE VISION FOR THE SSI METHOD .........................................77

5.1SSI ENHANCEMENTS FOR COMMON INTERSECTION PLANNING AND 

DESIGN APPLICATIONS ......................................................................................... 78

5.2SSI ENHANCEMENTS FOR BROADER SAFE SYSTEM IMPLEMENTATION

..80

APPENDIX A: SSI LIBRARY OF INTERSECTION TYPES .......................................85

TRADITIONAL ........................................................................................................... 86

ROUNDABOUT.......................................................................................................... 89

RESTRICTED CROSSING U-TURN (RCUT) ......................................................... 91

MEDIAN U-TURN (MUT) ......................................................................................... 94

BOWTIE ...................................................................................................................... 96

JUGHANDLE............................................................................................................... 98

QUADRANT ROADWAY ....................................................................................... 100

PARTIAL DISPLACED LEFT TURN (PDLT)........................................................ 102

FULL DISPLACED LEFT TURN (FDLT)............................................................... 104

APPENDIX B: SSI METHOD EXAMPLE CALCULATIONS...................................107

EXPOSURE ................................................................................................................ 112

SEVERITY .................................................................................................................. 115

COMPLEXITY ........................................................................................................... 122

SUMMARY OF EXAMPLE RESULTS..................................................................... 134

COMPUTATION OF THE SSI SCORE.................................................................. 137

REFERENCES ................................................................................................................141
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LIST OF TABLES

Table 1. Five sustainable safety principles (Source: SWOV, 2013).............................. 6

Table 2. Possible long-term maximum travel speeds related to infrastructure, given 

best practices in vehicle design and 100 percent restraint use (Source: Tingvall & 

Haworth, 1999). ...............................................................................................................11

Table 3. SSI method data inputs....................................................................................21

Table 4. AIS injury codes and corresponding probability of death (Harmon, et al., 

2018).................................................................................................................................. 24

Table 5. Regression parameters as computed by Evans (1994). ................................26

Table 6. Estimated impact speeds at which risk of severe injury and death reach 

specified levels, adapted from Tefft (2013)...................................................................28

Table 7. Percentage of crashes by impact speed from Tefft (2013). .........................29

Table 8. MAIS4+ to MAIS3+ risk adjustments and results. ........................................30

Table 9. Speed category assignments for different intersection types......................33

Table 10. Assumed speed values for SSI methodology...............................................34

Table 11. Collision angle assumptions for SSI methodology......................................35

Table 12. Merge score for conflicting lanes parameter...............................................43

Table 13. Nonmotorized turn score for conflicting lanes complexity parameter. ..47

Table 14. Speed values used in SSI method examples. ...............................................53

Table 15. Collision angle values used in SSI method examples. ................................54

Table 16. Intersection attributes for Scenario 1..........................................................56

Table 17. CAP-X results for Scenario 1. .......................................................................57

Table 18. SPICE results for Scenario 1. ........................................................................58

Table 19. SSI score results for Scenario 1. ...................................................................59

Table 20. Relative exposure, average P(FSI), and average complexity adjustment 

results for Scenario 1.......................................................................................................61

Table 21. Intersection attributes for Scenario 2..........................................................64

Table 22. CAP-X results for Scenario 2. .......................................................................65

Table 23. SPICE results for Scenario 2. ........................................................................66

Table 24. SSI score results for Scenario 2. ...................................................................67

Table 25. Relative exposure, average P(FSI), and average complexity adjustment 

results for Scenario 2.......................................................................................................69

Table 26. Intersection attributes for Scenario 3..........................................................71

Table 27. CAP-X results for Scenario 3. .......................................................................72

Table 28. SPICE results for Scenario 3. ........................................................................73

Table 29. SSI score results for Scenario 3. ...................................................................74

Table 30. Relative exposure, average P(FSI), and average complexity adjustment 

results for Scenario 3.......................................................................................................76

Table 31. Key characteristics and considerations related to the traditional 

intersection alternatives. ................................................................................................86

Table 32. Key characteristics and considerations related to the roundabout 

intersection alternatives. ................................................................................................89
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Table 33. Key characteristics and considerations related to the RCUT intersection 

alternatives.......................................................................................................................91

Table 34. Key characteristics and considerations related to the MUT intersection 

alternative.........................................................................................................................94

Table 35. Key characteristics and considerations related to the bowtie intersection 

alternative.........................................................................................................................96

Table 36. Key characteristics and considerations related to the jughandle 

intersection alternative...................................................................................................98

Table 37. Key characteristics and considerations related to the quadrant roadway 

intersection alternative.................................................................................................100

Table 38. Key characteristics and considerations related to the PDLT intersection 

alternative.......................................................................................................................102

Table 39. Key characteristics and considerations related to the FDLT intersection 

alternative.......................................................................................................................104

Table 40. Example calculation core inputs. ................................................................107

Table 41. Default input values used for example calculations.................................. 108

Table 42. Conflict points used for example calculations...........................................109

Table 43. Summary of exposure calculation example results.................................. 134

Table 44. Summary of severity calculation example results. ...................................135

Table 45. Summary of complexity calculation example results...............................136

Table 46. Exposure-severity-complexity product results for unsignalized RCUT 

crossing conflict points.................................................................................................. 137

Table 47. Exposure-severity-complexity product results for unsignalized RCUT 

merging conflict points. ................................................................................................138

Table 48. Exposure-severity-complexity product results for unsignalized RCUT 

diverging conflict points................................................................................................138

Table 49. Exposure-severity-complexity product results for unsignalized RCUT 

nonmotorized conflict points. ......................................................................................139
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LIST OF FIGURES

Figure 1. Graphic. The five layers of protection in the KEMM..................................... 9

Figure 2. Graphic. Portrayal of the Safe System in FHWA’s Safe System Approach 

brochure. ..........................................................................................................................10

Figure 3. Graphic. Risk assessment framework. ..........................................................15

Figure 4. Graphic. Conflict points at a MUT intersection...........................................23

Figure 5. Equation. Exposure of index for conflict point c. .........................................23

Figure 6. Graphic. Diagram illustrating various angles of collision............................25

Figure 7. Equation. Probability of fatality or serious injury for one vehicle at 

crossing, merging, or diverging conflict point cveh. .......................................................26

Figure 8. Equation. Delta-V for vehicle Ui at conflict point cveh...................................26

Figure 9. Graphic. P(FSI) for occupants of one vehicle versus delta-V of that vehicle 

during a crash...................................................................................................................27

Figure 10. Equation. Probability of fatality or serious injury for both vehicles at 

conflict point c with weighted average regression parameters.................................. 28

Figure 11. Equation. Logistic regression model form for nonmotorized road user 

fatality and severe injury based on Tefft (2013)...........................................................28

Figure 12. Equation. Probability of fatality or serious injury for nonmotorized 

collision point c. ...............................................................................................................30

Figure 13. Graphic. Comparison of pedestrian risk curves.........................................31

Figure 14. Equation. Sum of exposure-severity-complexity products for all conflict 

points of type t. ................................................................................................................36

Figure 15. Equation. SSI score for all conflict points of type t. ...................................36

Figure 16. Equation. Intersection SSI score (all conflict points combined). .............37

Figure 17. Equation. Conflicting traffic complexity factor, L1. ....................................38

Figure 18. Equation. Traffic control parameter, atraffic control. .........................................38

Figure 19. Graphic. Minor road left turn to illustrate the SSI traffic control 

parameter.........................................................................................................................40

Figure 20. Equation. Example traffic control parameter calculation. .......................41

Figure 21. Graphic. Example crossing and merging for left-turn movement from 

the minor road.................................................................................................................43

Figure 22. Equation. Example merge score calculation..............................................44

Figure 23. Equation. Conflicting lanes parameter – vehicles......................................44

Figure 24. Graphic. Four crossing and one merging conflict points that receive the 

conflicting lanes complexity parameter associated with the left-turn movement 

from the minor road. ......................................................................................................45

Figure 25. Equation. Conflicting lanes parameter – nonmotorized road users........45

Figure 26. Graphic. Example for nonmotorized movement crossing the minor road.

...........................................................................................................................................46

Figure 27. Equation. Example nonmotorized turn score calculation – eastbound 

approach. ..........................................................................................................................47
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Figure 28. Equation. Example nonmotorized conflicting lanes parameter 

calculation.........................................................................................................................48

Figure 29. Equation. Conflicting speed parameter. .....................................................49

Figure 30. Equation. Nonmotorized movement complexity factor. .........................49

Figure 31. Graphic. Example indirect nonmotorized path at an RCUT. ..................50

Figure 32. Illustration of intersection conditions for Scenario 1................................55

Figure 33. Graphic. Illustration of intersection conditions for Scenario 2. ...............63

Figure 34. Graphic. Illustration of intersection conditions for Scenario 3. ...............70

Figure 35. Graphic. Diagram of movement-based conflict points for Traditional 

Signalized and All-Way Stop Control intersections. ...................................................87

Figure 36. Graphic. Diagram of movement-based conflict points for Traditional 

Minor Road Stop Control intersections. .......................................................................88

Figure 37. Graphic. Diagram of movement-based conflict points for Roundabout 

intersections.....................................................................................................................90

Figure 38. Graphic. Diagram of movement-based conflict points for Signalized 

RCUT intersections.........................................................................................................92

Figure 39. Graphic. Diagram of movement-based conflict points for Unsignalized 

RCUT intersections.........................................................................................................93

Figure 40. Graphic. Diagram of movement-based conflict points for MUT 

intersections.....................................................................................................................95

Figure 41. Graphic. Diagram of movement-based conflict points for Bowtie 

intersections.....................................................................................................................97

Figure 42. Graphic. Diagram of movement-based conflict points for Jughandle 

intersections.....................................................................................................................99

Figure 43. Graphic. Diagram of movement-based conflict points for Quadrant 

Roadway intersections. ................................................................................................. 101

Figure 44. Graphic. Diagram of movement-based conflict points for Partial DLT 

intersections...................................................................................................................103

Figure 45. Graphic. Diagram of movement-based conflict points for Full DLT 

intersections...................................................................................................................105

Figure 46. Graphic. Example calculation conflict points for Traditional Signalized 

intersection.....................................................................................................................110

Figure 47. Graphic. Example calculation conflict points for Roundabout 

intersection.....................................................................................................................110

Figure 48. Graphic. Example calculation conflict points for Unsignalized RCUT 

intersection.....................................................................................................................111

Figure 49. Equation. Exposure index example for traditional signalized intersection 

merging conflict point Trad-1. .....................................................................................112

Figure 50. Equation. Exposure index example for traditional signalized intersection 

crossing conflict point Trad-2.......................................................................................112

Figure 51. Equation. Exposure index example for roundabout intersection crossing 

conflict point RAB-1. .....................................................................................................113
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Figure 52. Equation. Exposure index example for roundabout intersection merging 

conflict point RAB-2. .....................................................................................................113

Figure 53. Equation. Exposure index example for roundabout intersection 

nonmotorized conflict point RAB-3. ...........................................................................113

Figure 54. Equation. Exposure index example for unsignalized RCUT intersection 

merging conflict point RCUT-1....................................................................................114

Figure 55. Equation. Exposure index example for unsignalized RCUT intersection 

diverging conflict point RCUT-2. .................................................................................114

Figure 56. Equation. Exposure index example for unsignalized RCUT intersection 

nonmotorized conflict point RCUT-3. ........................................................................115

Figure 57. Equation. ΔV example for traditional signalized intersection crossing 

conflict point Trad-2......................................................................................................115

Figure 58. Equation. Example of P(FSI) for one vehicle at traditional signalized 

intersection crossing conflict point Trad-2.................................................................116

Figure 59. Equation. Example of probability of fatality or serious injury for both 

vehicles at traditional signalized intersection crossing conflict point Trad-2. ........116

Figure 60. Equation. ΔV example for traditional signalized intersection diverging 

conflict point Trad-3......................................................................................................116

Figure 61. Equation. Example of P(FSI) for one vehicle at traditional signalized 

intersection diverging conflict point Trad-3. ..............................................................117

Figure 62. Equation. Example of P(FSI) for both vehicles at traditional signalized 

intersection diverging conflict point Trad-3. ..............................................................117

Figure 63. Equation. Example of P(FSI) at traditional signalized intersection 

nonmotorized conflict point Trad-4............................................................................117

Figure 64. Equation. ΔV example for roundabout intersection crossing conflict point 

RAB-1. .............................................................................................................................118

Figure 65. Equation. Example of P(FSI) for one vehicle at roundabout intersection 

crossing conflict point RAB-1. ......................................................................................118

Figure 66. Equation. Example of P(FSI) for both vehicles at roundabout intersection 

crossing conflict point RAB-1. ......................................................................................118

Figure 67. Equation. ΔV example for roundabout intersection merging conflict 

point RAB-2....................................................................................................................119

Figure 68. Equation. Example of P(FSI) for one vehicle at roundabout intersection 

merging conflict point RAB-2.......................................................................................119

Figure 69. Equation. Example of P(FSI) for both vehicles at roundabout intersection 

merging conflict point RAB-2. ......................................................................................119

Figure 70. Equation. P(FSI) example for roundabout intersection nonmotorized 

conflict point RAB-3. .....................................................................................................120

Figure 71. Equation. ΔV example for unsignalized RCUT intersection merging 

conflict point RCUT-1. ..................................................................................................120

Figure 72. Equation. Example of P(FSI) for one vehicle at unsignalized RCUT 

intersection merging conflict point RCUT-1..............................................................120
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Figure 73. Equation. Example of P(FSI) for both vehicles at unsignalized RCUT 

intersection merging conflict point RCUT-1. .............................................................121

Figure 74. Equation. ΔV example for unsignalized RCUT intersection merging 

conflict point RCUT-4. ..................................................................................................121

Figure 75. Equation. Example of P(FSI) for one vehicle at unsignalized RCUT 

intersection merging conflict point RCUT-4..............................................................121

Figure 76. Equation. Example of P(FSI) for both vehicles at unsignalized RCUT 

intersection merging conflict point RCUT-4. .............................................................121

Figure 77. Equation. P(FSI) example for roundabout intersection nonmotorized 

conflict point RCUT-3. ..................................................................................................122

Figure 78. Equation. Traffic control parameter example for traditional signalized 

intersection crossing conflict point Trad-1.................................................................123

Figure 79. Equation. Traffic control parameter example for traditional signalized 

intersection left turn crossing conflict point Trad-2..................................................123

Figure 80. Equation. Merge score example for traditional signalized intersection 

merging conflict point Trad-1. .....................................................................................124

Figure 81. Equation. Conflicting lanes parameter example for traditional signalized 

intersection merging conflict point Trad -1................................................................124

Figure 82. Equation. Conflicting lanes parameter example for traditional signalized 

intersection crossing conflict point Trad-2.................................................................125

Figure 83. Equation. Conflicting lanes parameter example for traditional signalized 

intersection crossing conflict point Trad-5.................................................................125

Figure 84. Equation. Conflicting speed parameter example for traditional signalized 

intersection merging conflict point Trad-1.................................................................126

Figure 85. Equation. Conflicting traffic complexity factor example for traditional 

signalized intersection merging conflict point Trad-1...............................................126

Figure 86. Equation. Conflicting traffic complexity factor example for traditional 

signalized intersection crossing conflict point Trad-2. ..............................................127

Figure 87. Equation. Conflicting traffic complexity factor example for traditional 

signalized intersection crossing conflict point Trad-5. ..............................................127

Figure 88. Equation. Merge score example for roundabout intersection merging 

conflict point RAB-2. .....................................................................................................128

Figure 89. Equation. Conflicting speed parameter example for roundabout 

intersection conflict points RAB-1, RAB-2, and RAB-4.............................................128

Figure 90. Equation. Conflicting speed parameter example for roundabout 

intersection nonmotorized conflict point RAB-3.......................................................129

Figure 91. Equation. Conflicting traffic complexity factor example for roundabout 

intersection crossing conflict point RAB-1. ................................................................129

Figure 92. Equation. Conflicting traffic complexity factor example for roundabout 

intersection merging conflict point RAB-2. ................................................................129

Figure 93. Equation. Conflicting traffic complexity factor example for roundabout 

intersection nonmotorized conflict point RAB-3.......................................................129
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Figure 94. Equation. Conflicting traffic complexity factor example for roundabout 

intersection merging conflict point RAB-4. ................................................................129

Figure 95. Equation. Nonmotorized movement complexity factor example for 

roundabout intersection nonmotorized conflict point RAB-3. ................................130

Figure 96. Equation. Traffic control parameter example for unsignalized RCUT 

intersection merging conflict point RCUT-1..............................................................130

Figure 97. Equation. Example of conflicting lanes parameter for unsignalized RCUT 

intersection merging conflict point RCUT-1..............................................................131

Figure 98. Equation. Example of conflicting lanes parameter for unsignalized RCUT 

intersection nonmotorized conflict point RCUT-3....................................................131

Figure 99. Equation. Merge score example for unsignalized RCUT intersection 

merging conflict point RCUT-4....................................................................................132

Figure 100. Equation. Conflicting speed parameter example for unsignalized RCUT 

intersection conflict points RCUT-1, RCUT-2, RCUT-3, and RCUT-4. ..................132

Figure 101. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection merging conflict point RCUT-1..................................................132

Figure 102. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection diverging conflict point RCUT-2. ...............................................132

Figure 103. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection nonmotorized conflict point RCUT-3. .....................................133

Figure 104. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection merging conflict point RCUT-4..................................................133

Figure 105. Equation. Nonmotorized movement complexity factor example for 

unsignalized RCUT intersection conflict point RCUT-3. ..........................................133

Figure 106. Equation. Example conflict point type SSI score for unsignalized RCUT 

crossing conflict points.................................................................................................. 139

Figure 107. Equation. Example conflict point type SSI score for unsignalized RCUT 

merging conflict points. ................................................................................................139

Figure 108. Equation. Example conflict point type SSI score for unsignalized RCUT 

crossing conflict points.................................................................................................. 140

Figure 109. Equation. Example conflict point type SSI score for unsignalized RCUT 

crossing conflict points.................................................................................................. 140

Figure 110. Equation. Example intersection SSI score for unsignalized RCUT. ....140
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ABBREVIATIONS

AADT average annual daily traffic 

ADT average daily traffic

ADS automated driving system

AIS abbreviated injury scale

AWSC all-way stop control

BTCAV base traffic control adjustment value

CAP-X Capacity Analysis for Planning of Junctions

CFI continuous flow intersection

CMF crash modification factor

CRSS Crash Report Sampling System

DOT Department of Transportation 

EB eastbound 

FDLT full displaced left turn

FHWA Federal Highway Administration

FIRST Fatality and Injury Reporting System Tool

FSI fatality or serious injury

F&I fatal and injury

HSM Highway Safety Manual

ICE intersection control evaluation 

KEMM Kinetic Energy Management Model

LT left turn

MAIS Maximum Abbreviated Injury Scale

MOE measure of effectiveness 

mph miles per hour 

MRSC minor road stop control

MUT median U-turn

MUTCD Manual on Uniform Traffic Control Devices

NASS National Automotive Sampling System 

NB northbound 

NCHRP National Cooperative Highway Research Program

NHTSA National Highway Traffic Safety Administration

NM nonmotorized

NSC National Safety Council 

PCDS Pedestrian Crash Data Study 

PDLT partial displaced left turn

PSL posted speed limit

QR quadrant roadway

RAB roundabout 
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RCUT restricted crossing U-turn

ROW right-of-way

RT right turn

RTZ Road to Zero

SB southbound 

SPICE Safety Performance for Intersection Control Evaluation 

SPF safety performance function

SSI Safe System for Intersections

USDOT United States Department of Transportation

V/C volume-to-capacity ratio

WB westbound 

X-KEMM-X Extended Kinetic Energy Management Model for Intersections
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CHAPTER 1: INTRODUCTION

In October 2016, a partnership between the National Safety Council (NSC), National Highway 

Traffic Safety Administration (NHTSA), Federal Highway Administration (FHWA), and Federal 

Motor Carrier Safety Administration announced the Road to Zero (RTZ) coalition (NSC, 

2016). The RTZ coalition seeks to eliminate traffic fatalities in the U.S. by 2050, an aim that 

aligns with the growing number of Vision Zero goals, efforts, and action plans in the U.S. The 

Vision Zero movement, a goal to eliminate traffic fatalities and severe injuries through 

leadership, data analysis, community engagement, and accountability, and other similar programs 

such as Toward Zero Deaths laid the groundwork for RTZ. RTZ is the first national 

partnership of its kind with more than 740 coalition members (Ecola et al., 2018). The RTZ 

coalition was announced around the same time annual traffic fatalities in the U.S. increased

following years of welcomed decline. U.S. traffic fatalities increased 7.2 percent between 2014 

and 2015—the largest percentage increase in nearly 50 years (NHTSA, 2016). U.S. traffic 

fatalities increased another 5.6 percent between 2015 and 2016, totaling 37,806 in 2016 

(NHTSA, 2017). Fortunately, traffic fatalities declined again in 2017 (37,473), 2018 (36,560), and 

2019 (36,120) (NHTSA, 2020a). 

Some countries with Vision Zero initiatives have identified key principles to guide their national 

approaches to road safety management—principles that would achieve a Safe System. Hauer 

(2005) noted that road safety management activities are of two kinds. The first comprises 

activities directed at influencing road safety, including safety-oriented activities of Federal, State, 

and local agencies; safety councils; law enforcement; and other safety stakeholders. Activities 

that occur under the Highway Safety Improvement Program are one example. The second kind 

includes those activities that influence safety, but do not always have safety as their central aim. 

Examples include transportation planning and engineering activities driven by other 

transportation needs, such as mobility/congestion mitigation, reliability, and 

accessibility/connectivity. The Safe System approach applies to both kinds of road safety 

management activities. 
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Chapter 2 of this report provides a thorough discussion of the Safe System approach. The 

concepts of minimizing or preventing crashes between users having large differences in 

direction, speed, and mass are central to a Safe System approach, as are the following 

foundational principles:

• Human beings make mistakes, but the consequences of such mistakes should not result 

in a fatality or serious injury.

• The human body has a limited physiological tolerance of crash forces.

• Roadway designers and users have a shared responsibility in managing crash forces to a 

level that does not result in death or serious injury.

• To implement a Safe System, a “whole-system” approach is required—one that involves 

system designers and managers, vehicle manufacturers, and roadway users, among 

others. 

As planned points of conflict—including conflicts between vehicles and nonmotorized users—

intersections and intersection safety performance have major implications on the safety 

performance of the overall transportation system. More than half of all fatal and injury crashes 

in the U.S. occur at or near intersections (NHTSA, 2020b). In 2019 alone, 10,180 people were 

killed in intersection and intersection-related crashes (NHTSA, 2020c). For these reasons, 

intersections become a primary focus of a Safe System approach.

The practice of intersection planning and design has evolved in recent decades to rethink the 

traditional intersection in search of opportunities to increase multimodal safety and operational 

performance. Design principles once considered alternative (e.g., eliminating direct left turns

with a right-turn/U-turn combination) are now widely accepted as common practice in many 

parts of the country (Hughes et al., 2010). Single isolated applications of innovative intersection 

designs have expanded into corridor-wide deployments as their numerous benefits have 

become better quantified, documented, and understood. Many of these innovative designs are 

now being refined further to better address the needs and concerns of nonmotorized users.

Whereas early installations of innovative intersection designs often relied on unique project 

circumstances, and perhaps an impassioned champion to spearhead their introduction and 

acceptance, many agencies have now taken steps to normalize their consideration in project 

planning processes. A growing number of States have developed or are currently developing 

Intersection Control Evaluation (ICE) policies, procedures, and tools. ICE is a data-driven, 

performance-based framework and approach used to objectively screen alternatives and 

identify an optimal geometric and control solution for an intersection. Although there are 

differences among ICE policies, they are consistent in emphasizing transparency, flexibility, and 

adaptability. 
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In addition to the rise in ICE policies nationwide, other ongoing Federal, State, and local 

intersection initiatives that align well with Safe System principles include crosscutting speed 

management strategies, pedestrian and bicyclist enhancements and integration, systemic safety 

analysis and management, and the strengthening of relationships between project-level impacts 

and program-level safety performance measurement efforts.

The scoping phase of a roadway project typically comprises confirming the project purpose and 

need, initiating the environmental review process, and developing initial design alternatives,

among other activities. It is at this early stage in the project development process where a Safe 

System analysis can be most beneficial. While a project purpose and need statement may center 

upon improving traffic safety, there are other common drivers (e.g., reducing traffic congestion 

and delay, improving network connectivity in support of economic development, replacing 

deficient infrastructure) that are not explicitly linked to reducing fatal and serious injury 

collisions. The results of a Safe System analysis are not intended to be the only factor in 

weighing project alternatives; rather, they should be considered as another factor alongside 

traffic operations, impacts to the natural and human environments, alignment with network 

goals surrounding other modes, constructability and maintenance of traffic, right-of-way and 

construction costs, etc.

The purpose of this report is to provide a technical basis by which practitioners can apply a Safe 

System approach to initially inform intersection planning and design, as well as to conduct inservice assessments of existing intersections. 

Chapter 2 of the report provides background on the concepts and principles of the Safe System 

approach, including contributions by transportation agencies and researchers around the world. 

Chapter 3 is a detailed explanation of a method that practitioners can use today to apply the 

ideas presented in chapter 2 and using readily available data. Chapter 4 showcases application of 

the method to three example intersections and demonstrates how the Safe System approach 

can be integrated into existing agency policies and practices. Finally, chapter 5 provides some 

ideas for future expansion of the method.

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CHAPTER 2: SAFE SYSTEM CONCEPTS

2.1 CHAPTER OBJECTIVE

This chapter presents an overview of fundamental Safe System concepts. It provides a brief 

history of the Safe System approach to road safety management and its tie to Vision Zero. The 

chapter also presents the central Safe System principle of kinetic energy management and the 

need for a whole-system approach to manage kinetic energy to a level that eliminates traffic 

fatalities and serious injuries. The chapter concludes with a framework to outline how road 

planners and designers can begin assessing road infrastructure from a kinetic energy 

management perspective. 

2.2 HISTORY AND BACKGROUND

While some Safe System principles are already evident in various U.S. road safety management 

policies and practices, much of the experience in defining and applying a Safe System approach 

has occurred in a few European countries, Australia, and New Zealand. Sweden was among the 

first countries to employ a Safe System approach to national road safety management. The 

Swedish parliament passed a Road Traffic Safety Bill founded on Vision Zero in 1997, concluding 

that a zero-fatality target was the only justifiable target for road traffic (Johansson, 2009). Vision 

Zero in Sweden is framed as an ethical approach, where it can never be ethically acceptable that 

people are killed or seriously injured when moving within the road transportation system 

(Johansson, 2009). Crashes resulting in less serious injuries and property damage are not 

considered to be an important part of the road safety problem, even if they do result in 

significant societal and agency costs (Johansson, 2009). Some of the early Vision Zero 

documentation noted that a key paradigm shift in implementing Vision Zero is the idea that 

mobility and safety cannot be “traded off” against each other but instead the level of mobility 

follows from achieving the desired level of safety.

Tingvall & Haworth (1999) noted two ways to achieve a Safe System in which there is no 

foreseeable event on the road system that could lead to a loss of life or serious injury:

1. Eliminate the events (i.e., crashes) that lead to harm.

2. Manage the events so that the mechanical forces in the events do not exceed human 

tolerances for harm. 

While Vision Zero describes the goal and Safe System describes the approach, both accept the 

premise that crashes will not be completely avoided, therefore managing the mechanical forces 

in those crashes becomes the priority. Johansson (2009) further elaborated this point, 

explaining that functionalizing Vision Zero means that the “basic parameter in the design of the 
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road transport system” should be to not exceed the “level of violence the human body can 

tolerate without being killed or seriously injured” in the event of a crash (p. 827). Road design 

practices have historically sought to account for variable driver behavior and performance by 

making roads wider to allow, for example, a driver to recover in the event of a lane deviation 

or roadway departure. However, wider roads also tend to result in higher operating speeds, 

increasing the chances of fatalities and serious injuries when crashes do occur because of the 

speeds. Design based on the Safe System approach also accommodates driver error, but in a 

different way, by recognizing that crashes will occur and seeking to manage the kinetic energy 

that transfers to the human body in crashes.

The overarching principle of kinetic energy management is central to the Safe System approach. 

Belin et al. (2012) noted that kinetic energy management has a scientific foundation, citing work 

by DeHaven (1942), Haddon (1980), and Robertson (1983). Vision Zero made this scientific 

foundation the basis of road design and management in Sweden. 

The Netherlands developed its Sustainable Safety vision in the early 1990’s and it was fully 

implemented through a Sustainable Safety Start-Up Program in 1997 (SWOV, 2013). The vision 

aims to prevent traffic fatalities and serious injuries from occurring and has five fundamental 

principles (shown in table 1). 

Table 1. Five sustainable safety principles1

 (Source: SWOV, 2013). 

Sustainable Safety 

Principle

Description

Functionality of roads “Monofunctional” roads (i.e., roads have a single function) as 

either through roads, distributor roads, or access roads in a 

road hierarchy.

Homogeneity of mass 

and/or speed and direction

Equality of speed, direction, and mass at moderate and high 

speeds. 

Predictability of road user 

behavior by recognizable 

road design

Road environment and road user behavior that support road 

user expectations through consistency and continuity of road 

design. 

Forgiveness of road design 

and of road users

Injury limitation through a forgiving road environment and 

anticipation of road user behavior.

State awareness by the 

road user

Ability to assess one’s capability to handle the driving task.

1 Table 2 in the Bikeway Selection Guide presents a summary of intersection characteristics and performance 

considerations for a variety of bikeway types, organized by the Sustainable Safety principles (Schultheiss et al., 

2019).
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A fact sheet on the five sustainable safety principles describes the overarching theme of kinetic 

energy management in the following way (SWOV, 2013):

• Where road users/vehicles with large mass differences use the same traffic space, the 

speeds should be so low that the most vulnerable road users and transport modes 

come out of a crash without any serious injuries. In an ideal situation, this is achieved by 

evoking low speeds through use of the road infrastructure, not by appealing to the road 

users’ individual choices.

• At locations where traffic is at high speeds, different types of road users and vehicles

moving in different directions should be physically separated from each other as much as 

possible to prevent conflicts leading to serious injury. 

Mooren et al. (2011) provided a historical look at how the Safe System approach in Australia, 

first adopted in principle by the Australian Transport Council in 2004, evolved from Vision 

Zero and Sustainable Safety. Central to the Safe System approach in Australia is the concept of 

human tolerance to crash impacts and whole-system efforts spanning roads, speeds, vehicles, 

and people aimed at preventing crashes that result in death or serious injuries (Wooley et al., 

2018). In its National Road Safety Strategy (2011-2020), the Australian Transport Council 

(2011) identifies three guiding principles to their Safe System approach:

1. People make mistakes. Humans will continue to make mistakes and the 

transportation system must accommodate these mistakes. Death or serious injury 

should not be the consequence of user errors.

2. Human physical frailty. There are known physical limits to the amount of force the 

human body can withstand before serious injury.

3. A forgiving road transportation system. A Safe System is one where forces in 

collisions do not exceed the limits of human tolerance. System planners, designers, and 

managers should therefore consider the physical limits of the human body in planning, 

designing, and maintaining roads and vehicles and in managing speeds.

Safer Journeys 2020: New Zealand’s Road Safety Strategy 2010-2020 drew on experience in 

Australia and guided investments in road safety over this period. New Zealand’s vision is “a safe 

road system, increasingly free of death and serious injury” (New Zealand Ministry of Transport, 

2010, p. 10). Safer Journeys takes a Safe System approach to working towards this vision. As 

with other approaches already discussed, human tolerance to crash forces is central to the 

New Zealand Safe System approach, recognizing that this criterion “will need to be the key 

design factor for the system. Crash forces will be managed so they do not exceed these limits” 

(New Zealand Ministry of Transport, 2010, p. 10).
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2.3 KINETIC ENERGY MANAGEMENT MODEL 

Section 2.2 highlighted human tolerance to crash forces, and management of forces to a level 

that does not exceed human tolerance, as central to a Safe System approach. To help advance 

understanding and implementation of this concept, Corben et al. (2010) developed the Kinetic 

Energy Management Model (KEMM) as a conceptual model. Kinetic energy management to a 

level that reduces or eliminates (in the case of a Safe System) the chances of fatalities or serious 

injuries occurs by either avoiding crashes altogether or, in the event of a crash, managing the 

transfer of kinetic energy. 

Corben et al. (2010) created five “layers” to make up the KEMM that are illustrated in figure 1

and described below:

• Layer 1 – Human Biomechanical Tolerance: This layer captures how the human body 

absorbs and distributes kinetic energy during a crash and how this can result in pain 

and/or injuries. Characteristics of this layer can vary as a function of age, gender, size, 

and other characteristics of the user.

• Layer 2 – Transfer of Kinetic Energy to the Human: This layer is comprised of the 

mechanics by which kinetic energy is transferred from the vehicle to humans in a crash. 

For vehicle occupants, safety features such as seat belts and air bags extend the time and 

area over which kinetic energy is transferred, easing the absorption by the body. The 

crashworthiness of vehicles captured in this layer may also depend on the points of 

impact and impact angles. For nonmotorized users, the contact is direct, without much 

chance for increasing the time and area over which the energy is transferred. 

• Layer 3 – Kinetic Energy per Crash: This layer quantifies the level of kinetic energy in a 

crash. Vehicle speeds, relative directions, and vehicle masses are primary drivers of the 

amount of kinetic energy in a crash.

• Layer 4 – Crash Risk given Exposure: This layer focuses on the risk of a crash for 

different levels of exposure. Research has found that crash risk given exposure is 

influenced by a wide range of characteristics of the users, vehicles, roads, and 

environment. 

• Layer 5 – Exposure: For single-vehicle crashes to occur, vehicles must travel over some 

length of road. For multivehicle and nonmotorized crashes to occur, vehicle or user 

paths must conflict. This layer captures the level to which users are exposed to the 

chances of different crash types.

As part of implementing a kinetic energy management approach, planners, designers, and 

managers of the road network are seeking to reduce the risk of crashes occurring by reducing 

exposure (Layer 5) and/or reducing risk for a given level of exposure (Layer 4). In other words, 
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these Layers 4 and 5 determine crash frequency. In the cases where crashes occur, Layers 1, 2, 

and 3 determine crash severity. The numerical ordering of the layers may seem 

counterintuitive, but Corben et al. (2010) note that this is to reinforce that the priority of 

Vision Zero and the Safe System approach is minimizing harm (Layers 1 through 3) as opposed 

to crash elimination (Layers 4 and 5). 

© Corben et al. 2010

Figure 1. Graphic. The five layers of protection in the KEMM. 

2.4 WHOLE-SYSTEM APPROACH 

It is not possible to achieve a Safe System through road infrastructure planning, design, and 

operation alone. While infrastructure characteristics such as geometrics and traffic operation 

and control strategies affect user exposure, crash risk, and crash severity, achieving a Safe 

System depends on contributions from the whole transportation system. This “whole-system 

approach,” as identified by Wooley et al. (2018), considers speeds, people, and vehicles in 

addition to roads.
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Implementing a whole-system approach involves system planners, designers, and operators, 

vehicle manufacturers, emergency services, and system users. This is sometimes represented as 

interacting elements such as “safe roads,” “safe speeds,” “safe vehicles,” “safe road users,” and 

“post-crash care”. This approach is commonly reflected in State Strategic Highway Safety Plan

efforts, which outline strategies for leveraging resources that span engineering, education, 

enforcement, and emergency medical services to collectively address safety challenges and 

reduce fatalities and serious injuries (FHWA, 2017). The remaining sections of this chapter 

briefly address selected topics across the interacting Safe System elements. FHWA has 

incorporated these principles and elements into its Safe System guidance. Figure 2 displays an 

example of this.

Source: FHWA.

Figure 2. Graphic. Portrayal of the Safe System in FHWA’s Safe System Approach 

brochure. 
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2.4.1 Safe Speeds

Speed and speed management practices are central to the level at which a Safe System can be 

achieved. Speed is the key determinant of kinetic energy per crash (i.e., kinetic energy related 

to mass and the square of velocity). Consolidating concepts of the KEMM Layers 1, 2, and 3, 

Tingvall & Haworth (1999) provided the speed thresholds shown in table 2 as representing an 

“inherently safe system.” 

Table 2. Possible long-term maximum travel speeds related to infrastructure, given 

best practices in vehicle design and 100 percent restraint use (Source: Tingvall & 

Haworth, 1999). 

Type of Infrastructure and Traffic Possible Travel Speed, km/hr (miles 

per hour [mph]) 

Locations with possible conflicts between 

pedestrians and cars

30 km/hr (20 mph)2

Intersections with possible side impacts 

between cars

50 km/hr (30 mph)

Roads with possible frontal impacts between 

cars

70 km/hr (45 mph)

Roads with no possibility of a side impact or 

frontal impact (only impact with the 

infrastructure) 

100+ km/hr (60+ mph)

2 Conversions added using “Corresponding Design Speeds in Metric and US Customary Units” from The American 

Association of State Highway and Transportation Officials’ A Policy on Geometric Design of Highways and Streets

(2018).
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Johansson (2009) provided the following “boundary values” and provided guidance for 

“integration” versus “separation3”: 

• Vulnerable road users should not be exposed to motor vehicles at speeds exceeding 30 

km/hr (20 mph).

o If this cannot be satisfied, separate or reduce vehicle speeds to 30 km/hr (20 

mph). 

• For 90-degree crossings, car occupants should not be exposed to other motorized 

vehicles at speeds exceeding 50 km/hr (30 mph).

o If this cannot be satisfied, then separate, reduce the crossing angle, or reduce 

speeds to 50 km/hr (30 mph).

• For oncoming traffic, car occupants should not be exposed to other motorized vehicles 

at speeds exceeding 70 km/hr (45 mph) when the opposing motorized vehicles are of 

the same size or 50 km/hr (30 mph) when the opposing motorized vehicles are of 

considerably different weight.

o If this cannot be satisfied, then separate, homogenize weights, or reduce speeds.

• Car occupants should not be exposed to the roadside at speeds exceeding 70 km/hr (45 

mph). This maximum speed is 50 km/hr (30 mph) if the roadside contains trees or other 

fixed objects.

Achieving the speeds and separation targets outlined by Tingvall & Haworth (1999) and 

Johansson (2009) requires broad political will and societal acceptance. Outside of these targets, 

however, research exists to link vehicle speeds, relative directions, and masses to the chances 

of one or more fatalities or serious injuries in the event of a crash. In addition, speed also plays 

roles in the crash risk for a given level of exposure (Layer 4 in the KEMM). Such information 

could be used by system planners, designers, and operators to inform infrastructure decisions 

in terms of kinetic energy management, even if there is not broader political and societal 

commitment for achieving a Safe System.

3 Johansson (2009) notes that separation is physical separation, usually a barrier, and is never a temporal one (e.g., 

traffic signal timing to separate conflicting movements). Later discussion will address distinctions as part of Safe 

System treatment hierarchies. 
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2.4.2 Safe Road Users

User performance and behavior also play central roles in a Safe System approach to road safety 

management. Of the five “Sustainable Safety Principles” from the Netherlands, two focus on 

user capabilities as well as “user expectations through consistency and continuity of road 

design” (SWOV, 2012, p. 2). Factors such as user experience, workload, fatigue, compliance, 

distraction, and fitness to drive influence the crash risk for a given level of exposure (Layer 4 in 

the KEMM). The characteristics of people involved in crashes are also part of Layer 1 of the 

KEMM, influencing whether a crash that transferred a given amount of kinetic energy to the 

humans involved results in a fatality or serious injury.

Shared responsibility is another Safe System concept that relates to the “safe road users” 

element and to the idea of traffic safety culture across users and transportation agencies. 

Shared responsibility generally means the responsibility for creating and maintaining a Safe 

System falls on both the system managers and the road users. Shared responsibility is laid out in 

three points from Sweden’s Vision Zero (Tingvall & Haworth, 1999):

• The managers of the system are ultimately responsible for the design, operation, and use 

of the road transportation system and therefore responsible for the level of safety 

within the entire system.

• Road users are responsible for following rules set by the system managers for using the 

road system.

• If road users fail to obey these rules due to lack of knowledge, acceptance, or ability, or 

if serious injuries occur, the system managers are responsible for taking necessary steps 

to address people being killed or seriously injured.

2.4.3 Safe Vehicles 

Vehicle design plays a key role in multiple KEMM layers. Vehicle size can affect crash risk for a 

given level of exposure (Layer 4 in the KEMM) due to lane keeping, maneuverability, and 

acceleration and deceleration performance. The presence and type of crash avoidance 

technologies will also affect crash risk per exposure. The size of the vehicle, in addition to 

impact speed and impact angle, is a key factor determining the amount of kinetic energy in a 

crash (Layer 3 in the KEMM). The crashworthiness of vehicles – which may depend on the 

points of impact and impact angles, structural design, and related devices (e.g., seatbelts, 

airbags)—determines how much energy is ultimately transferred to vehicle occupants (Layer 2 

in the KEMM). Vehicle size also determines how much and at which impact points kinetic 

energy is transferred to non-motorized users (also Layers 3 and 2 in the KEMM).
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2.4.4 Safe Roads 

The classification of roads based on their function—and the extent to which their function is 

made evident to users by their design is key to achieving a Safe System. This is most notably the 

case with the Functionality and Predictability principles of Sustainable Safety in the Netherlands 

(see table 1), and the corresponding design features of through roads, distributor roads, and 

access roads in the Netherlands (Wegman et al., 2008). Network-wide road classification and 

self-explaining design approaches consistent with context and function continue to evolve in the 

U.S., a major advancement being the development of a context sensitive functional classification 

system (Stamatiadis et al., 2018), which was incorporated into the latest edition of A Policy on 

Geometric Design for Highways and Streets (AASHTO, 2018). 

In addition to broader classification practices and reinforcement of road function with selfexplaining design, road geometrics and traffic control devices can reduce workload, reinforce 

user expectations, and simplify user decision making (all part of Layer 4 of the KEMM). 

Importantly, geometrics can also determine both the angles and speeds of crashes that do 

occur, thereby influencing the kinetic energy per crash (KEMM Layer 3). 

Tingvall & Haworth (1999) noted that one of the first steps road planners, designers, and 

operators can take is to analyze and/or rank infrastructure from a kinetic energy management 

perspective. They described the ranking primarily through the lens of speed but noted traffic 

volumes are also key to the analysis to show the importance of modifications (i.e., from an 

exposure perspective). Tingvall & Haworth (1999) recognized that the analysis and/or ranking 

can be used for long-term planning, project planning, and as a “performance measure” for 

moving towards an inherently Safe System. 

A framework by Jurewicz et al. (2015), shown in figure 3, is helpful in visualizing road 

infrastructure elements and their connection to kinetic energy management. The framework 

begins with consideration of users, including traffic composition and local demographics, and 

the dimensions of the infrastructure. Ultimately, exposure by user group will play a significant 

role in crash frequency and severity.

The second element of the framework looks at combinations of factors related to the crash 

likelihood given levels of exposure. Conflict points between different road users and how user 

workload and behavior might contribute to crashes occurring at these points are a focus of this 

part of the assessment. Infrastructure elements that emerge as risk or protective factors (e.g., 

absence/presence of channelization, intersection sight distance, right-turn-on-red). 

The third element of the framework is highly relevant to the Safe System approach, looking at 

factors influencing injury severities should a crash occur. These factors include impact speeds, 

impact angles, objects impacted, vehicle characteristics, and the characteristics of who is 

involved in the crashes (i.e., vehicle occupants, pedestrians, cyclists). Most of these factors 
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relate to the amount of kinetic energy passed to vehicle occupants or other road users and 

whether it exceeds thresholds that will increase the probability of fatality or serious injury. This 

framework informed the development of a Safe System for Intersections (SSI) method 

described in chapters 3.

© Austroads 2015. 

Figure 3. Graphic. Risk assessment framework. 

2.4.5 Post-Crash Care

When a crash does occur and result in an injury, injured persons rely on a quick response from 

emergency personnel (FHWA, 2020). The speed of this response may mean the difference 

between a minor injury and a serious injury or fatality occurring as a result of the crash. A 

proper emergency response involves quickly locating and traveling to the site of the crash, 

stabilizing the injured person(s), and efficiently transporting them to the appropriate medical 

facility. 
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In addition to this emergency medical response, the post-crash care element also encompasses 

forensic analysis at the crash site, traffic incident management (to prevent or minimize the 

occurrence of secondary crashes), and other activities.
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CHAPTER 3: SSI METHOD FOR INTERSECTION CONTROL 

EVALUATION

3.1 CHAPTER OBJECTIVE 

The objective of this chapter is to present an analytical SSI methodology that intersection 

planners and designers can readily implement that dovetails with the typical project 

development process— i.e., one that incorporates Safe System principles from chapter 2 and 

relies upon commonly available project-level data. The goal is to provide a technical basis by 

which intersection planners and designers can apply kinetic energy management to common 

intersection projects in the U.S. However, the method’s framework provides flexibility to 

incorporate broader system efforts and characteristics (e.g., users, vehicles, speeds) in the 

future if supporting data are available. Chapter 5 contains ideas for future enhancements. 

This chapter describes the characteristics, data needs, assumptions, computations, and output 

of the SSI method. The information is presented in the context of a Stage 1 Intersection 

Control Evaluation (ICE), at the scoping phase of project development where intersection 

alternatives are analyzed with respect to whether they meet project needs and are practical to 

pursue. The chapter concludes with ideas for possible extensions of the SSI method to a Stage 

2 ICE, a more detailed process that coincides with the preferred alternative selection phase. 

Chapter 4 provides a series of project-specific example applications of the method. 

The framework and method were developed and refined through input from a group of 

stakeholders from FHWA, as well as several State Departments of Transportation (DOTs) and 

local agencies.

3.2 SSI METHOD OVERVIEW 

The SSI method in this chapter represents a first step towards the development of objective 

analysis approaches that capture key Safe System concepts and are implementable by 

intersection planners and designers in the U.S. This method is intended to be adaptable to 

adjustments in its assumptions based on local data or improved knowledge through future 

research. The following paragraphs highlight key characteristics of the SSI method. Subsequent 

sections of this chapter provide additional details and supporting background information. 

Conflict Point Identification and Classification. The kinetic energy transferred to people 

involved in a crash, and the human body’s tolerance to the resulting forces, are central to the 

Safe System approach. The KEMM in chapter 2 identified a variety of factors that affect the 

amount of kinetic energy transferred to people in a crash (Layers 2 and 3). The SSI method 

focuses on vehicle speeds and impact angles for multiple vehicle crashes and vehicle speeds for 

crashes involving nonmotorized users. With these distinctions, the identification and 
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classification of conflict points by conflicting users and conflicting movements are fundamental 

to the SSI method. 

Exposure. Applying Layer 5 of the KEMM to intersections, the likelihood of a crash at a given 

conflict point is related to the number of conflicting movements that pass through that conflict 

point. The SSI method accounts for this concept through an exposure index, which is estimated 

for each conflict point, and represents the product of daily conflicting flows through the conflict 

point. 

Conflict Point Severity. The SSI method defines conflict point severity as an estimate of the 

probability of at least one fatality or serious injury (P(FSI)) resulting from a crash between 

conflicting road users making movements that define the conflict point. The method defines 

serious injury as an injury with a Maximum Abbreviated Injury Scale (MAIS) score of 3 or above, 

which includes serious, severe, critical, and maximum (i.e., fatal) injury classifications (Harmon 

et al., 2018). The computation of the P(FSI) is based on a mechanistic approach to determining 

crash severity based on key crash characteristics (i.e., collision speed, collision angle) and injury 

level as defined by medical and public health professionals. It represents an aggregation of 

Layers 3, 2, and 1 of the KEMM in chapter 2. 

Movement Complexity. Human factors play a key role in the Safe System approach. User 

behavior and performance, along with the workload imposed (or mitigated) by the design and 

operation of the intersection will affect the crash risk per given level of exposure (Layer 4 of 

the KEMM). The SSI method focuses on intersection features that represent the overall 

intersection form and size and that could affect the task complexity for users making specific 

movements (i.e., passing through specific conflict points) at an intersection. The current SSI 

method focuses on the following features in characterizing the complexity of a movement:

• Type of traffic control (applicable to both motorized and nonmotorized users).

• Number of lanes on approaches carrying conflicting traffic that a user must cross or 

merge with (applicable to both motorized and nonmotorized users).

• Speed of conflicting traffic (applicable to both motorized and nonmotorized users).

• Presence of indirect crossing paths and nonintuitive vehicle movements (applicable to 

nonmotorized users only).

The first feature is reliant on user compliance with the traffic control devices at the 

intersection. The latter three features are either a direct result of, or influenced by, 

intersection geometry. 

Results. The results of applying the SSI method include multiple measures of effectiveness 

(MOEs) and a proposed set of SSI scores. The MOEs include the exposure through different 
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conflict point types, the average P(FSI) for different conflict point types, and the average 

complexity for movements passing through different conflict point types. The SSI scores are 

derived based on the combined concepts of conflict points, conflict point severity, exposure, 

and complexity, and are a means to characterize the extent to which an intersection alternative 

in a given context aligns with the principles of a Safe System. The score for an intersection 

control alternative ranges from zero to 100, with higher scores representing higher levels of 

Safe System performance (i.e., lower chances of fatalities and serious injuries). 

The Safe System concepts of kinetic energy transfer and management are grounded in science 

and represent a mechanistic approach to predicting crash injury outcomes. In order to explore 

the relationship of this SSI method to crash-based studies and models, results of the SSI analysis 

were qualitatively compared to results of crash-based predictive methods, particularly crashbased results applicable to fatal and injury (i.e., F&I or KABC) crashes. Given the current focus 

of the SSI method on a Stage 1 ICE application, the qualitative “litmus-test” comparisons 

highlighted general similarities and differences in the relative positions of intersection 

alternatives compared to an existing or future no-build condition. Chapter 4 includes such 

comparisons for three example project scenarios.

Beyond these qualitative comparisons, it was concluded that a conventional validation of the SSI 

score to crash-based predictive models is not yet possible. Notably, current intersection crash 

predictive methods are generally insensitive to intersection characteristics that are key to Safe 

System principles, such as size (in terms of cross sections of the approaching roadways and 

crossing distances), turning volumes, nonmotorized user volumes, and speeds. In addition, 

crash-based predictive methods are based on data from crash reports. Relationships between 

injuries reported as suspected serious injuries (A) on crash reports and serious injuries as 

defined by medical professionals on the MAIS scale may vary from location to location 

depending on crash reporting practices. Crash costs in the USDOT’s Benefit-Cost Analysis 

Guidance for Discretionary Grant Programs suggest that, on average, only a percentage of 

reported crashes coded as suspected serious injuries (A) on crash reports are serious injuries 

as defined by medical professionals on the MAIS scale (USDOT, 2020). 

Continued advancements in crash reporting, injury surveillance (including crash report and 

hospital record linkages), and more widespread availability of vehicle movement and speed data 

will allow more empirical linkages to be made between SSI scores and fatal and serious injury 

crash data. Chapter 5 contains future considerations for linking SSI scores to fatal and serious 

injury crash experience.

Potential Use. The Safe System performance of an intersection, represented by the SSI MOEs 

and the SSI scores, can serve as additional safety metrics to inform the process of screening 

alternatives and identifying an optimal solution for an intersection. A Stage I ICE safety analysis 

provides a basis to characterize safety performance of various alternatives. Performance 
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analyses that occur during a Stage I ICE may rely on both qualitative and quantitative methods. 

Depending on the project intent, the Stage I safety analysis is generally meant to determine one 

of the following: 

• If improving safety is the primary need for a project, does the intersection alternative 

address the safety need by enhancing safety performance?

• If improving safety is not the primary need for a project, does the intersection 

alternative maintain or enhance safety performance?

The SSI MOEs and SSI scores can complement crash-based metrics that come from predictive 

approaches like those in the Highway Safety Manual (HSM) and Safety Performance for 

Intersection Control Evaluation (SPICE) by:

• Focusing on fatalities and serious injuries defined on the MAIS scale and the key 

mechanisms that lead to these injuries (e.g., speeds, collision angles).

• Providing a metric for the safety of nonmotorized users while robust crash-based 

metrics are still in development.

• Communicating tradeoffs between vehicle-vehicle conflict SSI scores and vehiclenonmotorized conflict SSI scores across different intersection alternatives.

The SSI MOEs and SSI scores can also provide metrics that consider safety in the absence of an 

HSM or SPICE analysis. This may be valuable in cases where it is not possible to conduct crashbased analyses on one or more alternatives, such as for atypical or emerging intersection 

concepts that are not-addressed by crash-based methods. With these uses in mind, along with 

the complementary nature of Safe System metrics and crash-based metrics, stakeholders guiding 

the development of future versions of resources such as the HSM may find it beneficial to 

incorporate the SSI method and other types of Safe System assessments. 

3.3 DATA NEEDS

The required and optional traffic and geometric data inputs for implementing the SSI method 

are listed in table 3. The SSI method was developed with typically-available project data in mind 

in order to make it readily useable: speed (specifically, posted speed limit (PSL)), average annual 

daily traffic (AADT) volumes, and the number of through lanes on the intersecting roads. There 

are also several other inputs that, if available, will make the analysis more project-specific. Some 

of these optional inputs (e.g., vehicle speeds for different intersection movements and volumes 

of nonmotorized users) are central to Safe System principles but have not historically been as 

utilized or explored by the research and practitioner communities. The SSI method in this 

chapter offers assumptions and default values for their use, but agency-prescribed or projectspecific values could also be used.
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Table 3. SSI method data inputs. 

Required Operational and 

Geometric Inputs

Other Operational and Geometric Inputs

• Posted speed limit

• AADT volumes

• Number of through lanes in one 

direction on each approach

• Through, right-turning, left-turning, and Uturning movement speeds

• Roundabout entering, circulating, and exiting 

movement speeds

• Nonmotorized AADT volumes

• Directional split

• Turning movement proportions (or turning 

movement AADT volumes)

• Left-turn traffic signal phasing (protected, 

protected/permitted, or permitted)

• Collision angles between conflicting 

movements (may vary from default due to 

intersection skew)

3.4 CONFLICT POINT INDENTIFICATION AND CLASSIFICATION

A conflict point is any location where the paths of road users coincide (FHWA, 2019). A traffic 

conflict is any traffic event involving the interaction of two users where one or both users may 

have to take evasive action to avoid a collision (Glauz & Migletz, 1980). Conflict points are the 

locations on the roadway where traffic conflicts are most likely to occur based upon the typical 

travel paths of road users. By their nature as planned points of conflict, intersections represent 

concentrated groupings of conflict points. 
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The SSI method categorizes conflict points as either crossing, merging, diverging, or 

nonmotorized conflict points, and adapts ideas from Gustafson (2018) with some modifications:

• Crossing conflict point—a location where vehicle paths come from different traffic 

streams, intersect, and then proceed as two separate traffic streams (i.e., two input 

traffic streams and two output traffic streams).

• Merging conflict point—a location where vehicle paths come from different traffic 

streams and converge into the same traffic stream (i.e., two input traffic streams and 

one output traffic stream). 

• Diverging conflict point—a location where vehicle paths diverge from a single traffic 

stream into two separate traffic streams (i.e., one input traffic stream and two output 

traffic streams). 

• Nonmotorized conflict point—a location where a vehicle path crosses a 

pedestrian/cyclist path. 

The SSI method currently assumes that bicyclists follow the same paths as pedestrians through 

intersections. Future enhancements to the method could incorporate additional layers of 

vehicle-bicycle conflict points that depend on the selection of bicycle accommodation through 

the intersection, as outlined in the Bikeway Selection Guide (Schultheiss et al., 2019). Additional 

discussion of these enhancements is contained in section 3.8 and chapter 5. The SSI method 

also does not consider rear-end conflicts that result from speed differentials that arise from 

traffic congestion or deceleration and stopping due to traffic control devices (i.e., yield signs, 

stop signs, and traffic signals). It does consider rear-end conflicts that result from speed 

differentials at diverging conflict points where vehicles making different movements have 

different speeds.

Conflict points can be identified on a movement basis or on a lane-by-lane basis. Since this initial 

SSI method is intended for use in project scoping, and exact lane arrangements may not be 

known at this project development stage, the SSI method identifies conflict points on a 

movement basis. Figure 4 shows an example of the movement-based conflict points for a 

Median U-Turn (MUT) intersection. Movement-based conflict points are not dependent on the 

number of lanes or presence of auxiliary lanes for an alternative; rather, they are disaggregated 

by each movement combination. For example, there are two different nonmotorized conflict 

points associated with a nonmotorized road user crossing the receiving lanes of a minor road 

approach in figure 4: one associated with right-turning vehicles from the major road, and one 

associated with through-moving vehicles on the minor road. Appendix A illustrates movementbased conflict points for various intersection alternatives that State agencies with ICE policies 

commonly consider as part of a Stage I ICE. 
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Source: FHWA. 

Figure 4. Graphic. Conflict points at a MUT intersection.

3.5 EXPOSURE 

The likelihood of a crash at a given conflict point is related to the number of conflicting 

movements that pass through that conflict point. The SSI method accounts for this concept of 

exposure through an exposure index, which is estimated for each conflict point. The SSI 

method adopts an exposure index definition from Hakkert & Mahalel (1978). The exposure 

index at conflict point c, Ic, is simply the product of vehicle or nonmotorized user daily volumes 

through that conflict point (Q1,c and Q2,c), illustrated in figure 5.

Figure 5. Equation. Exposure of index for conflict point c. 

The values for Q1,c and Q2,c are determined using the daily volumes, turning movements, and 

intersection geometry.

The individual conflict point exposure indices can be summed across all conflict points of a 

certain type at an intersection to compute the total exposure for each conflict point type (e.g., 
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total exposure through all crossing conflict points, total exposure through all merging conflict 

points, etc.). Appendix B provides example exposure index calculations.

3.6 CONFLICT POINT SEVERITY 

The SSI method defines conflict point severity as the estimated probability of at least one fatal 

or serious injury, P(FSI), as a result of a crash between conflicting road users making the typical 

movements that define the conflict point. The SSI method defines injury severity on the 

abbreviated injury scale (AIS), which is based on information provided by trained medical 

professionals following an assessment of a patient’s injuries at the hospital (Burch et al., 2014). 

AIS classifications of injury severity may be more consistently coded within a State, across 

States, and over time than injury determinations made by police officers at the scenes of 

crashes. The ability to make a direct correlation to a person’s probability of survival (shown in 

table 4) is another benefit of the AIS scale.

Table 4. AIS injury codes and corresponding probability of death (Harmon, et al., 

2018). 

AIS 

Code

Injury Example Injury Probability of 

Death (%)

0 None No injury 0 

1 Minor Superficial laceration 0 

2 Moderate Fractured sternum 1 – 2 

3 Serious Open humerus fracture 8 – 10 

4 Severe Perforated trachea 5 – 50 

5 Critical Ruptured liver with tissue loss 5 – 50 

6 Maximum Total severance of aorta 100 

AIS scores can characterize individual injuries on a person (e.g., an AIS score for different 

regions of the body injured in a crash). The MAIS is the most severe AIS across all body 

regions. Burch et al. noted that the trauma research community relies on AIS codes to analyze 

injury data and has accepted a serious injury definition as an AIS score of 3 or higher (Burch et 

al., 2014). The SSI method therefore defines fatal and serious injuries as injuries with MAIS 

scores of 3 or above. 

The following sections detail the calculations used to estimate conflict point severity for the SSI 

method. The first section focuses on vehicle-vehicle conflict points (cveh), which include crossing, 

merging, and diverging conflict points. The second section focuses on vehicle-nonmotorized

conflict points (cped). The general approach outlined in these two sections follows the same 

general approach as in the Austroads Extended Kinetic Energy Management Model (X-KEMMX) (Jurewicz et al., 2017), except for some differences in data sources and assumptions. 

Appendix B provides example conflict point severity calculations. 
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3.6.1 Vehicle-to-Vehicle Conflict Points

The SSI method estimates P(FSI) at crossing, merging, and diverging conflict points using an 

estimated speed for each conflicting movement and an estimated angle between conflicting 

movements. The SSI method assumes that the angle between conflicting movements is 

representative of the angle of collisions that would occur at the conflict point. This collision 

angle for conflict point cveh, φveh, is defined as the angle at which two vehicles (U1 and U2) would 

collide at that conflict point, measured from the vehicle U1’s longitudinal axis (see figure 6). 

Using this convention, a collision angle of zero degrees is a rear-end collision; a collision angle 

of 180 degrees is a head-on collision; and collision angles of 90 degrees and 270 degrees are 

right-angle collisions.

© Austroads 2017

Figure 6. Graphic. Diagram illustrating various angles of collision. 

The SSI method estimates P(FSI) at each vehicle-vehicle conflict point using a model developed 

by Joksch (1993) (as described in Evans, 1994). This model predicts P(FSI) for occupants of each 

individual vehicle (i.e., U1 and U2) involved in a vehicle-vehicle collision. The SSI method applies 

the model at each crossing, merging, and diverging conflict point. Figure 7 illustrates the 
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application of the Joksch (1993) model to the SSI context.

Figure 7. Equation. Probability of fatality or serious injury for one vehicle at 

crossing, merging, or diverging conflict point cveh. 

In this model, ΔVU_i,c_veh represents the change in the velocity vector of vehicle Ui between a 

point in time just before the crash and a point in time just after the crash. The SSI method 

employs an approach to estimate ΔVU_i,c_veh based on the speeds of vehicles U1 and U2 at each 

crossing, merging, and diverging conflict point (SU1,c_veh and SU2,c_veh) and φc_veh, shown in figure 8. 

Figure 8. Equation. Delta-V for vehicle Ui at conflict point cveh.

This approach for estimating ΔVU_i,c_veh assumes conservation of momentum and equal masses of 

both colliding vehicles. Under these assumptions, “delta-V” for both vehicles is the same (i.e. 

ΔVU_1,c_veh = ΔVU_2,c_veh). Evans (1994) estimated different values for α and k in figure 7 for different 

combinations of occupant restraint use and crash severity using 1982-1991 crash data from the 

National Automotive Sampling System (NASS). Evans (1994) only included crashes in his 

analysis where “delta-V” was estimated and coded through a structural analysis of the vehicle 

deformation produced by the crash; table 5 summarizes his results.

Table 5. Regression parameters as computed by Evans (1994).

Fatality 

(unbelted)

Fatality 

(belted)

Fatality 

(frontal)

Fatality 

(all)

Serious 

Injury1

(unbelted)

Serious 

Injury1

(belted)

α 70.61 69.18 66.01 70.75 66.09 67.43 

k 3.54 4.57 2.22 2.62 3.80 4.51 

S.E. for 

k 0.18 0.25 0.11 0.17 0.17 0.32 

1

Evans (1994) uses the term “severe injuries,” and notes that the term indicates 

injuries rated at 3 or greater on the AIS.

The SSI method requires this approach to be more general, without consideration of occupant 

restraint use, so its development comprised an estimation of weighted averages of the two 

regression parameters, α and k, to combine the different scenarios that Evans had considered. 

The process involved querying four years of crash data (2014 to 2017) from NHTSA’s Fatality 

 

 
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and Injury Reporting System Tool (FIRST). FIRST allows users to query several crash databases 

including the Fatality Analysis and Reporting System (FARS), which contains records of every 

fatal crash in the U.S., and the Crash Report Sampling System (CRSS), which contains data from 

nationally representative police reported crashes of all severities. FIRST also contains data 

elements that allow the user to filter based on the restraint use.

The next step created distributions based on crash severity and restraint use with the FIRST 

data, matching the scenarios Evans developed in table 5. 

These crash distributions yielded estimates for:

• Percent of fatal and injury crashes that result in a fatality.

• Percent of fatal and injury crashes that result in no fatality.

• Percent of fatalities in which the person was belted.

• Percent of injuries in which the person was belted.

The final step used these four percentages to compute weighted averages of the values Evans

calculated, which resulted in α = 67.29 and k = 3.79. Incorporating these values into figure 7

results in the P(FSI) relationship illustrated by figure 9.

Source: FHWA

Figure 9. Graphic. P(FSI) for occupants of one vehicle versus delta-V of that 

vehicle during a crash.
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After estimating P(FSI) for each vehicle, the SSI method estimates P(FSI) at the crash-level 

(considering occupants of both vehicles) using figure 10.

Figure 10. Equation. Probability of fatality or serious injury for both vehicles at 

conflict point c with weighted average regression parameters.

3.6.2 Nonmotorized Conflict Points

The SSI method estimates the severity of nonmotorized-vehicle conflict points based on the 

speed of vehicles traveling through the nonmotorized conflict point. The approach is based on a 

combination of data from Tefft (2013) and Chidester & Isenberg (2001). Tefft (2013) modeled 

the probability of pedestrian fatality or severe injury based on the estimated vehicle speed at 

impact using data from NHTSA’s NASS Pedestrian Crash Data Study (PCDS). Tefft (2013) 

noted these data are the most recent U.S. data of pedestrian crashes where impact speed was 

estimated using crash reconstruction methods. The study did not directly present the model 

details but did present the results in tabular form, as shown in table 6. 

Table 6. Estimated impact speeds at which risk of severe injury and death reach 

specified levels, adapted from Tefft (2013).

Risk 

(%) 

Severe Injurya

Impact Speed 

(mph)

95% Confidence 

Interval

10 17.1 (14.4 – 20.0)

25 24.9 (22.4 – 27.6)

50 33.0 (29.9 – 37.2)

75 40.8 (36.5 – 47.3)

90 48.1 (42.4 – 57.1) a

Severe injury is defined as a MAIS score of 4 or 

greater and includes fatality.

Tefft’s (2013) numbers can be represented by a logistic regression model, such as that shown in

figure 11.

Figure 11. Equation. Logistic regression model form for nonmotorized road user 

fatality and severe injury based on Tefft (2013).
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In this functional form, β1 and β2 are regression coefficients, and V is the estimated vehicle 

speed at impact in mph. Transforming the logistic regression model into a linear form allows 

least squares linear regression to determine the unknown coefficients that best fit the Tefft 

(2013) results. However, additional adjustments to the results are needed.

First, Tefft’s model defined fatality and severe injury as a MAIS score of 4 and above. Therefore, 

to remain consistent with the definition of fatality and serious injury used in the vehicle-vehicle 

conflict point severity method detailed in the previous section, the model derived directly from 

Tefft’s (2013) results had to be adjusted to account for MAIS scores of 3 and above. This 

modification was informed by a general distribution of MAIS data for pedestrian crashes in the 

U.S., in addition to data from the NHTSA PCDS (Chidester & Isenberg, 2001).The distribution 

of MAIS scores presented in Chidester & Isenberg (2001) shows that the percentage of 

pedestrian crashes with MAIS 3 and above is 15 percentage points higher than the percentage 

of pedestrian crashes with MAIS 4 and above. 

Since Chidester & Isenburg (2001) did not present the MAIS percentages as a function of speed, 

the 15 percentage-point increase had to be distributed across the speeds in table 6, thereby 

increasing the corresponding risk at each speed. The distribution was determined using a table 

in the Tefft (2013) study that grouped the number and percentage of crashes by ranges of 

impact speeds (see table 7). The percentages from table 7 were applied to the overall 15 

percentage-point increase for each respective row in table 6 to arrive at a risk adjustment. 

Table 8 provides the calculations and results. 

Table 7. Percentage of crashes by impact speed from Tefft (2013).

Impact Speed 

(mph)

Percentage of Crashes 

(%) 

< 15.0 52% 

15.0-24.9 25% 

25.0-34.9 12% 

35.0+ 11% 
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Table 8. MAIS4+ to MAIS3+ risk adjustments and results.

Risk of 

MAIS 4+ 

(%) 

Impact 

Speed (mph)

Table 7

Risk Adjustment Estimated Risk of 

MAIS 3+ (%)

10 17.1 15% * 52% = 7.8% 17.8 

25 24.9 15% * 25% = 3.8% 28.8 

50 33 15% * 12% = 1.8% 51.8 

75 40.8 15% * 7.3% = 1.1%1 76.1 

90 48.1 15% * 3.7% = 0.6%1 90.6 

1

Two-thirds of the 11% of crashes at 35 mph+ impacts speeds are applied to 

the 40.8 mph row; one-third to the 48.1 mph row. 

The adjusted risk percentages and the impact speeds were used to determine the unknown 

coefficients in the logistic regression model in figure 11. Figure 12 represents the final model 

used by the SSI method for estimating P(FSI) at nonmotorized conflict points.

Figure 12. Equation. Probability of fatality or serious injury for nonmotorized

collision point c. 

The lines in figure 13 represent the different nonmotorized risk curves discussed in this section. 

The solid line denotes the modified Tefft model developed for use in the SSI method. It 

generally predicts a higher risk of nonmotorized fatality or serious injury than the other curves, 

except at high speed values. This result is intuitive, as these higher-speed crashes are likely to 

result in injuries above MAIS 4, and therefore adding the MAIS 3 category does not alter the 

curve at higher speeds.
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Source: FHWA

Figure 13. Graphic. Comparison of pedestrian risk curves.

While both the Tefft (2013) and Chidester & Isenberg (2001) studies focused on pedestrian 

crashes, the SSI method applies the severity curve here to both pedestrians and cyclists as part 

of the previously highlighted SSI assumption that bicyclists follow the same paths as pedestrians 

through intersections.

3.6.3 Speed and Angle Assumptions

Application of the P(FSI) models to determine conflict point severity requires estimates of 

vehicle speeds through each conflict point and – for vehicle-to-vehicle conflicts – an estimate of 

the collision angle between the vehicles. 

Vehicle Speeds. There is little existing research into speed prediction at intersections, 

especially in differentiating speeds of different movements and maneuvers at different points 

throughout the vehicle path. The research that does exist (mostly for right-turning movements) 

requires geometric inputs that are generally not available during a project scoping stage. For 

this reason, the SSI method adopts a simplified set of speed assumptions to cover the different 

vehicle maneuvers at intersections. These assumptions can be adjusted based on local 

knowledge or any data that become available in the future.
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First, each vehicle movement at a conflict point is assigned to a speed category. Table 9 

illustrates the assignment of speed categories for the movements at eight of the different 

intersection configurations included in the SSI library of intersection types in appendix A: 1) 

signalized traditional, 2) minor road stop control (MRSC) traditional, 3) all-way stop control 

(AWSC) traditional, 4) signalized restricted crossing U-turn (RCUT), 5) unsignalized RCUT, 6) 

median U-turn (MUT), 7) jughandle, and 8) quadrant roadway (QR). The speed category 

assignment is based on a combination of factors including the intersection type, traffic control 

type, and movement. Movements that are not controlled by traffic signals or stop signs 

(typically uncontrolled major road movements) are assigned the speed category that 

corresponds to that movement. For example, the major road through movement at a MRSC 

intersection would be assigned the “major through” speed category. If the movement in 

question originates on an approach operating under stop or signal control, the movement is 

assigned to that respective speed category. For example, the left turn movement from the 

minor road at a signalized traditional intersection (i.e., minor left movement in the first column 

of table 9) is assigned to the signal control speed category. The exceptions are movements 

from the major road at a signalized intersection. The SSI method makes a simplifying 

assumption of assigning these movements to the uncontrolled category. For example, a through 

movement on the major road at a signalized traditional intersection (i.e., major through) will be 

assigned to the “major through” speed category, based on the assumption that most vehicles on 

the major road arrive during a green signal indication and are not making different movements 

from a stopped position. However, this assumption could be adjusted to reflect different 

conditions.
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Table 9. Speed category assignments for different intersection types.

Movement Traffic Control Type

Signalized 

Traditional

MRSC 

Traditional

AWSC 

Traditional

Signalized 

RCUT

Unsignalized 

RCUT

MUT Jughandle Quadrant 

Roadway

Major through Major 

through

Major 

through

Stop Major 

through

Major through Major 

through

Major 

through

Major 

through

Major left turn (LT) Major left Major left Stop Major left Major left Major left Major left --

Major right turn 

(RT)

Major right Major right Stop Major right Major right Major 

right

Major right Major right

Minor through Signal Stop Stop -- -- Signal Signal Signal

Minor left Signal Stop Stop -- -- -- Signal --

Minor right Signal Stop Stop Signal Stop Signal Signal Signal

Major U-turn -- -- -- Signal Stop Signal -- --

Jughandle left -- -- -- -- -- -- Signal --

Jughandle right -- -- -- -- -- -- Signal --

Minor through at 

jughandle 

-- -- -- -- -- -- Minor 

through

--

Minor through at 

QR

-- -- -- -- -- -- -- Minor 

through

Minor LT into QR -- -- -- -- -- -- -- Minor left

Minor RT into QR -- -- -- -- -- -- -- Minor 

right

Major LT into QR -- -- -- -- -- -- -- Major left

Major RT into QR -- -- -- -- -- -- -- Major right

Left turns from QR -- -- -- -- -- -- -- Signal

Right turns from QR -- -- -- -- -- -- -- Signal
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Next, each speed category is matched to the corresponding speed values in table 10. 

There are two speed values that apply to movements governed by stop control and 

therefore assigned to the stop control speed category: stop near-side and stop far-side. 

The stop control near-side speed value in table 10 is applied to movements made from 

stop control at conflict points on the side of the intersection near the stop bar from 

which the vehicle has accelerated. The stop control far-side speed value in table 10 is 

applied to movements made from stop control at conflict points on the side of the 

intersection opposite the stop bar, where the vehicle has had more opportunity to 

accelerate. 

There are two similar speed values for the signal control speed category: signal control 

near-side and signal control far-side. These speed values are only applied to minor road 

approaches at signalized intersections. This assumes that minor road traffic will typically 

arrive on a red signal indication, accelerating from a stop when the signal changes to 

green.

Finally, there are three specific speed values for roundabouts – entering, circulating, and 

exiting – due to their unique geometric characteristics and inherent effects on vehicle 

speed, as well as their distinct arrangement of vehicle movements.

Agencies are encouraged to assess the speed value ranges in table 10 and adjust them 

based on local knowledge or available intersection speed data.

Table 10. Assumed speed values for SSI methodology.

Speed Category Speed (mph)

Low End High End

Major through 0.9 * Major PSL 1.1 * Major PSL

Major left 10 30 

Major right 10 20 

Minor through 0.7 * Minor PSL Minor PSL

Minor left 10 30 

Minor right 10 20 

Stop control near-side 10 20 

Stop control far-side 20 30 

Signal control near-side 10 20 

Signal control far-side 20 30 

Roundabout entering 10 20 

Roundabout circulating 15 25 

Roundabout exiting 20 30 

For vehicle-nonmotorized conflict points, the SSI method only requires the vehicle speed 

at the conflict point to compute P(FSI). This speed is assigned as described above based on 

the vehicle movement involved at the conflict point.
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This approach to determining vehicle speeds may not apply perfectly to every potential 

traffic control situation or vehicle maneuver at a given intersection. Users of the method 

are encouraged to adjust the speeds as they see fit to better reflect the conditions of the 

intersection being analyzed. Additionally, ongoing and future research may inform 

improvements to these speed assumptions, such as through increased understanding of 

the effects of different traffic control types, traffic volumes, and approach geometry on 

vehicle speeds. Chapter 5 contains additional discussion of speed data and modeling needs 

to support future SSI enhancements.

Collision Angles. The collision angle used to compute conflict point severity in the SSI 

method is based on the convention established in Jurewicz et al. (2017) (see figure 6). To 

facilitate efficient application to a variety of intersections, the SSI method uses five 

categories of potential collision types with assumed collision angles, as shown in table 11. 

Table 11. Collision angle assumptions for SSI methodology.

Collision Type Typical Collision Angle Range 

(deg)

Crossing – Broadside 80 – 100 (or 260 – 280) 

Crossing – Left Turn 220 – 240 

Crossing – Roundabout 45 – 75 

Merging 30 – 60 (or 300 – 330) 

Diverging 0 – 20 (or 340 – 360) 

These collision angles are based on typical movement arrangements at intersections. They 

do not account for intersection skew or other context-specific geometrics but could be 

adjusted if that information is available.

3.7 MOVEMENT COMPLEXITY, USER WORKLOAD, AND THE SSI 

SCORE

The information provided in sections 3.4 to 3.6 and appendix A present steps to identify 

and classify conflict points for different intersection alternatives, determine user exposure 

at different conflict point types, and quantify conflict point severity. Measures derived 

from these steps can begin to give intersection planners and designers a general idea of 

how an intersection alternative aligns with Safe System principles. Possible MOEs to this 

point include the level of exposure for each conflict point type combined with the average 

P(FSI) for those same conflict point types. 

Concepts that consider user behavior and performance, along with the workload imposed 

(or mitigated) by the design and operation of the intersection will also affect the crash risk 

per given level of exposure (Layer 4 of the KEMM). The SSI method therefore considers 

intersection features that represent the overall intersection form and size and that could 
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affect the task complexity for users making specific movements (i.e., passing through 

specific conflict points) at an intersection. Section 3.7 presents a series of concepts 

intended to represent the level of complexity for different movements through an 

intersection. The SSI method assumes that intersection attributes associated with lower 

levels of complexity for all users brings an intersection into closer alignment with a Safe 

System. 

Factors representing movement complexity are combined with the concepts of exposure 

and severity through an SSI score. The SSI score has a range of zero to 100, with 100 

representing combinations of project contexts and intersection alternatives that are 

closest to a Safe System for the users considered by this method. The method produces 

an SSI score for each conflict point type (i.e., crossing, merging, diverging, nonmotorized) 

as well as for the intersection.

The first step in determining the SSI score is to compute the sum of the exposureseverity-complexity products for all individual conflict points of a specific type, Et (see

figure 14). This is done for all four conflict point types to create Ecrossing, Emerging, Ediverging, and 

Enonmotorized. 

Figure 14. Equation. Sum of exposure-severity-complexity products for all 

conflict points of type t. 

L1 and L2 are complexity factors that are described in sections 3.7.2 and 3.7.3 of this 

chapter. 

The second step is to estimate the SSI scores for the combined conflict points of type 

t, SSIt.

Figure 15. Equation. SSI score for all conflict points of type t. 

The parameter z, within the structure of figure 15, is a constant that scales the sum of 

exposure-severity-complexity products to the SSI score that falls between zero and 100. 

It is a feature of the method and is based on the distribution of values for the sum of 

exposure-severity-complexity products across a wide range of different intersection 

alternatives and project contexts. If the process and assumptions in this report are 

followed to develop the exposure-severity-complexity products for an intersection, the 
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value for z is 1.37 x 107. The value would not be calibrated or adjusted to local conditions 

in this case. 

The third and final step is to estimate the SSI score for the intersection, SSIint, considering 

all conflict points combined. This step is performed using the equation in figure 16.

Figure 16. Equation. Intersection SSI score (all conflict points combined). 

The following sections discuss the two complexity factors, L1 and L2, that are part of the 

exposure-severity-complexity product. L1 addresses complexity added by the 

characteristics of conflicting traffic, which can be moderated by the type of traffic control. 

L2 addresses additional complexity specific to nonmotorized movements through the 

intersection. 

3.7.1 Conflict Point Application of the Complexity Factors

The complexity concepts in this section are applicable to a movement level (e.g., left turn 

from major road, through movement on minor road, etc.). However, the notation in 

figure 14 shows that the two complexity factors, L1 and L2, are applied at the individual 

conflict point level i. This is done by applying the complexity factor for a movement to the 

applicable conflict points along that same movement. The following sections will illustrate 

this movement-level analysis and corresponding conflict point application. Appendix B 

provides example calculations and applications of the two complexity factors.

3.7.2 Conflicting Traffic Complexity Factor

The first intersection complexity factor, L1, captures complexity added by the 

characteristics of conflicting traffic, while accounting for how much of that complexity is 

moderated by the type of traffic control. L1 applies to both vehicle and nonmotorized

movements through an intersection and therefore to the vehicle-vehicle and vehiclenonmotorized conflict points along those movements. 

For each possible movement, L1 is computed as the product of three parameters that 

represent the characteristics of the traffic control and conflicting traffic for that 

movement (shown in figure 17).
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Figure 17. Equation. Conflicting traffic complexity factor, L1. 

In figure 17, the three parameters on the right side of the equation represent the 

increased or decreased complexity due to the type of traffic control, the number of 

conflicting lanes, and the speed of conflicting traffic for different movements through the 

intersection. The remainder of section 3.7.2 describes each of these parameters in detail.

Traffic Control. The first parameter included in the conflicting traffic complexity factor, 

L1, is the traffic control parameter, atraffic control. This parameter accounts for the reduction in 

complexity that occurs when certain movements are separated in time due to the type of 

traffic control. As an example, the left-turning movement from the minor road could be a 

complex movement depending on the number of lanes and speed of conflicting traffic on 

the major road approaches. However, if the intersection is signal controlled, the minor 

and major road movements will not operate simultaneously, significantly decreasing the 

complexity of making the left-turn movement from the minor road. The traffic control 

parameter in this case will be a value less than one, reducing the conflicting traffic 

complexity factor for the left-turning movement from the minor road. 

The traffic control parameter takes the form in figure 18, with BTCAV representing the 

base traffic control adjustment value and f representing a weight given to the use of traffic 

control devices, and user compliance to those traffic control devices, to separate conflicts.

Figure 18. Equation. Traffic control parameter, atraffic control. 

In the SSI method, potential values for BTCAV are informed by Crash Modification Factor 

(CMF) values for stop control, protected, and protected/permitted traffic signal control 

operations. The traffic control categories and corresponding BTCAV assumed ranges are:

• Permitted or yield control: 1.0. 

• Protected/Permitted: 0.6-0.9 (based on CMF Clearinghouse ID 4270). 

• Protected: 0.005-0.015 (based on CMF ID 333). 

• Stop-Control: 0.4-0.5 (based on CMF ID 309, inverse). 

The type of control for each movement and the corresponding BTCAV applied to each 

conflict point along a movement is determined based on the type of conflict separation 

achieved by the traffic control. For example, figure 19 shows a left turn movement from 

the minor road of a traditional, four-leg intersection. For illustration purposes, the 
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discussion will consider this left-turn movement if the intersection operated as MRSC or if 

the intersection was signalized. There are eight conflict points along this left turn 

movement from the minor road:

• One diverging conflict point between the left-turn and through movement from 

the same minor road approach.

o Since the SSI method does not currently incorporate effects of traffic 

control devices on rear-end conflicts, the value for atraffic control = BTCAV = 1 

for this diverging conflict point, regardless of whether the intersection is 

MRSC or signalized.

• Two nonmotorized conflict points: one between the left-turn and nonmotorized 

road users crossing the same minor road approach and one between the left-turn 

and nonmotorized road users crossing the major road.

o For MRSC, since the minor road left turn of interest is coming from a stopcontrolled approach, both nonmotorized conflict points are assigned to the 

stop control category.

o For signalized operation, the conflict point between the minor road left 

turn and nonmotorized road users crossing the minor road approach is 

assigned to the protected category, since the signal control will separate 

these two movements in time. The conflict point between the minor road 

left turn and nonmotorized road users crossing the major road approach 

will be assigned to either the permitted, protected/permitted, or protected 

category, depending on the type of phasing for the left turn movement.

• Four crossing conflict points: one each with the through movement and the left 

turn from the near-side major road approach, one with the left turn from the farside major road approach, and one with the opposing through movement on the 

minor road.

o For MRSC, all four crossing conflict points are assigned to the stop control 

category.

o For signalized operation, the three crossing conflict points between the 

minor road left turn and the through and left turn movements from the 

major road are assigned to the protected category, since the signal control 

will separate these movements in time. The crossing conflict point between 

the minor road left turn and the opposing minor road through will be 

assigned to either the permitted, protected/permitted, or protected 

category, depending on the type of phasing for the left turn movement.
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• One merging conflict point with the far-side major road through movement.

o For MRSC, the merging conflict point is assigned to the stop control 

category.

o For signalized operation, the merging conflict point is assigned to the 

protected category, since the signal control will separate these movements 

in time.

Source: FHWA

Figure 19. Graphic. Minor road left turn to illustrate the SSI traffic control 

parameter.

Based on the foundational Safe System principles in chapter 2, the SSI method provides 

the option of reducing the BTCAV using a weight, f, less than one. This would mean that 

the traffic control parameter would not reduce movement complexity by the full value of 

the BTCAV. The traffic control parameter is dependent on user compliance with traffic 

control devices. The Safe System literature in chapter 2 suggests that traffic control 

devices would receive a “lower weight” as part of a Safe System analysis. For example, 

Jurewicz et al. (2015) conclude that separating movements by signalization provides only 

low to moderate levels of alignment with a Safe System at an intersection. Johansson 

(2009) asserts that separation in a Safe System is physical separation of conflicting 

movements and is not a temporal one, such as with traffic signal timing. Example 

calculations in this document use a traffic control parameter weight, f, of 0.5. Agencies can 

adjust values for BTCAV and f based on local conditions and experience.
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As one example calculation, when the two movements that define a given conflict point 

are controlled by protected-permitted signal control (e.g., left-turns from the major road 

and opposing through movements), the corresponding BTCAV is 0.6-0.9 (assume 0.85 for 

this example). The traffic control parameter for this conflict point is computed using figure 

18. The example calculation that incorporates a weight of 0.5 is shown in figure 20. 

Figure 20. Equation. Example traffic control parameter calculation.

Conflicting Lanes. The conflicting lanes parameter, aconflcting lanes, of the conflicting traffic 

complexity factor considers the overall intersection size and the potential workload on 

road users as they make specific movements through the intersection. The parameter is 

based on the number of lanes that carry conflicting traffic movements for a selected 

movement of interest. For any selected movement in the following “list of movements”, 

conflicting traffic movements are those that cross or merge with the selected movement 

of interest and are also listed above the selected movement on the list:

1. Major through and right turn.

2. Major left turn.

3. Minor through and right turn. 

4. Minor left turn. 

5. Nonmotorized. 

Placing nonmotorized movements at the bottom of this list prioritizes nonmotorized

movements in the SSI analysis when characterizing the complexity of an intersection. 

Although nonmotorized road users typically have higher priority from a regulatory or 

traffic control perspective, their vulnerability in a crash, along with uncertainty about 

driver awareness of their presence at any given time, may require nonmotorized road 

users to be aware of conflicting traffic movements that are lower-priority from a 

regulatory or traffic control perspective. 

In the SSI method, the complexity of each movement at an intersection is scored based on 

how many conflicting major and minor approaching traffic streams the movement crosses 

and/or merges with and the number of through lanes on those approaches (i.e., excluding 

turn lanes, whose presence may or may not be known during a Stage I ICE). To illustrate 

this concept, there are three through lanes on the eastbound approach in figure 21, three

through lanes on the westbound approach, and one through lane each on the north and 
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southbound approaches. Subsequent paragraphs detail the steps of calculating the 

conflicting lanes parameter, first for vehicle-vehicle conflict points and then for 

nonmotorized-vehicle conflict points, and continue to reference the illustrative example in 

figure 21. 

Beginning with vehicle-vehicle conflict points, the first step in computing the conflicting 

lanes parameter for each movement is to determine the movement’s cross score. A 

movement’s cross score is the maximum sum of through lanes (i.e., 1, 2, 3...) carrying

conflicting traffic on the intersection approaches that a movement crosses without refuge 

during the movement. 

Using the example of the left-turning movement from the minor road in figure 21, this 

movement crosses the approaching traffic stream on the near-side of the major road—

three lanes in this case—plus the opposing through traffic stream—one lane in this case—

on the minor road. A median is not present to provide refuge to the left-turning vehicle 

and allow a two-stage movement. Thus, the resulting cross score for the left turn from 

the minor road is 4. If there was a median wide enough to allow a two-stage movement, 

the cross score for this movement would be 3. Median details may not be available during 

a Stage 1 ICE, but medians are an inherent part of some intersection alternatives. 

Appendix A provides default median assumptions contained within the intersection 

diagrams and Stage 1 calculations of this report. 
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Source: FHWA

Figure 21. Graphic. Example crossing and merging for left-turn movement 

from the minor road.

The second step in computing the conflicting lanes parameter for each vehicular 

movement is to determine the movement’s merge score. The merge score considers the 

number of lanes on the intersection approach that the subject movement is merging with, 

NM. Table 12 contains the equations for computing the merge score for different values of 

NM. 

Table 12. Merge score for conflicting lanes parameter. 

Number of Through Lanes 

on Merge Approach (NM) 

Merge Score

1 M 

2 M(1 + W2) 

3+ M[1 + W2 + W3+(NM – 2)]
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In table 12, M represents a binary indicator variable capturing whether or not the merge 

score applies to the subject movement. The value for M will be 1 for any of the following 

movements:

• A turning movement merging with a through movement that is higher than the turning 

movement on the list of movements (e.g., a right turn from the minor road merging 

with a through movement on the major road).

• A movement entering the circulatory roadway of a roundabout and merging with 

traffic that is in already in the circulatory roadway and continuing around the 

circulatory roadway.

• A movement that approaches a roundabout and turns right merging with traffic that is 

exiting the roundabout in that same direction.

The value for M will be 0 otherwise. W2 and W3+ represent the merging weights for Lane 

2 (the lane adjacent to the lane the driver is merging into) and Lane 3+ (any lanes beyond 

Lane 2). These weights represent the relative level of attention needed from the driver 

for selecting a gap. The default values for W2 and W3+ are 0.75 and 0.5, respectively. Lane 

1 (the lane the driver is merging into) has a merging weight of 1 because the driver would 

generally be paying full attention to traffic in the lane they are merging into.

Building on the example in figure 21, the left-turning movement from the minor road is 

merging with traffic from a major road approach having three through traffic lanes. The 

merge score in this case is shown in figure 22.

Figure 22. Equation. Example merge score calculation.

The merge score is added to the cross score to determine the overall conflicting lanes 

parameter, aconflicting lanes(see figure 23). 

Figure 23. Equation. Conflicting lanes parameter – vehicles.

In this vehicle-vehicle conflict point example, the conflicting lanes parameter for the leftturning movement from the minor road in figure 21 is 6.25. The number 6.25 is aconflicting lanes

when computing the conflicting traffic complexity factor for the individual crossing and 

merging conflict points along this left-turn movement and where the left-turn movement

is the lower movement on the list of movements. These five conflict points for the left-
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turning movement from the minor road in figure 21 are identified with darker linework in 

figure 24. 

Source: FHWA

Figure 24. Graphic. Four crossing and one merging conflict points that receive 

the conflicting lanes complexity parameter associated with the left-turn 

movement from the minor road.

The conflicting lanes parameter for each nonmotorized movement is based on similar 

concepts, but with some differences in the details. The conflicting lanes parameter for a 

nonmotorized movement is the nonmotorized movement’s cross score plus a total

nonmotorized turn score, as shown in figure 25.

Figure 25. Equation. Conflicting lanes parameter – nonmotorized road users. 

A nonmotorized movement’s cross score is the maximum number of through lanes that 

the nonmotorized movement must cross without refuge. The total nonmotorized turn 

score considers complexity added by pedestrians or cyclists checking for oncoming 

vehicles from approaches parallel to their movement. In the case of the traditional 
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intersection example shown in figure 26, a nonmotorized road user crossing the south leg 

of the intersection must cross the northbound through lane and the southbound through 

lane (turn lanes are not considered in the current SSI method). There is no refuge island. 

This results in a value of 2 for this nonmotorized movement’s cross score. The 

nonmotorized road user is also monitoring the eastbound and westbound approaches to 

determine if any vehicles may be turning from those approaches into the nonmotorized 

road user’s path (i.e., a right turn from the eastbound approach or a left turn from the 

westbound approach).

Source: FHWA

Figure 26. Graphic. Example for nonmotorized movement crossing the minor 

road.

To account for the complexity added by approaching traffic on the parallel approaches, 

table 13 presents a series of equations for computing the approach nonmotorized turn 

score for each approach that is parallel to the subject nonmotorized movement. The 
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equations are similar to the merge score equations in table 12, and utilize the same 

assumed weight values, where W2 is 0.75 and W3+ is 0.5. In the case of potential left turns 

from the westbound approach in figure 26, the pedestrian or cyclist would be mostly

focused on identifying potential left-turning vehicles in the leftmost lane (Lane 1), but may 

also be monitoring the subsequent lanes (Lane 2 and Lane 3) to lesser degrees for vehicles 

that may be changing lanes as they approach the intersection to turn. 

Table 13. Nonmotorized turn score for conflicting lanes complexity

parameter. 

Number of Through Lanes 

on Parallel Approach (NP) 

Approach Nonmotorized

Turn Score

1 1 

2 1 + W2

3+ 1 + W2 + W3+(NP – 2) 

In table 13, NP represents the number of through lanes on the subject approach parallel to 

the nonmotorized movement in question. An approach nonmotorized turn score should 

be computed for each parallel approach separately, in case there are different numbers of 

through lanes on the approaches. The total nonmotorized turn score is the sum of the 

individual approach nonmotorized turn scores. 

Continuing with the example of a pedestrian or cyclist crossing the south approach in 

figure 26, the nonmotorized road user is surveying the eastbound and westbound 

approaches, which have three through lanes each (NP = 3). The approach nonmotorized

turn score associated with the eastbound approach is computed as shown in figure 27. 

Because the westbound approach has the same number of through lanes in this example, 

the approach nonmotorized turn score calculation associated with the westbound 

approach is the same. Therefore, the total nonmotorized turn score is 2.25 + 2.25 = 4.5.

Figure 27. Equation. Example nonmotorized turn score calculation – 

eastbound approach.

It follows that the nonmotorized conflicting lanes parameter for the subject nonmotorized

movement is computed as shown in figure 28. This value of 6.5 would be applied to the 

nonmotorized conflict points along the subject nonmotorized movement in figure 26. 
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Figure 28. Equation. Example nonmotorized conflicting lanes parameter 

calculation.

If a nonmotorized road user refuge area separated the northbound minor road approach 

lane from the southbound receiving lane (enough for a two-stage crossing), the 

nonmotorized movement’s cross score would be one and the conflicting lanes parameter 

would be 5.5.

Speed of Conflicting Traffic. The third parameter that is part of the conflicting traffic 

complexity factor is the conflicting speed parameter, aconflcting speed, which also considers an 

aspect of road user workload. When a road user is attempting to navigate an intersection, 

the user must judge the speeds of conflicting traffic at the intersection when searching for 

a gap. Higher speeds of conflicting traffic increase the complexity of this task. 

The conflicting vehicle speed for any movement is the highest speed of all the conflicting

traffic streams, with conflicting traffic streams being those that cross or merge with the 

subject movement and are higher on the list of movements. Using the example of the leftturning movement from the minor road in figure 21, the conflicting vehicle speed, Vc, is 

the highest of the speeds of the traffic streams from the near-side major roadway

(through and left-turn movements), far-side major roadway (through and left-turn 

movements), and opposing minor road approach (through movement). Using the speed 

assumptions in table 10, the highest conflicting vehicle speed is the speed of the through 

movement on the major road, which is somewhere between 90 to 110 percent of the 

major road posted speed limit. This rule applies to nonmotorized-vehicle conflict points as 

well as vehicle-vehicle conflict points. For the subject nonmotorized movement in figure 

26, the conflicting vehicle speed, Vc, is the highest of the speeds of the traffic streams from 

the near-side major roadway (right-turn movements), far-side major roadway (left-turn 

movements), northbound minor road approach (through, left-turn, and right-turn 

movements), and southbound minor road approach (through movement).

Research shows that a 10-percent reduction in vehicle speed is associated with a 15-

percent reduction in crash likelihood (Campbell, et al., 2012). Since this is a relative 

adjustment, arbitrarily setting the speed of 60 mph as a conflicting speed parameter of 1 

and applying that relationship results in figure 29 for the conflicting speed parameter, 

aconflicting speed, where Vc is the conflicting vehicle speed. This value of aconflicting speed is applied 

when computing the conflicting traffic complexity factor for individual crossing, merging, 

or nonmotorized conflict points. 
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Figure 29. Equation. Conflicting speed parameter.

3.7.3 Nonmotorized Movement Complexity Factor

The second complexity factor is the nonmotorized complexity factor, L2. This factor 

accounts for indirect and nonintuitive movements at an intersection that may present 

additional complexity for pedestrians and cyclists. The nonmotorized movement 

complexity factor takes a value of either 1, 2, or 3 based on two different indicators: an 

indirect paths indicator, iindirect, and a nonintuitive motor vehicle movements indicator, 

inonintuitive. If neither indicator applies to a given nonmotorized movement, then the value of 

the nonmotorized movement complexity factor is 1 for that movement and its 

corresponding conflict points. If one indicator applies, the value is 2, and if both indicators 

apply, the value is 3. The nonmotorized movement complexity factor is therefore 

computed according to figure 30.

Figure 30. Equation. Nonmotorized movement complexity factor.

The indirect paths indicator applies to any nonmotorized movement where the pedestrian 

or cyclist is required to traverse a path other than their intended direction of travel (i.e., 

an indirect path). As an example, consider a nonmotorized movement from the bottom 

right quadrant to the top right quadrant of the RCUT shown in figure 31; because the 

typical Z-type crossing here requires a nonmotorized road user to travel outside of their 

desired direction, the indirect paths indicator applies.
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Source: FHWA

Figure 31. Graphic. Example indirect nonmotorized path at an RCUT.

The nonintuitive motor vehicle movements indicator, inonintuitive, is applied to any 

nonmotorized movements that cross nonintuitive motor vehicle movements. An example 

of when the nonintuitive motor vehicle movements indicator is equal to one would be the 

nonmotorized movements on some or all approaches of a displaced left turn intersection, 

where motor vehicle traffic could alternate direction several times over the course of the 

nonmotorized road user crossing. 

3.8 EXPANDING THE SSI LIBRARY OF INTERSECTION CONCEPTS 

Appendix A contains various intersection alternatives that State agencies with ICE policies 

commonly consider as part of a Stage I ICE. The library could be expanded to include 

other intersection alternatives of interest, including at-grade crossroad ramp terminals, 

and then the same Stage I ICE SSI methodology could be applied to those new 

alternatives. 

The alternatives in appendix A currently assume typical nonmotorized paths and assume 

that bicyclists follow the same paths as pedestrians. Given the significant impact of 

pedestrian and bicyclist considerations in a Safe System approach, future efforts should 

focus on how to incorporate more detailed analyses of pedestrians and bicyclists into a 

Stage 1 ICE. One promising approach is to develop multiple alternatives for a single 

intersection type that differ by pedestrian and bicycle accommodation. Instead of one 
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RCUT, the library could contain, for example, RCUT with sidewalk and on-street bike 

lanes, RCUT with shared use paths, RCUT with sidewalks and separated bike lanes and a 

protected intersection, etc. Such concepts would not only support a more informative 

pedestrian and bicycle SSI analysis, but would advance intersection planning and design 

practice in general with earlier consideration and pedestrian and bicyclist alternatives.

The Bikeway Selection Guide is one resource for informing the development of new 

intersection alternatives within each intersection type that are distinguished by pedestrian 

and bicycle facilities (Schultheiss et al., 2019). National Cooperative Highway Research 

Program (NCHRP) Research Report 926, Guidance to Improve Pedestrian and Bicyclist Safety 

at Intersections, is one example of a group of recently published and ongoing research 

efforts contributing to the development of these concepts (Sanders et al., 2020). 

3.9 SSI EXTENSIONS TO STAGE 2 ICE – ALTERNATIVE SELECTION

A Stage 2 ICE is intended to differentiate among the intersection alternatives brought 

forward from the Stage I analysis that is the focus of this report. Stage 2 ICE is conducted 

as part of preliminary engineering and includes the estimating of environmental, utility, and 

right-of-way impacts. Analyses that occur in a Stage 2 ICE are at a level of detail that 

allows objective comparisons of alternatives to each other.

The concepts in this chapter can be extended for a Stage 2 ICE. In addition to the features 

that are part of the SSI Stage 1 analysis, the following present practical extensions of the 

SSI method for Stage 2 ICE:

• Incorporating the presence, number, and type of turn lanes, which would be 

expected to have the following impacts: 

o Decreasing the speed differences between through and turning vehicles at 

the diverging conflict points on intersection approaches.

o Increasing crossing scores that are part of the conflicting traffic complexity 

factor.

o Possibly changing turning speed and traffic control assumptions, depending 

on the type of turning lanes (e.g., separate free-flow right turning roadway 

at a signalized intersection).

• Incorporating additional detail that becomes available with respect to signal 

operation (e.g., left-turn operation, right-turn-on-red restrictions, leading 

pedestrian intervals).
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• Incorporating additional detail on the presence and size of medians and pedestrian 

and bicyclist refuge at the intersection, which could impact:

o Pedestrian refuge during crossing movement.

o Vehicle refuge and the introduction of multi-stage vehicle movements 

through the intersection.

• Representing any potential impacts of intersection skew on the collision angles in 

table 11.

The section 3.7 recommendation to consider different intersection alternatives within 

each intersection type that are distinguished by pedestrian and bicycle facilities also applies 

to a Stage 2 ICE.
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CHAPTER 4: EXAMPLE PROJECT APPLICATIONS

This chapter presents three example applications of the SSI method to individual 

intersections that are part of realistic project scenarios. The three project scenarios 

represent different area types, traffic volumes, lane configurations, traffic control types, 

and nonmotorized user volumes: 

• Scenario 1—a suburban signalized intersection of two medium-volume roads with 

moderate use by nonmotorized users. 

• Scenario 2—a rural unsignalized intersection of two-lane roads with few 

nonmotorized users.

• Scenario 3—an urban signalized intersection of two high-volume roads with heavy 

use by nonmotorized users.

Chapter 3 presented typical ranges for two inputs to the SSI method: vehicle speeds and 

collision angles. The examples laid out in the remainder of this chapter assume specific 

values from within these ranges, displayed in table 14 and table 15. 

Table 14. Speed values used in SSI method examples.

Speed Category Speed (mph)

Major through Major PSL

Major left 20 

Major right 15 

Minor through 0.85 * Minor PSL

Minor left 20 

Minor right 15 

Stop control near-side 15 

Stop control far-side 25 

Signal control near-side 15 

Signal control far-side 25 

Roundabout entering 20 

Roundabout circulating 25 

Roundabout exiting 30 
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Table 15. Collision angle values used in SSI method examples.

Collision Type Collision Angle (deg)

Crossing – Broadside 90 (or 270)

Crossing – Left Turn 230 

Crossing – Roundabout 60 

Merging 45 (or 315)

Diverging 10 (or 350)

Following a basic description of the conditions at each intersection, the examples discuss 

Stage 1 ICE alternatives screening based on capacity, crash-based safety performance 

assessments, and SSI results. 

4.1 SCENARIO 1

4.1.1 Intersection Conditions

Scenario 1 is a suburban signalized intersection of a four-lane arterial and a two-lane 

collector and is depicted in figure 32. The intersection is being studied as part of a 

broader corridor planning effort. Design year traffic volumes are estimated at 25,000 and 

20,000 vehicles per day, respectively, on the major and minor roads. The posted speed 

limits are 45 mph on the major road and 35 mph on the minor. There are sidewalk 

facilities along all approaches, and the intersection serves a moderate number of 

nonmotorized users.
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Source: FHWA

Figure 32. Illustration of intersection conditions for Scenario 1.

The information in table 16 summarizes the key intersection attributes. 
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Table 16. Intersection attributes for Scenario 1. 

Item Input Value

Area type Suburban 

Functional classification – major Minor arterial

Functional classification – minor Collector

Design year AADT – major 25,000 

Design year AADT – minor 20,000 

Number of thru lanes – major 4 

Number of thru lanes – minor 2 

Traffic control type Signalized

Posted speed limit – major 45 

Posted speed limit – minor 35 

Nonmotorized average daily 

traffic (ADT) 2,400 

A Stage 1 ICE analysis of this intersection occurred as part of the corridor planning study. 

The following sections summarize the capacity, crash-based safety performance, and SSI 

analysis results. Note that the results of these analyses are presented using the 

intersection type names from the SSI library of intersections (contained in appendix A). In 

some cases, the analysis results come from other tools that may use slightly different 

naming conventions.

4.1.2 Capacity-Based Feasibility Review

The Stage 1 ICE alternatives screening used the Capacity Analysis for Planning of Junctions 

(CAP-X) tool. CAP-X is a spreadsheet-based tool for determining the operational 

performance of different intersection types. It primarily assesses intersection types by 

computing the volume-to-capacity (V/C) ratio given vehicle volume inputs and intersection 

lane arrangements. Table 17 summarizes the CAP-X results and provides the overall V/C 

ratio and V/C ranking. Based on these results and the general lane arrangements of the 

corridor, the minor road stop control (MRSC) traditional, all-way stop control (AWSC) 

traditional, and 1x1 roundabout are dropped from further consideration. 
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Table 17. CAP-X results for Scenario 1.

Type of Intersection

Overall 

V/C 

Ratio

V/C 

Ranking

Quadrant Roadway 0.25 1 

Full Displaced Left Turn (FDLT) 0.27 2 

Median U-Turn (MUT) 0.31 T3

2x2 Roundabout 0.31 T3

Partial Displaced Left Turn (PDLT) 0.32 5 

Bowtie 0.40 6 

Signalized Traditional (existing) 0.44 7 

Signalized Restricted Crossing U-Turn 

(RCUT) 0.48 8 

2x1 Roundabout 0.53 9 

1x1 Roundabout 0.63 10 

Unsignalized Restricted Crossing U-Turn 

(RCUT) 0.85 11 

All-Way Stop Control (AWSC) Traditional 1.36 12 

Minor Road Stop Control (MRSC) 

Traditional 1.38 13 

Jughandle* -- --

* The Jughandle intersection is not included in CAP-X, but it has the capacity to handle high 

intersection volumes.

4.1.3 Crash-Based Safety Performance Review

The Stage 1 ICE alternatives screening also used the SPICE tool. SPICE is a spreadsheetbased tool for determining the safety performance of different intersection types using 

crash-based predictive analysis. 

The information in table 18 summarizes the SPICE results for Scenario 1. The SPICE 

output contains the predicted number of crashes for the design year for both total 

crashes (i.e., all types and severities) and fatal and injury crashes unless there is not an 

appropriate safety performance function (SPF) available, as in the case of the 2x2 

roundabout. The results show that all the intersection types for which there are 

predictive methods available have fewer total and fewer fatal and injury crashes than the 

signalized traditional intersection that is the no-build condition. Based on these SPICE 

results, no additional intersections are dropped from consideration. 
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Table 18. SPICE results for Scenario 1.

Control Strategy

Predicted Crashes in 

Design Year 

(crashes/year)

Fatal & 

Injury Total

Unsignalized RCUT 0.53 1.69 

MUT 1.24 4.08 

Jughandle 1.31 3.55 

Signalized RCUT 1.38 4.08 

FDLT 1.55 4.22 

Signalized Traditional (existing) 1.77 4.80

2x2 Roundabout No SPF 2.29 

2x1 Roundabout* -- --

Quadrant Roadway* -- --

PDLT* -- --

Bowtie* -- --

* These intersection types are not included in SPICE but are included in the SSI 

library of intersections. 

4.1.4 SSI Methodology and Results

This section presents the results of applying the SSI method in chapter 3 to the Scenario 1 

example. Table 19 summarizes the SSI scores for the feasible intersection alternatives 

from appendix A. The list of intersection alternatives is ordered based on the overall 

Intersection SSI Score, showing that the 2x1 roundabout has the highest (i.e., best) SSI 

score. There are seven intersection design alternatives that indicate an improved SSI 

score compared to the existing, signalized traditional intersection: 2x1 roundabout, MUT, 

2x2 roundabout, signalized RCUT, bowtie, quadrant roadway, and jughandle. 

The four rightmost columns in table 19 contain the SSI scores for individual conflict point 

types. The seven alternatives listed above have improved SSI scores for the nonmotorized

conflict points compared to the signalized traditional intersection (which is the 

existing/no-build condition). There are eight options that have improved crossing conflict 

SSI scores compared to the no-build alternative: 2x1 roundabout, MUT, 2x2 roundabout, 

signalized RCUT, bowtie, unsignalized RCUT, FDLT, and PDLT. These designs reroute 

one or more movements at the intersection, removing crossing conflict points, reducing 
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vehicle speeds and angles at crossing conflict points, or both. As expected, the range of 

nonmotorized and crossing Conflict Type SSI Scores is lower than the merging and 

diverging scores, indicating that nonmotorized and crossing conflicts are more likely to 

lead to fatalities and serious injuries than merging and diverging conflicts. The zero SSI 

scores for nonmotorized conflict points at several of the alternatives reflect the relatively 

higher probability of a nonmotorized road user fatality or serious injury if there was a 

nonmotorized-vehicle crash at this intersection under the speed assumptions of the SSI 

method. 

Table 19. SSI score results for Scenario 1. 

Intersection 

Type

Intersection 

SSI Score

Conflict Type SSI Scores

Nonmotorized Crossing Merging Diverging

2x1 

Roundabout 52 8 93 98 100 

MUT 44 10 52 83 88 

2x2 

Roundabout 42 4 90 98 100 

Signalized 

RCUT 40 5 74 77 86 

Bowtie 31 4 23 94 96 

Quadrant 

Roadway 30 6 14 93 94 

Jughandle 27 3 18 93 97 

Signalized 

Traditional 

(existing)

24 2 19 93 100

Unsignalized 

RCUT 19 0 65 69 86 

FDLT 10 0 32 91 97 

PDLT 9 0 26 91 97 

The information in table 20 provides additional context to help interpret the SSI scores. 

The intersection alternatives are listed in the same order as in table 19. The left portion 

of the table displays the exposure for each conflict point type relative to the existing/nobuild alternative (where “NM” stands for nonmotorized). In other words, the exposure 

for the existing intersection design (in this case, the signalized traditional intersection) is 
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set to one and the exposure for the other intersection types is shown relative to it. 

Values greater than one represent higher exposure at those conflict point types while 

values less than one represent lower exposure. 

The middle portion of the table shows the average P(FSI) for each conflict point type. 

Together, these two metrics provide insights to the contributions of exposure and 

severity to the SSI scores in table 19. Note, for example, that while the signalized RCUT 

has a slightly higher average P(FSI) for crossing conflict points than the signalized 

traditional (0.09 versus 0.04)4, exposure at crossing conflict points is 81 percent lower for 

the signalized RCUT compared to the signalized traditional. Other intersection 

alternatives with a similar pattern include the MUT, PDLT, and FDLT. The roundabout 

alternatives have equal exposure at crossing conflict points to the traditional intersection

but much lower chance of fatality or serious injury for these crossing conflict points due 

to the lower speeds and shallower angles of the crossing conflicts.

The rightmost portion of the table shows the average complexity adjustment for each 

conflict point type. This is computed by summing the products of the complexity factors

(L1 and L2) for each conflict point of a certain type and then dividing that sum of products 

by the number of conflict points of that particular type. It shows that most of the 

intersection types have less user complexity for nonmotorized and crossing conflict points 

than the existing signalized traditional intersection. The additional complexity of the PDLT 

and FDLT intersections for pedestrians and cyclists result in these intersection 

alternatives receiving a lower SSI score given the projected nonmotorized volumes 

crossing at-grade at this intersection.

4 The movement-based conflict point diagrams in appendix A show that the average P(FSI) for the RCUT is 

based on its two crossing conflict points. Both are defined by left-turning and through moving vehicles on 

the major road. The signalized traditional intersection has more crossing conflict points (16 versus 2), with 

some occurring at lower speeds. This lowers the average P(FSI) across all crossing conflict points. 
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Table 20. Relative exposure, average P(FSI), and average complexity adjustment results for Scenario 1.

Intersection 

Type

Relative Exposure

(Relative to Existing) Average P(FSI) Average Complexity Adjustment

NM Cross Merge Diverge NM Cross Merge Diverge NM Cross Merge Diverge

2x1 

Roundabout 1.00 1.00 1.51 1.49 0.33 0.00 0.00 0.00 1.83 0.92 0.99 1.00 

MUT 1.25 0.84 2.58 2.88 0.33 0.04 0.01 0.00 1.04 0.84 0.77 1.00 

2x2 

Roundabout 1.00 1.00 1.51 1.49 0.33 0.00 0.00 0.00 2.44 1.22 1.15 1.00 

Signalized 

RCUT 1.22 0.19 3.31 3.25 0.28 0.09 0.01 0.00 1.73 0.84 0.77 1.00 

Bowtie 1.25 0.94 2.46 2.43 0.34 0.04 0.01 0.00 1.84 1.68 1.01 1.00 

Quadrant 

Roadway 1.00 1.34 1.57 1.77 0.27 0.04 0.01 0.00 1.84 1.34 0.96 1.00 

Jughandle 1.07 1.11 1.28 1.20 0.29 0.04 0.01 0.00 2.08 2.00 1.23 1.00 

Signalized 

Traditional 

(existing)

1.00 1.00 1.00 1.00 0.29 0.04 0.01 0.00 3.15 2.03 1.53 1.00

Unsignalized 

RCUT 1.22 0.19 3.31 3.25 0.31 0.09 0.01 0.00 3.06 1.21 1.11 1.00 

FDLT 1.00 0.89 1.00 1.00 0.32 0.04 0.01 0.00 4.37 1.30 2.01 1.00 

PDLT 1.00 0.96 1.00 1.00 0.32 0.04 0.01 0.00 4.74 1.70 2.12 1.00 
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4.2 SCENARIO 2

4.2.1 Intersection Conditions

Scenario 2 is a rural unsignalized intersection of a two-lane minor arterial and a two-lane minor 

collector and is depicted in figure 33. The minor road is under stop control, while the major 

road is uncontrolled. The intersection was included in a list of locations considered for safety 

improvement based on the last three years of observed crash data compared to expected crash 

counts at this site. Design year traffic volumes are estimated at 10,000 and 2,500 vehicles per 

day, respectively, on the major and minor roads. The posted speed limit on both roadways is 

55 mph. The intersection serves a low number of nonmotorized users.
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Source: FHWA

Figure 33. Graphic. Illustration of intersection conditions for Scenario 2.
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The information in table 21 summarizes the key intersection attributes. 

Table 21. Intersection attributes for Scenario 2. 

Item Input Value

Area type Rural

Functional classification – major Minor arterial

Functional classification – minor Minor collector

Design year AADT – major 10,000 

Design year AADT – minor 2,500 

Number of thru lanes – major 2 

Number of thru lanes – minor 2 

Traffic control type Minor road STOP

Posted speed limit – major 55 

Posted speed limit – minor 55 

Nonmotorized ADT 100 

A Stage 1 ICE analysis of this intersection occurred as part of the safety improvement study. 

The following sections summarize the capacity, crash-based safety performance, and SSI analysis 

results. 

4.2.2 Capacity-Based Feasibility Review

The information in table 22 summarizes the CAP-X results and provides the overall V/C ratio 

and V/C ranking. Based on life cycle costs and Manual on Uniform Traffic Control Devices 

(MUTCD) traffic signal warrants, the low volumes at the intersection do not justify signal 

control. As such, all the signalized intersection types are dropped from further consideration.
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Table 22. CAP-X results for Scenario 2.

Type of Intersection

Overall 

V/C 

Ratio

V/C 

Ranking

Unsignalized RCUT 0.06 1 

FDLT 0.08 T2

2x1 Roundabout 0.08 T2

2x1 Roundabout 0.08 T2

Quadrant Roadway 0.09 T5

PDLT 0.09 T5

MRSC Traditional (existing) 0.11 7 

Signalized RCUT 0.15 T8

MUT 0.15 T8

1x1 Roundabout 0.16 T10 

Signalized Traditional 0.16 T10 

Bowtie 0.18 12 

AWSC Traditional 0.41 13 

Jughandle* -- --

* The Jughandle intersection is not included in CAP-X but it has the capacity to handle high 

intersection volumes.

4.2.3 Crash-Based Safety Performance Review

The information in table 23 summarizes the SPICE results for Scenario 2. The results show that 

all the intersection types for which there are predictive methods available have fewer predicted 

total and fewer predicted fatal and injury crashes than the MRSC traditional intersection (which 

is the existing condition). Based on the SPICE results, no additional intersections are dropped 

from consideration.
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Table 23. SPICE results for Scenario 2.

Control Strategy

Predicted Crashes in 

Design Year 

(crashes/year)

Fatal & 

Injury Total

1x1 Roundabout 0.25 1.59 

Unsignalized RCUT 0.53 1.69 

MRSC Traditional (existing) 1.15 2.61

2x2 Roundabout No SPF 2.29 

2x1 Roundabout* -- --

AWSC Traditional* -- --

* These intersection types are not included in SPICE but are included in the 

SSI library of intersections. 

4.2.4 SSI Methodology and Results

The information in table 24 summarizes the SSI scores for the remaining intersection 

alternatives under consideration for Scenario 2 from the library of SSI intersection alternatives 

in appendix A. It shows there are 5 intersection design alternatives under consideration that 

indicate improved Safe System performance compared to the existing MRSC traditional 

intersection design: the 1x1, 2x1, and 2x2 roundabouts, along with the AWSC traditional and 

unsignalized RCUT intersections. 

The individual conflict type SSI scores in table 24 illustrate the Safe System performance of the 

intersection design in more detail. All the considered alternatives perform better from an SSI 

score perspective than the existing design for nonmotorized and crossing conflict points. The 

unsignalized RCUT scores worse than the existing MRSC traditional intersection for merging 

and diverging conflict points. This is because the unsignalized RCUT intersection design results 

in additional merging and diverging conflict points and exposure at those conflict points due to 

the way that turning movements are routed at the intersection. Overall, the merging and 

diverging conflict type SSI scores are high across all intersection designs, indicating lower 

probabilities of fatalities and serious injuries from these conflict types.

The range of intersection SSI scores across the alternatives is on the high end (i.e., closer to 

100) when compared to the results from Scenario 1. This is because the volumes at the 

intersection (both motorized and nonmotorized) are significantly lower in this scenario, 

decreasing the exposure. The low levels of exposure combine with lower levels of complexity 

to result in lower levels of crash likelihood, even though the higher speeds may lead to higher 
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probabilities of fatalities or serious injuries if a nonmotorized crash occurs or if a crash occurs 

between vehicles at crossing conflict points. 

Table 24. SSI score results for Scenario 2.

Intersection 

Type

Intersection 

SSI Score

Conflict Type SSI Scores

Nonmotorized Crossing Merging Diverging

1x1 

Roundabout 99 98 100 100 100 

2x1 

Roundabout 99 97 100 100 100 

AWSC 

Traditional 99 98 98 100 100 

2x2 

Roundabout 99 96 99 100 100 

Unsignalized 

RCUT 96 95 95 97 97 

MRSC 

Traditional

(existing)

94 92 86 99 98

The information in table 25 provides an additional level of detail for exploring the SSI results 

pertaining specifically to conflict point exposure, average P(FSI), and average complexity 

adjustments. It shows that the unsignalized RCUT alternative shows a significant decrease in 

exposure at crossing conflict points. The existing MRSC traditional intersection as well as the 

AWSC traditional alternative exhibit the lowest exposure at merging and diverging conflict 

points. 

The roundabout alternatives and the AWSC traditional design show improvements over the 

existing design in terms of average P(FSI) at crossing, merging, and diverging conflict points. The 

average P(FSI) at crossing conflict points for the unsignalized RCUT and MRSC traditional are 

0.16 and 0.06, respectively5

. All the intersection types under consideration have lower average 

complexity adjustments than the existing condition for nonmotorized and crossing conflict 

point types.

5 The Scenario 1 discussion addressed the reason for the higher average P(FSI) at RCUT crossing conflict points. 
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Implementing effective speed management strategies at locations such as Scenario 2 has proven 

challenging in the U.S. but would offer SSI score benefits, if effective. For example, if speed 

management strategies were able to reduce speeds on the major and minor road intersection 

approaches to 40 mph, the SSI score for the MRSC traditional intersection in table 25 would 

increase from 94 to 97. The average P(FSI) at the MRSC traditional crossing conflicts in table 25

would decrease from 0.06 to 0.03. The average complexity adjustment at the MRSC traditional 

crossing conflicts in table 25 would decrease from 1.66 to 1.37. Such hypothetical examples 

show that while the SSI method in chapter 3 was presented in the context of project scoping, it 

could also begin to inform multidisciplinary safety stakeholders and the traveling public about 

the SSI effects of speed management strategies that span the different elements of a Safe System 

(e.g., “safe speeds,” “safe road users,” “safe vehicles”).
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Table 25. Relative exposure, average P(FSI), and average complexity adjustment results for Scenario 2.

Intersection 

Type

Exposure (Relative to Existing) Average P(FSI) Average Complexity Adjustment

NM Cross Merge Diverge NM Cross Merge Diverge NM Cross Merge Diverge

1x1 

Roundabout 1.00 1.10 1.78 1.37 0.33 0.00 0.00 0.00 1.22 0.61 0.61 1.00 

2x1 

Roundabout 1.00 1.10 1.78 1.37 0.33 0.00 0.00 0.00 1.83 0.92 0.99 1.00 

AWSC 

Traditional 1.00 1.00 1.00 1.00 0.19 0.01 0.00 0.00 2.74 1.63 1.37 1.00 

2x2 

Roundabout 1.00 1.10 1.78 1.37 0.33 0.00 0.00 0.00 2.44 1.22 1.15 1.00 

Unsignalized 

RCUT 1.10 0.40 3.38 2.12 0.33 0.16 0.02 0.02 2.10 0.68 0.68 1.00 

MRSC 

Traditional 

(existing)

1.00 1.00 1.00 1.00 0.31 0.06 0.01 0.01 3.26 1.66 1.37 1.00
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4.3 SCENARIO 3

4.3.1 Intersection Conditions

Scenario 3 is an urban signalized intersection of a six-lane arterial and a four-lane arterial and is 

depicted in figure 34. The intersection is being studied as part of a congestion mitigation 

project. Design year traffic volumes are estimated at 65,000 and 33,000 vehicles per day, 

respectively, on the major and minor roads. The posted speed limit on both roadways is 45 

mph. There are sidewalk facilities along all approaches, and the intersection serves large 

numbers of nonmotorized users.

Source: FHWA

Figure 34. Graphic. Illustration of intersection conditions for Scenario 3.
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The information in table 26 summarizes the key intersection attributes. 

Table 26. Intersection attributes for Scenario 3. 

Item Input Value

Area type Urban

Functional classification – major Principal arterial

Functional classification – minor Minor arterial

Design year AADT – major 65,000 

Design year AADT – minor 33,000 

Number of thru lanes – major 6 

Number of thru lanes – minor 4 

Traffic control type Signalized

Posted speed limit – major 45 

Posted speed limit – minor 45 

Nonmotorized ADT 4,000 

A Stage 1 ICE analysis of this intersection occurred as part of the congestion mitigation study. 

The following sections summarize the capacity, crash-based safety performance, and SSI analysis 

results. 

4.3.2 Capacity-Based Feasibility Review

The information in table 27 summarizes the CAP-X results and provides the overall V/C ratio 

and V/C ranking. Based on these results and the general lane arrangements of the intersection, 

the unsignalized and roundabout intersection types are dropped from further consideration.
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Table 27. CAP-X results for Scenario 3.

Type of Intersection

Overall 

V/C 

Ratio

V/C 

Ranking

FDLT 0.42 1 

PDLT 0.56 2 

MUT 0.58 3 

Quadrant Roadway 0.62 4 

Signalized Traditional (existing) 0.67 5 

Bowtie 0.75 6 

Signalized RCUT 0.84 7 

2x2 Roundabout 1.01 8 

2x1 Roundabout 1.84 9 

1x1 Roundabout 2.46 10 

AWSC Traditional 2.51 11 

Unsignalized RCUT 7.60 12 

MRSC Traditional 30.23 13 

Jughandle* -- --

* The Jughandle intersection is not included in CAP-X but it has the capacity 

to handle high intersection volumes.

4.3.3 Crash-Based Safety Performance Review

The information in table 28 summarizes the SPICE results for Scenario 3. The results show that 

all the intersection types for which there are predictive information available have fewer 

predicted total and fewer predicted fatal and injury crashes than the signalized traditional 

intersection (which is the existing condition). Based on the SPICE results, no additional 

intersections are dropped from consideration.
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Table 28. SPICE results for Scenario 3.

Control Strategy

Predicted Crashes in 

Design Year 

(crashes/year)

Fatal & 

Injury Total

MUT 3.38 10.52 

Jughandle 3.58 9.16 

Signalized RCUT 3.77 10.52 

FDLT 4.25 10.89 

Signalized Traditional (existing) 4.83 12.38

Quadrant Roadway* -- --

PDLT* -- --

Bowtie* -- --

* These intersection types are not included in SPICE but are included in the SSI 

library of intersections. 

4.3.4 SSI Methodology and Results

The information in table 29 summarizes the SSI scores for the remaining intersection 

alternatives still under consideration in Scenario 3 from the library of SSI intersection 

alternatives in appendix A. It shows that all the feasible intersection design options for this 

scenario result in an Intersection SSI Score of zero, except for the MUT and signalized RCUT 

which have a score of one. This means that none of the feasible designs would align well with 

Safe System principles due to the combinations of user volumes and vehicle speeds at the 

intersection. In this case, the alternatives are listed from the lowest to highest average 

exposure-severity-complexity products [i.e., (Ecrossing + Emerging + Ediverging + Enonmotorized)/4]. Using 

this measure, the MUT, signalized RCUT, bowtie, quadrant roadway, and jughandle have 

improved SSI performance compared to the signalized traditional alternative that represents the 

no-build condition. 

The individual conflict type SSI score results in table 29 illustrate the overall Safe System 

performance of the intersection design in more detail. While all the feasible options have an 

Intersection SSI Score of zero, some of the intersection types have SSI scoring differences when 

considering specific conflict point types. For example, the signalized RCUT performs better 

than other alternatives for crossing conflict points, while the traditional signalized and several 

others perform better for merging conflict points.
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Table 29. SSI score results for Scenario 3. 

Intersection 

Type

Intersection 

SSI Score

Conflict Type SSI Scores

Nonmotorized Crossing Merging Diverging

MUT 1 0 2 30 53 

Signalized 

RCUT 1 0 6 25 52 

Bowtie 0 0 0 67 76 

Quadrant 

Roadway 0 0 0 61 68 

Jughandle 0 0 0 58 79 

Signalized 

Traditional 

(existing)

0 0 0 64 100

FDLT 0 0 0 46 81 

PDLT 0 0 0 56 81 

The information in table 30 provides an additional level of detail for exploring the SSI score 

results pertaining specifically to conflict point exposure, average P(FSI), and average complexity 

adjustment. The MUT, signalized RCUT, FDLT, and PDLT have lower exposure at crossing 

conflict points than other alternatives. Most of the intersection types have lower average 

complexity adjustments than the signalized traditional intersection for nonmotorized and 

crossing conflict point types. The exceptions are the FDLT and PDLT, which have higher levels 

of nonmotorized complexity due to the indirect nonmotorized paths and nonintuitive motor 

vehicle movements at these intersection types. 

The average P(FSI) values are highest for nonmotorized and crossing conflict points. The 

average P(FSI) for nonmotorized conflict points range from 0.27 to 0.33 under the speed 

assumptions of the SSI method. The average P(FSI) for crossing conflict points range from 0.04 

to 0.09. The top MUT and signalized RCUT ranking is a result of reduced crossing conflict point 

exposure and lower levels of complexity for crossing and nonmotorized movements. The 

jughandle, quadrant roadway, and bowtie achieve their improved SSI score over the traditional 

intersection almost solely from the lower levels of complexity for crossing and nonmotorized

movements.

Scenario 3 shows that moving towards a Safe System at some locations is challenging to achieve 

based on the individual intersection design alternative alone. In some cases, solutions may be 
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found by looking to the network and providing improved connectivity for both motorized and 

nonmotorized users and avoiding the high level of exposure at a single, large intersection.
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Table 30. Relative exposure, average P(FSI), and average complexity adjustment results for Scenario 3.

Intersection 

Type

Exposure (Relative to Existing) Average P(FSI) Average Complexity Adjustment

NM Cross Merge Diverge NM Cross Merge Diverge NM Cross Merge Diverge

MUT 1.25 0.74 2.86 2.51 0.33 0.04 0.01 0.00 1.67 1.26 1.05 1.00 

Signalized 

RCUT 1.17 0.26 3.25 2.82 0.28 0.09 0.01 0.00 2.60 1.26 1.05 1.00 

Bowtie 1.25 1.05 2.50 2.21 0.34 0.04 0.01 0.00 2.95 2.53 1.51 1.00 

Quadrant 

Roadway 1.00 1.38 1.65 1.78 0.27 0.05 0.01 0.00 3.04 1.94 1.43 1.00 

Jughandle 1.08 1.18 1.37 1.20 0.29 0.04 0.01 0.00 2.99 2.59 1.89 1.00 

Signalized 

Traditional 

(existing)

1.00 1.00 1.00 1.00 0.29 0.04 0.01 0.00 4.41 2.63 2.26 1.00

FDLT 1.00 0.89 1.00 1.00 0.32 0.05 0.01 0.00 7.12 1.97 2.90 1.00 

PDLT 1.00 0.97 1.00 1.00 0.32 0.04 0.01 0.00 7.68 2.57 3.11 1.00 
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CHAPTER 5: FUTURE VISION FOR THE SSI METHOD

While U.S. intersection planning and design practices have incorporated Safe System principles 

to some extent over the last several decades, significant opportunities for advancing Safe 

System approaches remain. Where enough data are available, U.S. experiences with 

intersection alternatives that simplify road user decision-making and manage impact angles and 

speeds have shown safety performance benefits. These safety benefits are typically expressed in 

the form of CMFs derived from retrospective statistical analyses of crash data. The CMFs are 

usually applicable to the “intersection as a whole” and reflect overall changes or differences in 

the number of crashes at the intersection alternative of interest compared to another 

intersection alternative. In other words, intersection CMFs are often developed with and 

applicable to an aggregation of crashes resulting from different movements through the 

intersection, involving different intersection users, and resulting in a range of injury outcomes.

For example, intersection CMFs for fatal and injury crashes are applicable to crashes of all types 

with injury outcomes ranging from fatal to possible injuries. 

As a complement to more aggregate crash-based findings such as CMFs, the SSI method in 

chapter 3 provides an approach to characterize intersection alternatives with respect to the 

Safe System principles of simplified decision-making and management of impact angles and 

speeds, with the ultimate goal of reducing traffic fatalities and serious injuries. The method is 

applied at the conflict point level and incorporates the characteristics of different movements 

through the intersection for motorized and nonmotorized users. The SSI method is sensitive to 

volumes, vehicle speeds, potential collision angles, and geometry. The results of applying the SSI 

method comprise multiple MOEs and a corresponding set of SSI scores. The MOEs include 

exposure through different conflict point types, the average P(FSI) for different conflict point 

types, and the average complexity for movements passing through different conflict point types. 

The SSI scores are derived based on the combined concepts of conflict points, conflict point 

severity, exposure, and complexity and are a means to characterize the extent to which an

intersection alternative in a given context aligns with the principles of a Safe System. 

Chapter 3 concluded with ideas to expand the library of Stage I ICE intersection alternatives in 

appendix A to incorporate alternative pedestrian and bicycle facilities and to extend the 

method for Stage II ICE analyses. The remainder of this chapter builds on these ideas, outlining 

future enhancements and considerations for the SSI method. The ideas are organized into two 

categories: 1) SSI enhancements for common intersection planning and design applications and 

2) SSI enhancements for broader Safe System implementation.
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5.1 SSI ENHANCEMENTS FOR COMMON INTERSECTION PLANNING AND 

DESIGN APPLICATIONS

The SSI method in chapter 3 is intended for implementation by intersection planners and 

designers within the typical project development process. There are multiple enhancements to 

the method and supporting data that will improve its application in this typical project 

development context:

• Expand to other conflict types.

• Develop data and models to support intersection speed prediction.

• Link SSI MOEs and scores to FSI crash frequencies.

5.1.1 Expand to Other Conflict Types

Appendix A contains various intersection alternatives that State agencies with ICE policies 

commonly consider as part of a Stage I ICE. The alternatives in appendix A currently apply 

typical pedestrian paths and assume that bicyclists follow the same paths as pedestrians. Given 

the significant impact of pedestrian and bicyclist considerations in a Safe System approach, 

future efforts should focus on how to incorporate more refined identification and analysis of 

pedestrian and bicyclist conflict points. The conclusion of chapter 3 pointed out that one 

promising approach is to develop multiple alternatives for a single intersection type that differ 

by pedestrian and bicycle accommodation. Instead of one RCUT, the library could contain, for 

example, RCUT with sidewalk and on-street bike lanes, RCUT with shared use paths, RCUT 

with sidewalks and separated bike lanes and a protected intersection, and other variations. Each 

variation would illustrate the corresponding pedestrian and bicyclist conflict points as the 

starting point for applying the SSI method. 

The SSI method does not currently consider rear-end conflicts that result from speed 

differentials that arise from traffic congestion or deceleration and stopping due to traffic control 

devices (i.e., yield signs, stop signs, and traffic signals). It also does not consider merge and 

diverge conflicts that may vary in their location along an intersection approach due to lane 

changing, including weaving movements. These rear-end and sideswipe additions would increase 

the overall completeness of the method but may not have a significant impact on the overall SSI 

results due to the shallower angles and lower speed differentials of these conflict types. 

5.1.2 Develop Data and Models to Support Intersection Speed Prediction

Speed is central to the Safe System approach. As such, predicted operating speeds for vehicles 

approaching and navigating different intersection alternatives are inputs to the SSI method. 

Chapter 3 noted that there is little existing research into speed prediction at intersections, 
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especially in differentiating speeds of different movements and maneuvers at different points 

throughout the vehicle path. For this reason, the current SSI method adopts a simplified set of 

speed assumptions to cover the different vehicle maneuvers at intersections. These 

assumptions can be adjusted based on local knowledge or any data that become available in the 

future. 

Application of the SSI method would benefit from new research on estimating and predicting 

operating speeds through intersections. At a minimum, the research should provide insights to 

expected operating speeds by intersection type, type of traffic control, and movement. Ideally, 

the methods would also be sensitive to other characteristics of the intersection and 

intersection approaches that would influence speeds, particularly traffic volumes. This could 

support the development of the exposure-severity-complexity products in chapter 3 that are 

sensitive to speeds by time of day (e.g., peak, non-peak). The time-of-day exposure-severitycomplexity products could then be aggregated to determine the overall SSI scores and other 

MOEs. 

5.1.3 Link SSI MOEs and Scores to FSI Crash Frequencies

The exposure-severity-complexity products that lead to the SSI scores in chapter 3 contain the 

same general components as what would be expected in an intersection crash predictive 

method for fatal and serious injury crashes:

• Characterization of exposure.

• Movement complexity factors that, in addition to exposure, are expected to be 

associated with higher or lower crash likelihoods.

• The probability (or proportion) of crashes that occur resulting in a fatality or serious 

injury. 

Future efforts to validate and calibrate the SSI method using crash data could take multiple 

approaches: 

• One approach could seek to establish statistical associations between the SSI MOEs and 

SSI scores and the average number of intersection crashes. 

• A second approach could try to maximize the statistical associations between the SSI 

MOEs and SSI scores and the average number of intersection crashes. This could include 

calibrating some of the parameters that are part of the exposure-severity-complexity 

product using observed crash data. These parameters include:

o Coefficients (other than the currently assumed 1.0) applied to the volumes that 

make up the exposure indices.
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o Values for the traffic control parameters that make up part of the conflicting 

traffic complexity factor, including the BTCAV and the weight applied to traffic 

control.

o Weights assigned to adjacent lanes that are part of the merge score and 

nonmotorized turn score in the conflicting traffic complexity factor.

o Parameters that could adjust the level of contribution of the conflicting traffic 

complexity factor and nonmotorized movement complexity factor to the 

exposure-severity-complexity product and overall SSI score (currently, both are 

given equal weight).

Such efforts could further enhance the complementary nature of Safe System metrics and 

crash-based metrics and support steps towards future versions of resources such as the HSM 

incorporating the SSI method and other types of Safe System assessments. 

Ideally, efforts to validate and calibrate the SSI method with crash data would be based on fatal 

and serious injury crashes, with serious injuries determined on an AIS by trained medical 

professionals following an assessment of a patient’s injuries at the hospital. Such an approach, 

however, would require a traffic injury surveillance system in the State where police-reported 

crashes are linked to hospital records, which is rare. In the absence of such a system, it is 

possible that validation and calibration could occur with “KA” crashes.

5.2 SSI ENHANCEMENTS FOR BROADER SAFE SYSTEM 

IMPLEMENTATION 

In addition to use by intersection planners and designers within the typical project development 

process, the fundamental building blocks of the SSI method in chapter 3 would also allow it to 

incorporate impacts of broader system-level policies and characteristics on SSI MOEs and SSI 

scores. Such capabilities could help advance stakeholder knowledge of the Safe System 

approach to road safety management and support continued dialogue on steps to achieve a 

vision of zero fatalities and serious injuries in the U.S. The following sections offer ideas on how 

the SSI method could incorporate effects of system characteristics such as self-explaining roads 

and speed enforcement, vehicles, and users. 

5.2.1 Self-Explaining Roads and Speed Enforcement

Speed management is central to achieving a Safe System. Tingvall & Haworth (1999) provided 

table 2 as speeds representing an “inherently safe system.” Strategies to achieve such speeds in 

many cases span across “Safe System elements” and require political and societal will. Several 

countries that take a Safe System approach to road safety management have implemented or 

are implementing speed limit reductions along with high levels of enforcement to reduce 
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speeds. For example, the Netherlands Sustainable Safety Start-up Program included the largescale implementation of 30 km/hr (20 mph) zones in urban areas and 60 km/hr (40 mph) zones 

in rural areas, along with corresponding educational and enforcement activities. 

New Zealand’s Safer Journeys Action Plan 2011-2012 identified three areas of focus within their 

“Safe Speeds” element: 

• Public campaigns to achieve acceptance of safe speeds.

• Create speed limits that reflect a Safe System.

• Increase the use of safety cameras.

In addition, the classification of roads based on their function and the design and the operation 

of those roads to be self-explaining of that function play key roles in achieving a Safe System. 

This is most notably the case with the Functionality and Predictability principles of Sustainable 

Safety in the Netherlands, and the corresponding design features of through roads, distributor 

roads, and access roads (Wegman et al., 2008). 

The SSI method could be used to explore and communicate impacts of effective speed 

management and self-explaining roads policies at the intersection level. The effects of changing 

vehicle speeds in a significant way would be captured when quantifying conflict point severity 

(Section 3.6) and the movement complexity attributed to the speed of conflicting traffic 

(Section 3.7.2). The “Scenario 2” example in chapter 4 concluded with an exploration of 

effective speed management at a rural intersection using the SSI method that reduced approach 

speeds from 55mph to 40mph. 

Effective implementation of self-enforcing roads and longer-term changes in driver behavior 

would be seen in the conflicting lanes parameter of the conflicting traffic complexity factor. The 

parameter in the current method is based on the number of lanes that carry conflicting traffic 

movements for a selected movement of interest. For any selected movement in the following 

list, conflicting traffic movements are those that cross or merge with the selected movement of 

interest and are also listed above the selected movement on the list:

1. Major through and right turn. 

2. Major left turn. 

3. Minor through and right turn. 

4. Minor left turn. 

5. Nonmotorized. 

Chapter 3 noted that placing nonmotorized movements at the bottom of this list prioritizes 

nonmotorized movements in the SSI analysis when characterizing the complexity of an 

intersection. The current method noted that, although nonmotorized road users typically have 
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higher priority from a regulatory or traffic control perspective, their speed and vulnerability in a 

crash, along with uncertainty about driver awareness of their presence at any given time, may 

require pedestrians and cyclists to be aware of conflicting traffic movements that are lowerpriority from a regulatory or traffic control perspective. This adds complexity for nonmotorized users. Complexity would be reduced as long-term driver behavior changed to more 

consistently reflect typical nonmotorized road user priority from a regulatory or traffic control 

perspective. 

5.2.2 Vehicles

Vehicle design plays a key role in achieving a Safe System at an intersection. The SSI method 

could incorporate different aspects of vehicle design if corresponding data or assumptions are 

available. The following sections provide two examples.

Vehicle Size. When estimating P(FSI) for vehicle-vehicle conflict points, the current SSI 

method assumes the masses of both vehicles are the same. Differences in the sizes of two 

vehicles involved in a collision will impact the estimates of P(FSI) for the occupants of each 

vehicle. The SSI method could incorporate sensitivity to vehicle sizes through the following 

steps: 

• Establish vehicle categories and corresponding representative sizes (e.g., compact car, 

SUV/pickup truck, bus, large truck).

• Develop a method that translates user inputs or default values for vehicle mix into 

probabilities of crashes at a conflict point involving each possible combination of 

vehicles. Based on ties between “delta V” and P(FSI), the specifics of which vehicle is 

making which movement through different conflict points is an important detail. For 

example, the conflict point defining a left-turn from the major road, an opposing through 

on the major road, and a car-bus combination could have the bus turning left with the 

car as the opposing through vehicle or vice versa. Each of these two scenarios would 

have a different P(FSI). 

• Estimate P(FSI) curves as functions of speeds and angles for each vehicle combination.

• Use the probabilities of crashes at a conflict point involving each combination of vehicles 

and P(FSI) for each combination to compute an overall P(FSI). 

In a similar fashion, P(FSI) curves for pedestrian and bicyclist crashes can also be defined as a 

function of vehicle size and combined with the probability that a pedestrian or bicyclist crash 

involves each vehicle size to estimate an overall P(FSI). 

Vehicle Technologies. Automated driving system (ADS) technologies are quickly advancing 

and are expected to impact road safety in the coming years. Such technologies would be 
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expected to impact intersection crash likelihood and severity for different crash types. Such 

impacts would likely differ by ADS technology and conflict point type. The existing structure of 

the SSI method could incorporate ADS effects in an average/aggregate way. Distributions of 

vehicles with different technologies could be applied to movement volumes, resulting in 

exposure indices for each combination of ADS technologies. Those combinations could have 

different P(FSI) curves if the technologies are expected to automate reductions in speeds and/or 

collision angles during last the final seconds pre-crash scenarios. Much like the traffic control 

parameter of the conflicting lanes complexity factor, ADS parameters could also reduce 

complexity significantly, resulting in lower values for some exposure-severity-complexity factors 

and improved SSI MOEs and scores. 

5.2.3 Users

User characteristics such as fatigue, impairment, behavior (e.g., level of compliance, distraction), 

and performance capabilities can impact the likelihood of a crash as those users make different 

movements through an intersection. Similarly, a user’s age, condition, and use of safety 

equipment (e.g., seatbelts, helmets) can have significant effects on their level of injury resulting 

from a crash. Such extensive sets of user characteristics can quickly complicate the SSI method, 

but they are a part of a systems analysis of intersection safety. The existing structure of SSI 

method could incorporate such user characteristics in an average/aggregate way. Distributions 

of key user characteristics could be applied to movement volumes, resulting in exposure indices 

for each combination of user characteristics. Those combinations of user characteristics could 

have different P(FSI) curves, and different user characteristic parameters applied to the 

complexity factors. This would lead to exposure-severity-complexity products for different 

combinations of user characteristics, which could then be summed for different conflict point 

types and for the intersection, leading to the SSI MOEs and scores.

At some point, the large number of user and vehicle type combinations could lend themselves 

to an analysis by a microscopic safety simulation, where distributions of user characteristics, 

vehicle characteristics, and user arrival distributions are inputs and the intersection is modeled 

in a stochastic way. Crash probabilities for users making different movements would vary based 

on these characteristics and other conditions at any given time. Similarly, P(FSI) would be a 

function of the vehicles and users involved in a crash that had a specific speed and angle. Such a 

model could be validated by whether the simulation, carried out over a year or multi-year time 

period, would simulate comparable numbers and severities of crashes as to what is observed. 

Research and supporting data to inform the development of such a microscopic safety 

simulation model would improve the ability of intersection planners and designers to gain a 

greater system-level understanding of the factors leading to fatalities and serious injuries and to 

manage intersection safety toward the goal of achieving zero fatalities and serious injuries.
 
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APPENDIX A: SSI LIBRARY OF INTERSECTION TYPES

This appendix provides overviews of various intersection alternatives that transportation 

agencies could consider as part of Stage 1 ICE. For each intersection alternative, the appendix 

includes the following information:

• Intersection type (and aliases).

• Distinguishing features and other key considerations.

• Nonmotorized considerations. 

• Assumptions in SSI method application for Stage 1 ICE. 

o These are “default” assumptions made in this report for demonstrating the 

application of the SSI method to Stage 1 ICE. However, the method can be 

generalized and applied to agency- and project-specific situations that differ from 

the assumptions (e.g., three intersecting legs, major road median providing 

refuge for minor road through and left-turning vehicles at traditional 

intersection).

• Conditions supporting consideration. 

• Potential benefits.

• Traffic control characteristics.

• Counts and diagrams of movement-based conflict points.
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TRADITIONAL

Table 31. Key characteristics and considerations related to the traditional intersection alternatives. 

Intersection type Traditional 

Aliases Conventional; standard; default

Distinguishing 

features/key 

considerations

• Allows direct movements (left, thru, right) on all approaches; State or local agencies may implement some movement 

restrictions with traffic control devices. 

Nonmotorized

considerations

• One-stage or two-stage crossings depending on presence of refuge.

• Long signal cycle lengths can limit crossing opportunities.

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• Intersection has 4 legs.

• 3 traffic control schemes (signal control, all-way stop control, minor road stop control) considered.

• No medians on any legs.

Conditions supporting 

consideration

• Generally considered across a wide range of contexts.

Potential benefits • Widespread familiarity and intuitive nature of movements.

Traffic control 

characteristics

• Can operate under signal control, all-way stop control, or minor road stop control.

Movement-based 

conflict points 

Vehicle-vehicle – total 32

Vehicle-vehicle – crossing 16

Vehicle-vehicle – merging 8 

Vehicle-vehicle – diverging 8 

Nonmotorized-vehicle 24
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Source: FHWA

Figure 35. Graphic. Diagram of movement-based conflict points for Traditional Signalized and All-Way Stop 

Control intersections.
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Source: FHWA

Figure 36. Graphic. Diagram of movement-based conflict points for Traditional Minor Road Stop Control 

intersections.
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ROUNDABOUT

Table 32. Key characteristics and considerations related to the roundabout intersection alternatives. 

Intersection type Roundabout

Aliases 

Distinguishing 

features/key 

considerations

• Removes direct left turns from all approaches and replaces them with yield-controlled approaches into a counterclockwise circulatory lane.

• Can be installed at individual intersections (provided they are located far enough from nearby signalized/stop-controlled 

intersections that queues do not extend into the roundabout) or in series along a corridor.

Nonmotorized

considerations

• Splitter islands provide refuge and allow for two stage crossings.

Report 

assumptions in SSI 

method 

application for 

Stage 1 ICE 

• All approaches have splitter islands/pedestrian refuge islands.

• Three roundabout entry geometries considered: 1x1 Roundabout (1 lane in each direction on all approaches), 2x1 

Roundabout (2 lanes in each direction on major road, which yield to one circulating lane; 1 lane in each direction on 

minor road, which yield to two circulating lanes), and 2x2 Roundabout (2 lanes in each direction on all approaches, 

yielding to two circulating lanes).

• All approaches operate under yield control.

• Indirect Paths adjustment applied to all nonmotorized movements due to footprint and placement of crosswalks. 

Conditions 

supporting 

consideration

• High frequency of left-turning or right-angle crashes.

• Increased capacity or improved efficiency desired without adding lanes along the corridor.

• Sufficient space available at the intersection (wide nodes, narrow roads concept).

Potential benefits • Reduction in crossing conflict points.

• Roundabout geometry and yield control lead to reduced vehicle speeds.

• Geometry deflects approaching vehicles and produces shallower collision angles (less severe).

• Increased capacity and improved operational efficiency, as vehicles operate on a gap-acceptance model.

• Simplified decision-making for road users as conflicting movements approach from one direction.

Traffic control 

characteristics

• All approaches typically operate under yield control. Unexpected demand may result in signalized control of one or 

more entries, or signalized control of the circulating roadway. 

Movement-based 

conflict points 

(Compared to 

Traditional) 

Vehicle-vehicle – total 20 (32)

Vehicle-vehicle – crossing 4 (16)

Vehicle-vehicle – merging 8 (8)

Vehicle-vehicle – diverging 8 (8)

Nonmotorized-vehicle 8 (24)
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Source: FHWA

Figure 37. Graphic. Diagram of movement-based conflict points for Roundabout intersections.
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RESTRICTED CROSSING U-TURN (RCUT)

Table 33. Key characteristics and considerations related to the RCUT intersection alternatives. 

Intersection type Restricted crossing U-turn

Aliases J-turn; superstreet; synchronized street; reduced conflict intersection

Distinguishing 

features/key 

considerations

• Removes direct left turns and through movements from minor road (minor road left turns made via right-turn/Uturn combination, minor road through movements made via right-turn/U-turn/right-turn combination).

• Requires downstream U-turn accommodations along major road.

Nonmotorized

considerations

• Wider footprint lengthens crossings, but major road median provides refuge for multistage crossing.

• Shorter signal cycle lengths yield more frequent crossing opportunities.

• Z-crossing is most common pattern, resulting in some indirect nonmotorized movements. 

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• All approaches have medians/pedestrian refuge islands.

• 2 traffic control schemes (signal control, minor road stop control) considered.

• Z-type pedestrian crossing pattern is utilized, Indirect Paths adjustment applied to nonmotorized road users 

crossing major road.

Conditions supporting 

consideration

• Lower left-turning and through volumes from minor road.

• High frequency of right-angle crashes.

• Sufficient median width, right-of-way (ROW), and intersection spacing for U-turn accommodations.

• Accommodates wide range of major road volumes.

Potential benefits • Eliminates all but two crossing conflict points.

• Provision of pedestrian refuge medians.

• Simplified decision-making for road users as conflicting movements approach from one direction.

• Increased capacity and improved operational efficiency.

• Increased flexibility in signal timing, especially for accommodating unbalanced flows.

• Fewer signal phases may yield improved coordination with adjacent signals.

Traffic control 

characteristics

• Minor road stop control can be considered for low minor road volumes.

• Usually signalized with moderate to high minor road volumes.

• U-turns may operate under signal control, stop control, or yield control.

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 14 (32)

Vehicle-vehicle – crossing 2 (16)

Vehicle-vehicle – merging 6 (8)

Vehicle-vehicle – diverging 6 (8)

Nonmotorized-vehicle 10 (24)
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Source: FHWA

Figure 38. Graphic. Diagram of movement-based conflict points for Signalized RCUT intersections.
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Source: FHWA

Figure 39. Graphic. Diagram of movement-based conflict points for Unsignalized RCUT intersections.
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MEDIAN U-TURN (MUT)

Table 34. Key characteristics and considerations related to the MUT intersection alternative.

Intersection type Median U-Turn (MUT)

Aliases ThrU-turn; indirect left; express left; Michigan left; Michigan loon

Distinguishing 

features/key 

considerations

• Removes direct left turns from major and/or minor roads.

• Requires downstream U-turn accommodations along major road or minor road.

• Left turns made via right-turn/U-turn or U-turn/right-turn combination.

• Can be installed at individual intersections or applied in series along a corridor.

Nonmotorized

considerations

• Wider footprint lengthens crossings, but major road median provides adequate refuge for multistage crossing.

• Shorter signal cycle lengths yield more frequent crossing opportunities.

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• All approaches have medians/pedestrian refuge islands.

• All direct left turns are removed from intersection.

Conditions supporting 

consideration

• Higher proportion of thru volumes to left-turning volumes.

• Higher frequency of right-angle and rear-end crashes.

• Sufficient median width, ROW, and intersection spacing for U-turn accommodations.

• Can accommodate high intersection volumes.

Potential benefits • Reduction in crossing conflict points.

• Simplified task of crossing for nonmotorized road users as there are no conflicting left turn movements at the main 

intersection.

• Increased capacity and improved operational efficiency.

• Increased capacity and improved operational efficiency.

• Fewer signal phases may yield improved coordination with adjacent signals.

Traffic control 

characteristics

• Main junction is signalized.

• U-turns may operate under signal control, yield control, or no control.

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 16 (32)

Vehicle-vehicle – crossing 4 (16)

Vehicle-vehicle – merging 6 (8)

Vehicle-vehicle – diverging 6 (8)

Nonmotorized-vehicle 16 (24)
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Source: FHWA

Figure 40. Graphic. Diagram of movement-based conflict points for MUT intersections.

 
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BOWTIE

Table 35. Key characteristics and considerations related to the bowtie intersection alternative.

Intersection type Bowtie 

Aliases 

Distinguishing 

features/key 

considerations

• Removes direct left turns from all approaches.

• Roundabouts placed on the minor road on each side of the main intersection.

• Left turn movements are accommodated by a combination of right turns, U-turns at a roundabout, and through 

movements through the main intersection.

Nonmotorized

considerations

• Crossings at main intersection similar to a traditional intersection.

• Crossings at roundabouts are the same as roundabouts, i.e. splitter islands provide refuge and allow for two stage 

crossings.

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• No left turn movements at the main intersection.

• Secondary roundabouts do not provide a speed reduction benefit for vehicles entering the main intersection.

Conditions supporting 

consideration

• Increased capacity required without sufficient ROW to add lanes along the corridor.

• Sufficient ROW available up/downstream of main intersection for roundabouts.

• Moderate-heavy major road through volumes and low-moderate left turn volumes.

Potential benefits • Eliminates all left turning crossing conflicts.

• Conflicts at secondary roundabouts receive same benefits as standalone roundabout.

• Simplified task of crossing for pedestrians as there are no conflicting left-turn movements at the main intersection.

• Increased capacity and improved operational efficiency for the major through movements.

• Fewer signal phases may yield improved coordination with adjacent signals.

Traffic control 

characteristics

• Main intersection operates under signal control.

• Roundabouts on minor road operate the same as standard roundabouts, i.e. yield control.

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 20 (32)

Vehicle-vehicle – crossing 4 (16)

Vehicle-vehicle – merging 8 (8)

Vehicle-vehicle – diverging 8 (8)

Nonmotorized-vehicle 16 (24)
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Source: FHWA

Figure 41. Graphic. Diagram of movement-based conflict points for Bowtie intersections.
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JUGHANDLE

Table 36. Key characteristics and considerations related to the jughandle intersection alternative.

Intersection type Jughandle

Aliases New Jersey Left

Distinguishing 

features/key 

considerations

• Removes direct right and left turns from one approach.

• Replaces these movements by directing them onto an at-grade roadway (the "jughandle").

• From the jughandle, vehicles can then turn left or right onto the intersecting road.

Nonmotorized

considerations

• Crossings at main intersection similar to a traditional intersection, though crossing widths may be reduced due to 

absence of turn lane(s).

• Nonmotorized road users traveling in the same quadrant as the jughandle have additional crossing point(s).

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• Though other configurations are possible, the most common type, the forward jughandle, is assumed.

Conditions supporting 

consideration

• High frequency of right-angle crashes.

• Sufficient ROW available in one quadrant for the jughandle.

• Relatively low left turn volumes.

Potential benefits • Removes one left turn movement from main intersection, eliminating the crossing and nonmotorized conflict points 

associated with that left turn movement at the main intersection.

• Increased capacity and improved operational efficiency due to removal of turns from one approach.

Traffic control 

characteristics

• Main intersection operates under signal control. 

• Left turns off of the jughandle are stop-controlled.

• Right turns off of the jughandle may be either stop-controlled or yield-controlled. 

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 31 (32)

Vehicle-vehicle – crossing 13 (16)

Vehicle-vehicle – merging 9 (8)

Vehicle-vehicle – diverging 9 (8)

Nonmotorized-vehicle 25 (24)
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Source: FHWA

Figure 42. Graphic. Diagram of movement-based conflict points for Jughandle intersections.

 
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QUADRANT ROADWAY

Table 37. Key characteristics and considerations related to the quadrant roadway intersection alternative.

Intersection type Quadrant roadway 

Aliases 

Distinguishing 

features/key 

considerations

• Removes direct left turns from all approaches.

• Two secondary intersections, one each on the major and minor roadways, are connected by a quadrant roadway.

• Left turns are accommodated by performing right turns and through movements at the main intersections and left 

and right turns at each of the secondary intersections.

Nonmotorized

considerations

• Crossings at main intersection similar to a traditional intersection, though crossing widths may be reduced due to 

absence of turn lane(s).

• Nonmotorized road users traveling in the same quadrant as the quadrant roadway have an additional crossing 

point(s).

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• Though it is possible for other configurations, such as having quadrant roadways in two quadrants or having 

roundabouts serve as the secondary intersections, a single quadrant roadway with signalized T-intersections is 

assumed.

Conditions supporting 

consideration

• High frequency of right-angle crashes.

• Roadway in one quadrant already exists and can be utilized as the connecting roadway.

• Heavy through and left turn volumes on both intersecting roads.

Potential benefits • Removes all left turn movements from main intersection, reducing crossing conflicts.

• Simplified task of crossing for nonmotorized road users, as there are no left turn vehicles intersecting crosswalks at 

the main intersection.

• Increased capacity and improved operational efficiency due to removal of all direct left turns from main intersection.

• Fewer signal phases may yield improved coordination with adjacent signals.

Traffic control 

characteristics

• Main intersection and secondary T-intersections are signalized.

• The three signalized intersections can be synchronized to provide optimal efficiency for both roadways.

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 30 (32)

Vehicle-vehicle – crossing 10 (16)

Vehicle-vehicle – merging 10 (8)

Vehicle-vehicle – diverging 10 (8)

Nonmotorized-vehicle 24 (24)
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Source: FHWA

Figure 43. Graphic. Diagram of movement-based conflict points for Quadrant Roadway intersections.

 
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PARTIAL DISPLACED LEFT TURN (PDLT)

Table 38. Key characteristics and considerations related to the PDLT intersection alternative.

Intersection type Partial displaced left turn (PDLT)

Aliases Continuous flow intersection (CFI)

Distinguishing 

features/key 

considerations

• Left-turning traffic along major or minor road crosses over to the left-hand side of the road at secondary 

intersections upstream of the main junction.

• Enables left-turns and through movements to occur simultaneously at main intersection without conflicting with one 

another. 

Nonmotorized

considerations

• Movements are more complex than at traditional intersection due to unique lane placement; traffic may approach 

from unexpected direction.

• Wider footprint lengthens crossings, but islands provide refuge for multistage crossing.

• Shorter signal cycle lengths yield more frequent crossing opportunities.

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• Displaced left turns are applied to major road.

• All approaches have medians/pedestrian refuge islands and right turns are all channelized.

• Indirect Paths adjustment applied to all nonmotorized conflict points (due to channelized right turns); Non-Intuitive 

Motor Vehicle Movements adjustment applied to nonmotorized conflict points along nonmotorized movements that 

cross approaches with displaced left turns.

Conditions supporting 

consideration

• Heavy thru and left-turning volumes.

• Left-turn queues that exceed existing storage.

• High frequency of crashes associated with left turns.

• Can accommodate high intersection volumes.

Potential benefits • Reduction in crossing conflict points.

• Increased capacity and improved operational efficiency.

• Fewer signal phases may yield improved coordination with adjacent signals.

Traffic control 

characteristics

• Main junction and crossovers are signalized.

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 30 (32)

Vehicle-vehicle – crossing 14 (16)

Vehicle-vehicle – merging 8 (8)

Vehicle-vehicle – diverging 8 (8)

Nonmotorized-vehicle 22 (24)
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Source: FHWA

Figure 44. Graphic. Diagram of movement-based conflict points for Partial DLT intersections.
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FULL DISPLACED LEFT TURN (FDLT)

Table 39. Key characteristics and considerations related to the FDLT intersection alternative.

Intersection type Full displaced left turn (FDLT)

Aliases Continuous flow intersection (CFI)

Distinguishing 

features/key 

considerations

• Left-turning traffic along major and minor road crosses over to the left-hand side of the road at secondary 

intersections upstream of the main junction.

• Enables left-turns and through movements to occur simultaneously at main intersection without conflicting with one 

another. 

Nonmotorized

considerations

• Movements are more complex than at traditional intersection due to unique lane placement; traffic may approach 

from unexpected direction.

• Wider footprint lengthens crossings, but median islands provide refuge for multistage crossing.

• Shorter signal cycle lengths yield more frequent crossing opportunities.

Report assumptions 

in SSI method 

application for Stage 

1 ICE

• All approaches have medians/pedestrian refuge islands and right turns are all channelized.

• Indirect Paths adjustment applied to all nonmotorized conflict points (due to channelized right turns) and NonIntuitive Motor Vehicle Movements adjustment applied to all nonmotorized conflict points.

Conditions supporting 

consideration

• Heavy thru and left-turning volumes.

• Left-turn queues that exceed existing storage.

• High frequency of crashes associated with left turns.

• Can accommodate high intersection volumes.

Potential benefits • Reduction in crossing conflict points.

• Increased capacity and improved operational efficiency.

• Fewer signal phases may yield improved coordination with adjacent signals.

Traffic control 

characteristics

• Main junction and crossovers are signalized.

Movement-based 

conflict points 

(Compared to 

Traditional)

Vehicle-vehicle – total 28 (32)

Vehicle-vehicle – crossing 12 (16)

Vehicle-vehicle – merging 8 (8)

Vehicle-vehicle – diverging 8 (8)

Nonmotorized-vehicle 20 (24)
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Source: FHWA

Figure 45. Graphic. Diagram of movement-based conflict points for Full DLT intersections.

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APPENDIX B: SSI METHOD EXAMPLE CALCULATIONS

This appendix presents example calculations of the SSI method for a selection of intersection 

types and conflict points. For each major step in the SSI method, the appendix illustrates 

calculations for several different conflict points at three different intersection alternatives: the 

traditional signalized intersection, the 2x1 roundabout, and the unsignalized RCUT intersection. 

The specific conflict points used were chosen to illustrate different aspects of the method.

The example calculations are based on the intersection conditions of Scenario 1 in chapter 4, a 

suburban intersection of a four-lane arterial and a two-lane collector that currently exists as a 

traditional signalized intersection as depicted in figure 32. Table 40 contains the data inputs as 

well as some assumptions used to perform the calculations. Note that some of these 

assumptions may not be necessary depending on an agency’s available data. For instance, if an 

agency had access to turning movement counts (either peak hour counts or turning movement 

ADTs) it would not be necessary to assume a directional split or turning proportions. 

Table 40. Example calculation core inputs.

Item Input Value Assumption

Design year AADT – major 25,000 50% directional split. Turning proportions: 25% left 

turn, 25% right turn.

Design year AADT – minor 20,000 50% directional split. Turning proportions: 25% left 

turn, 25% right turn.

Nonmotorized ADT 2,400 Nonmotorized volume is evenly distributed across 

the four crossings at the intersection.

Number of thru lanes – major 4 --

Number of thru lanes – minor 2 --

Traffic control type Signalized Left-turn signal phasing for both major and minor 

roads is protected-permitted.

Posted speed limit – major 45 --

Posted speed limit – minor 35 --

Furthermore, the movement speeds, collision angles, P(FSI) regression parameters, BTCAV’s, 

driver merging weights, and nonmotorized turn score merging weights are derived from the 

ranges presented in chapter 3. In most cases, Scenario 1 calculations use the midpoint of the 

ranges. Table 41 summarizes the input values for the example calculations in this appendix. 
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Table 41. Default input values used for example calculations.

Category Item Value Units

Movement speeds

Major through Major PSL mph

Major left 20 mph

Major right 15 mph

Minor through 0.85 * Minor PSL mph

Minor left 20 mph

Minor right 15 mph

Stop control near-side 15 mph

Stop control far-side 25 mph

Signal control near-side 15 mph

Signal control far-side 25 mph

Roundabout entering 20 mph

Roundabout circulating 25 mph

Roundabout exiting 30 mph

Collision angles

Crossing – Broadside 90 deg 

Crossing – Left Turn 230 deg 

Crossing – Roundabout 60 deg 

Merging 45 deg 

Diverging 10 deg 

P(FSI) regression 

parameters

alpha 67.29 --

k 3.79 --

Traffic control 

adjustments 

BTCAV, permitted 1 --

BTCAV, protected/permitted 0.85 --

BTCAV, protected 0.01 --

BTCAV, stop-controlled 0.45 --

Weight, f 0.5 --

Major left turn phasing Protected/permitted --

Minor left turn phasing Protected/permitted --

Driver Merging and 

Nonmotorized Turn 

Score Weights

Lane 1 (W1) 1 --

Lane 2 (W2) 0.75 --

Lane 3+ (W3+) 0.5 --

Finally, table 42 lists the conflict points featured in this appendix to illustrate the SSI method

example calculations. Some of these selected conflict points are used to illustrate each part of 

the SSI method (i.e., exposure, severity, and complexity calculations) while others were chosen 

to specifically highlight one specific part. The conflict point naming convention presented in the 

second column of table 42 is used throughout this appendix to simplify references to the 

different conflict points. Figure 46, figure 47, and figure 48 display the three intersection types 
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with the conflict points featured in this appendix denoted by darker linework and labels 

corresponding to the conflict point names in table 42. It will be helpful for the reader to refer 

to these figures, as well as the intersection figures presented in appendix A, to better visualize 

the different conflict points used in these example calculations. Note that the cardinal 

directions used to describe the different movements, conflict points, and areas of intersections 

assume the convention that “north” is oriented “up” toward the top of the page when the page 

is correctly oriented for reading. In both chapter 4 and appendix A, the intersecting road 

positioned in the “up-down” (i.e., north-south) direction is the minor road. The intersecting 

road positioned in the “left-right” (i.e., east-west) direction is the minor road. 

Table 42. Conflict points used for example calculations.

Intersection 

Type 

Conflict 

Point 

Name

Conflict Point Type Movement 1 Movement 2

Traditional 

Signalized

(see figure 46)

Trad-1 Merging – Right Turn Eastbound (EB) Thru Northbound (NB) Right

Trad-2 Crossing – Left Turn Southbound (SB) Thru NB Left 

Trad-3 Diverging NB Thru NB Right

Trad-4 Nonmotorized East Leg Nonmotorized 

(NM)

NB Right

Trad-5 Crossing NB Thru WB Thru

Roundabout 

(see figure 47)

RAB-1 Crossing NB Exiting WB Entering 

RAB-2 Merging – Exiting NB Entering EB Exiting

RAB-3 Nonmotorized North Leg NM SB Entering 

RAB-4 Merging - Circulating WB Entering Circulating

Unsignalized 

RCUT

(see figure 48)

RCUT-1 Merging – Left Turn WB Left EB Right

RCUT-2 Diverging EB Thru East U-Turn

RCUT-3 Nonmotorized Major NM WB Thru

RCUT-4 Merging – U-Turn WB Thru East U-Turn
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Source: FHWA

Figure 46. Graphic. Example calculation conflict points for Traditional Signalized 

intersection.

Source: FHWA

Figure 47. Graphic. Example calculation conflict points for Roundabout 

intersection.
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Source: FHWA

Figure 48. Graphic. Example calculation conflict points for Unsignalized RCUT

intersection.
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EXPOSURE 

This section presents example calculations for the exposure index of the SSI method. For 

background on this part of the method, refer to section 3.5 of this report. 

Traditional Signalized

In the case of the traditional signalized intersection, consider merging conflict point Trad-1 

where the eastbound through movement on the major road conflicts with the northbound right 

turn on the minor road. The daily vehicle volumes of these two movements are Q1 = 6,250 and

Q2 = 2,500 vehicles per day, respectively. Therefore, the exposure index for this conflict point 

would be computed as shown in figure 49. 

Figure 49. Equation. Exposure index example for traditional signalized intersection

merging conflict point Trad-1. 

Similarly, consider crossing conflict point Trad-2 represented by the southbound through 

movement on the minor road and the northbound left turn from the opposing the minor road

approach. The daily volumes for those movements are Q1 = 5,000 and Q2 = 2,500 vehicles per 

day, respectively. Therefore, the exposure index is computed as shown in figure 50. 

Figure 50. Equation. Exposure index example for traditional signalized intersection 

crossing conflict point Trad-2. 

Roundabout

Consider a 2x1 roundabout intersection and examine crossing conflict point RAB-1 in the 

northeast quadrant of the intersection. Determining the daily turning movement counts of 

these two movements is different than at the traditional intersection because the two traffic 

streams at this conflict point involve more than two movements in a traditional sense. This 

example will refer to the two traffic streams as “circulating” and “entering.” The circulating 

traffic stream includes both the northbound through movement and the eastbound left 

movement. The daily vehicle volume for the circulating traffic stream is therefore Q1 = 5,000 + 

3,125 = 8,125. Similarly, the daily vehicle volume for the entering traffic stream applicable to the 

crossing conflict point is the sum of the westbound left and westbound through turning 
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movement counts, or Q2 = 3,125 + 6,250 = 9,375. Now that the daily volumes have been 

determined for the two traffic streams, the exposure index is computed as shown in figure 51. 

Figure 51. Equation. Exposure index example for roundabout intersection crossing 

conflict point RAB-1. 

As another example of exposure index calculation at a 2x1 roundabout, consider merging 

conflict point RAB-2 in the southeast quadrant of the intersection represented by the 

circulating movement that is exiting the roundabout eastbound and the movement coming 

northbound and turning right to also exit the roundabout eastbound. The circulating/exiting 

movement is made up of vehicles traveling in the eastbound through movement as well as the 

southbound left movement. This means the total volume for this movement is Q1 = 6,250 + 

2,500 = 8,750 vehicles per day. The northbound right is simply the turning movement count of 

northbound right-turning vehicles, or Q2 = 2,500 vehicles per day. The exposure index for this 

conflict point is computed as shown in figure 52. 

Figure 52. Equation. Exposure index example for roundabout intersection merging 

conflict point RAB-2. 

The exposure index for nonmotorized conflict points is computed in much the same way. 

Consider conflict point RAB-3, represented by the nonmotorized movement crossing the north 

leg (i.e., the approach on the north side of the intersection) and the southbound entering traffic. 

The nonmotorized volume crossing this leg is Q1 = 600 pedestrians/cyclists per day. The vehicle 

traffic will consist of all southbound movements: the southbound through, left, and right. This 

means the vehicle volume at this conflict point will be Q2 = 5,000 + 2,500 + 2,500 = 10,000 

vehicles per day. The exposure index for this conflict point is computed as shown in figure 53. 

Figure 53. Equation. Exposure index example for roundabout intersection 

nonmotorized conflict point RAB-3. 
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Unsignalized RCUT

As a third intersection alternative, consider the unsignalized RCUT. As in the roundabout, many 

conflict points at an RCUT involve more than two movements in the traditional sense, due to 

the way that both vehicular and nonmotorized movements are diverted in the RCUT design. 

First, examine merging conflict point RCUT-1, represented by the westbound left-turning 

movement and the eastbound right-turning movement. The westbound left movement includes 

the westbound left-turning traffic. Therefore, the volume of this movement at the conflict point 

is Q1 = 3,125 vehicles per day. The eastbound right-turning movement at an RCUT includes 

not only the right-turning traffic coming eastbound on the major road approach, but also the 

southbound through traffic, which made a right-turn, then a U-turn, and is now making another 

right-turn at this conflict point. So, the eastbound right-turning volume at the conflict point in 

questions is Q2 = 3,125 + 5,000 = 8,125 vehicles per day. The exposure index of this conflict 

point is computed as shown in figure 54. 

Figure 54. Equation. Exposure index example for unsignalized RCUT intersection 

merging conflict point RCUT-1. 

As another example of an RCUT conflict point, consider diverging conflict point RCUT-2 

represented by the eastbound through movement and the movement entering the U-turn on 

the east side of the intersection. The eastbound through movement at this point includes 

eastbound through, southbound left, and northbound right traffic. This means that Q1 = 6,250 + 

2,500 + 2,500 = 11,250 vehicles per day. The U-turning traffic, on the other hand, is comprised 

of vehicles making the northbound left and northbound through movements. Therefore, Q2 = 

5,000 + 2,500 = 7,500 vehicles per day. The exposure index of this conflict point is computed 

as shown in figure 55.

Figure 55. Equation. Exposure index example for unsignalized RCUT intersection 

diverging conflict point RCUT-2. 

As a final example of the exposure index computation at the unsignalized RCUT intersection, 

consider conflict point RCUT-3, represented by the nonmotorized movement crossing the 

major road and the westbound through movement. The RCUT alternative in appendix A 

utilizes a Z-shaped pattern for pedestrian crosswalks, meaning that there is only one crosswalk 
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across the major road. This means that the nonmotorized volume at this conflict point will be 

comprised of all pedestrian and bicyclist traffic crossing the major road, so Q1 = 1,200 

pedestrians/cyclists per day. The westbound through vehicle movement at this conflict point 

includes westbound through traffic as well as northbound left traffic. Therefore, Q2 = 6,250 + 

2,500 = 8,750 vehicles per day. The exposure index of this conflict point is computed as shown 

in figure 56.

Figure 56. Equation. Exposure index example for unsignalized RCUT intersection 

nonmotorized conflict point RCUT-3. 

SEVERITY

This section presents example calculations for the conflict point severity steps of the SSI 

method. For background on this part of the method, refer to section 3.6 of this report. 

Traditional Signalized

As the first example conflict point for the traditional signalized intersection severity calculation, 

consider crossing conflict point Trad-2, where the southbound through movement on the 

minor road crosses the northbound left turn from the opposing minor road approach. The first 

step to computing P(FSI) for this conflict point is to identify that this is a vehicle-vehicle conflict 

point, and therefore should employ the vehicle-vehicle model for conflict point severity. This 

model requires three inputs: ΔV, α, and k. In turn, the computation of ΔV requires the speeds of 

the two movements and the conflict angle between them. The speeds and angle can be 

determined by referring to table 10 and table 11. This example uses the midpoint of the 

presented typical ranges. In this case, the vehicle speeds for the minor through movement and 

minor left turn should be 15 mph (the “signal near” speed category) and 25 mph (the “signal 

far” speed category), respectively, based on the position of the conflict point relative to the 

stop bars on the approaches where the two movements originate. The conflict point fits the 

“Crossing – Left Turn” collision type category, so the collision angle is 230 degrees. Therefore, 

ΔV is computed as shown in figure 57. 

Figure 57. Equation. ΔV example for traditional signalized intersection crossing 

conflict point Trad-2. 
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To compute P(FSI) for one of the vehicles at the conflict point, this ΔV estimate is uses along 

with the values for α and k determined using the weighted average of the data from Evans 

(1994). This is shown in figure 58.

Figure 58. Equation. Example of P(FSI) for one vehicle at traditional signalized 

intersection crossing conflict point Trad-2. 

The final step is to compute the P(FSI) value across both vehicles at the conflict point as follows 

(using the equation in figure 10, where the P(FSI) values for both vehicles are the same, 

computed above in figure 58).

Figure 59. Equation. Example of probability of fatality or serious injury for both 

vehicles at traditional signalized intersection crossing conflict point Trad-2. 

This translates to a 1.42 percent probability of at least one fatal or serious injury occurring as a 

result of a crash between conflicting road users making the movements that define this conflict 

point. 

For comparison, consider diverging conflict point Trad-3, the northbound through and 

northbound right-turning movements on the minor road. In this case, following the same 

procedure as above, the vehicle speeds are 15 mph for both movements (because the 

movements originate from a minor approach at a signalized intersection, and the conflict point 

is on the near side of the intersection). The collision angle is 10 degrees. Given these inputs, 

the calculation of ΔV is shown in figure 60. 

Figure 60. Equation. ΔV example for traditional signalized intersection diverging 

conflict point Trad-3. 

Continuing through the calculations, P(FSI) for one vehicle at this conflict point is shown in

figure 61. 
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Figure 61. Equation. Example of P(FSI) for one vehicle at traditional signalized 

intersection diverging conflict point Trad-3. 

Finally, the P(FSI) value for both vehicles at the conflict point is computed as follows in figure 62. 

Figure 62. Equation. Example of P(FSI) for both vehicles at traditional signalized 

intersection diverging conflict point Trad-3. 

This translates to a 6.52 x 10-5 percent probability of at least one fatal or serious injury 

occurring as a result of a crash between conflicting road users making the movements that 

define this conflict point.

As you can see, the conflict severity for the diverging conflict point is significantly less than for 

the left turn crossing conflict point. This is because the diverging conflict point involves lower 

speeds, smaller differential in speeds, and a much smaller collision angle.

As a final example of the severity calculations at a traditional signalized intersection, examine 

conflict point Trad-4 represented by the nonmotorized movement crossing the east leg and the 

northbound right turn originating from the minor road. This time, the procedure for computing 

the conflict point severity is slightly different, since this is a nonmotorized conflict point. There 

is only one vehicle speed, V, which in this case is 15 mph (“signal near” speed category in table 

10). Using the equation presented in figure 12, the P(FSI) is computed as shown in figure 63.

Figure 63. Equation. Example of P(FSI) at traditional signalized intersection

nonmotorized conflict point Trad-4. 

This translates to a 12.1 percent probability of a non-motorized fatal or serious injury occurring 

as a result of a crash between conflicting road users making the movements that define this 

conflict point.
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As you can see, the conflict severity for the nonmotorized conflict point is significantly higher 

than for both the left turn crossing and diverging conflict points, even though the vehicle speed 

involved was not higher than the vehicle-vehicle examples. This is because nonmotorized road 

users (i.e., pedestrians and cyclists) are generally much more vulnerable to crash forces than 

users traveling in motor vehicles.

Roundabout

For the roundabout, this example will examine the same three conflict points as in the 

exposure index example presented previously. 

First, consider crossing conflict point RAB-1 in the northeast quadrant of the intersection. The 

collision angle for a roundabout crossing conflict point is 60 degrees. Of the two movements at 

this conflict point, one is “Exiting” and one is “Entering,” so the speeds of the movements are 

30 mph and 20 mph, respectively. Given these values, ΔV is computed as shown in figure 64.

Figure 64. Equation. ΔV example for roundabout intersection crossing conflict point

RAB-1. 

Using this ΔV value, the P(FSI) for one vehicle at this conflict point is shown in figure 65.

Figure 65. Equation. Example of P(FSI) for one vehicle at roundabout intersection 

crossing conflict point RAB-1. 

Finally, the P(FSI) value for both vehicles at the conflict point is computed as follows in figure 66.

Figure 66. Equation. Example of P(FSI) for both vehicles at roundabout intersection 

crossing conflict point RAB-1. 

This translates to a 0.420 percent probability of at least one fatal or serious injury occurring as 

a result of a crash between conflicting road users making the movements that define this 

conflict point. 
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Next, consider merging conflict point RAB-2 in the southeast quadrant of the intersection, 

represented by the circulating movement that is exiting the roundabout eastbound and the 

movement coming northbound and turning right to also exit the roundabout eastbound. This is 

a merging conflict point; the collision angle is 45 degrees. Of the two movements at this conflict 

point, one is “Entering” and one is “Exiting,” so the speeds of the movements are once again 20 

mph and 30 mph respectively. Given these values, ΔV is computed as shown in figure 67. 

Figure 67. Equation. ΔV example for roundabout intersection merging conflict 

point RAB-2. 

Using this ΔV value, the P(FSI) for one vehicle at this conflict point is shown in figure 68.

Figure 68. Equation. Example of P(FSI) for one vehicle at roundabout intersection 

merging conflict point RAB-2. 

Finally, the P(FSI) value for both vehicles at the conflict point is computed as follows in figure 69. 

Figure 69. Equation. Example of P(FSI) for both vehicles at roundabout intersection 

merging conflict point RAB-2. 

This translates to a 0.183 percent probability of at least one fatal or serious injury occurring as 

a result of a crash between conflicting road users making the movements that define this 

conflict point.

As a final example for roundabout severity calculation, consider conflict point RAB-3,

represented by the nonmotorized movement crossing the north leg and the southbound 

entering traffic. The P(FSI) is computed by following the same nonmotorized severity process 

outlined in the traditional signalized intersection example. The vehicle movement is categorized 

as “Entering” the roundabout, so the vehicle speed, V, is 20 mph. Therefore, P(FSI) is computed 

as shown in figure 70.
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Figure 70. Equation. P(FSI) example for roundabout intersection nonmotorized

conflict point RAB-3. 

This translates to a 20.3 percent probability of a non-motorized fatal or serious injury occurring 

as a result of a crash between conflicting road users making the movements that define this 

conflict point.

Unsignalized RCUT

To explore the severity calculations for the unsignalized RCUT example, first examine merging 

conflict point RCUT-1, represented by the westbound left turning movement and the 

eastbound right turning movement. This is a merging conflict point, so the collision angle is 45 

degrees. The left-turning movement is assigned to the “Major left” speed category (20 mph). 

The right-turning movement is assigned to the “Major right” speed category (15 mph). Given 

these values, ΔV is computed as shown in figure 71. 

Figure 71. Equation. ΔV example for unsignalized RCUT intersection merging 

conflict point RCUT-1. 

Using this ΔV value, the P(FSI) for one vehicle at this conflict point is shown in figure 72. 

Figure 72. Equation. Example of P(FSI) for one vehicle at unsignalized RCUT 

intersection merging conflict point RCUT-1. 

Finally, the P(FSI) value for both vehicles at the conflict point is computed as follows in figure 73. 
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Figure 73. Equation. Example of P(FSI) for both vehicles at unsignalized RCUT 

intersection merging conflict point RCUT-1. 

This translates to a 0.0394 percent probability of at least one fatal or serious injury occurring as 

a result of a crash between conflicting road users making the movements that define this 

conflict point.

Next, consider merging conflict point RCUT-4, represented by the westbound through 

movement and the movement making a U-turn east of the main intersection. This is once again 

a merging conflict point, so the collision angle is 45 degrees. The through movement is assigned 

to the “Major through” speed category (equal to the posted speed limit, or 45 mph in this 

case). The U-turning movement at the unsignalized RCUT is stop-controlled, so this movement 

is assigned to the “Stop near” speed category (15 mph) given the location of the conflict point 

in relation to the stop bar. Given these values, ΔV is computed as shown in figure 74. 

Figure 74. Equation. ΔV example for unsignalized RCUT intersection merging 

conflict point RCUT-4. 

Using this ΔV value, the P(FSI) for one vehicle at this conflict point is shown in figure 75.

Figure 75. Equation. Example of P(FSI) for one vehicle at unsignalized RCUT 

intersection merging conflict point RCUT-4. 

Finally, the P(FSI) value for both vehicles at the conflict point is computed as follows in figure 76. 

Figure 76. Equation. Example of P(FSI) for both vehicles at unsignalized RCUT 

intersection merging conflict point RCUT-4. 
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This translates to a 1.35 percent probability of at least one fatal or serious injury occurring as a 

result of a crash between conflicting road users making the movements that define this conflict 

point. 

Finally, consider conflict point RCUT-3, represented by the nonmotorized movement crossing 

the major road and the westbound through turning movement. The vehicle movement is 

categorized as “Major through,” so the vehicle speed, V, is 45 mph. Therefore, P(FSI) is 

computed as shown in figure 77.

Figure 77. Equation. P(FSI) example for roundabout intersection nonmotorized

conflict point RCUT-3. 

This translates to an 84.9 percent probability of a non-motorized fatal or serious injury 

occurring as a result of a crash between conflicting road users making the movements that 

define this conflict point. This P(FSI) value is so high due to the high speed of the traffic on the 

major road in this example.

COMPLEXITY 

This section presents example calculations for the complexity steps of the SSI method, including 

the conflicting traffic complexity factor and nonmotorized complexity factor. For background 

on this part of the method, refer to section 3.7 of this report. 

Traditional Signalized

Conflicting Traffic Complexity Factor

Computing the conflicting traffic complexity factor involves determining the three separate 

parameters: atraffic control, aconflicting lanes, and aconflicting speed. 

Traffic Control. The first parameter is the traffic control parameter. Since the intersection is 

signalized, all movements are signal-controlled. 

To begin the example of the traffic control parameter for the traditional signalized intersection, 

consider the crossing conflict point Trad-1, represented by the eastbound through movement 

and the northbound right-turning movement. The signal phases of the two movements in 

question at conflict point Trad-1 operate in a fully protected manner (since the SSI method 

does not consider the provision of right-turn-on-red). Using the BTCAV of 0.01 for protected 
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movements and a weighting factor, f, of 0.5 (as discussed in chapter 4), the traffic control 

parameter is computed as shown in figure 78.

Figure 78. Equation. Traffic control parameter example for traditional signalized 

intersection crossing conflict point Trad-1. 

Next, consider crossing conflict point Trad-2, where the southbound through movement

conflicts with the northbound left turn from the minor. As noted in table 41, the minor road

left turns are not fully protected at this intersection, but rather operate under 

protected/permitted phasing. Using the BTCAV of 0.85 for protected/permitted movements and 

f = 0.5, the traffic control parameter is computed as shown in figure 79.

Figure 79. Equation. Traffic control parameter example for traditional signalized 

intersection left turn crossing conflict point Trad-2. 

As a third example of the traffic control parameter at the traditional signalized intersection 

alternative, consider conflict point Trad-5 where the northbound through meets the westbound 

through movement on the major road. These two movements are fully protected by the signal 

phasing. Therefore, the traffic control parameter for conflict point Trad-5 is computed using 

the same equation and inputs as in figure 78, resulting in atraffic control = 0.505.

Conflicting Lanes. The second parameter in the conflicting traffic complexity factor 

calculation is the conflicting lanes parameter. For this parameter, one must first identify the 

lower movement involved in each conflict point from the following list: 

1. Major through and right turn.

2. Major left turn.

3. Minor through and right turn. 

4. Minor left turn. 

5. Nonmotorized.

For our first traditional signalized intersection example conflict point, Trad-1 (the eastbound 

through and northbound right conflict point), the lower movement on the list is the 

northbound right. 
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The next step is to identify the cross score for the lower movement, the northbound right. 

The northbound right turn does not cross any intersection approaches, so the cross score is 

zero. 

The third step is to determine the merge score for the lower movement. The merge score 

considers the number of lanes carrying conflicting traffic as that conflicting traffic approaches 

the merging conflict point. Table 12 shows the equations for the merge score. To calculate the 

merge score, note that at conflict point Trad-1, the right-turning movement from the minor 

road is merging with through-moving traffic from a major road approach having two through 

traffic lanes (the eastbound through movement), therefore M = 1 and NM = 2. The calculation of 

the merge score in this example is shown in figure 83.

Figure 80. Equation. Merge score example for traditional signalized intersection 

merging conflict point Trad-1.

The merge score is added to the cross score to determine the conflicting lane parameter, 

aconflicting lanes, as illustrated in figure 81. 

Figure 81. Equation. Conflicting lanes parameter example for traditional signalized 

intersection merging conflict point Trad -1. 

For the next example of the conflicting lanes parameter, examine conflict point Trad-2, where 

the southbound through movement meets the northbound left-turning movement. The 

northbound left turn is the lower movement on the list of movements. The northbound left 

turn movement crosses the near-side approach of the major road carrying eastbound 

conflicting traffic—two lanes in this case—plus the opposing minor road approach carrying 

southbound conflicting traffic—one lane in this case. A median is not present to provide refuge 

to the left-turning vehicle and allow a two-stage movement. Thus, the resulting crossing score 

for this left turn from the minor road is 2 + 1 = 3.
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In this example, the left-turning movement from the minor road is merging with traffic from a 

major road approach having two through traffic lanes (the westbound through movement), 

therefore M = 1 and NM = 2. The merge score is then calculated in the same way as shown in 

figure 83, resulting again in a merge score of 1.75. The merge score is added to the cross score 

to determine the conflicting lane parameter, aconflicting lanes, for conflict point Trad-2 as illustrated in 

figure 82. 

Figure 82. Equation. Conflicting lanes parameter example for traditional signalized 

intersection crossing conflict point Trad-2.

This value of the conflicting lanes parameter would also apply to all other crossing and merging 

conflict points in which the northbound left turn is the lower movement on the list of 

movements. 

As a third example, consider conflict point Trad-5, where the northbound through movement 

meets the westbound through movement. The northbound through movement is lower on the 

list of movements. The northbound through movement crosses both the eastbound approach 

on the near-side of the intersection – two through lanes in this case – and the westbound

approach on the far side of the intersection – another two lanes. A median is not present to 

provide refuge and allow a two-stage movement. Thus, the resulting cross score for the minor 

road through movement is 2 + 2 = 4. 

The next step is to determine the merge score for the northbound through movement. The 

northbound through movement is not one of the movements where the merge score applies.

Therefore, the value of M is 0 and the merge score for this movement is also 0. The merge 

score is added to the cross score to produce the conflicting lane parameter, aconflicting lanes, as 

shown in figure 83.

Figure 83. Equation. Conflicting lanes parameter example for traditional signalized 

intersection crossing conflict point Trad-5. 

Note that this value of the conflicting lanes parameter would also be applied to any other 

crossing and merging conflict points at which the northbound through is the lower-priority 

movement.

Speed of Conflicting Traffic. For the first example of the conflicting speed parameter, 
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aconflicting speed, refer to conflict point Trad-1 (eastbound through at northbound right). The 

conflicting speed parameter requires one input: Vc, the conflicting vehicle speed. This is the 

highest speed of any of the traffic streams conflicting with the lower movement. In this case, the 

lower movement is the northbound right, and it only has one traffic stream: the eastbound 

through. Using the speed assumptions in table 10, the eastbound through movement is assigned 

the posted speed limit, or 45 mph in this case (based on taking the midpoint value of the typical 

range represented in the table).

The conflicting speed parameter is computed by plugging this conflicting vehicle speed into 

figure 84, which calculates a 15 percent reduction in crash likelihood for every 10 percent 

reduction in vehicle speed below a benchmark of 60 mph.

Figure 84. Equation. Conflicting speed parameter example for traditional signalized 

intersection merging conflict point Trad-1. 

Next, consider conflict point Trad-2 (southbound through at northbound left). In this case, the 

lower movement (the northbound left) has several conflicting traffic streams: eastbound 

through, westbound through, and southbound through. The highest speed of any of these 

conflicting traffic streams belongs to the major road through movements at 45 mph, so the 

conflicting speed parameter is calculated the same as shown in figure 84 and is equal to 0.833.It 

follows that the conflicting speed parameter for conflict point Trad-5 (northbound through at 

westbound through) is also 0.833 in this example.

Computing the Conflicting Traffic Complexity Factor. The traffic control parameter, 

conflicting lanes parameter, and conflicting speed parameter are multiplied together to produce 

the conflicting traffic complexity factor, as shown in figure 17. 

The results of the conflicting traffic complexity factor for the three traditional signalized 

intersection example conflict points used here are shown in figure 85, figure 86, and figure 87.

Figure 85. Equation. Conflicting traffic complexity factor example for traditional 

signalized intersection merging conflict point Trad-1.
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Figure 86. Equation. Conflicting traffic complexity factor example for traditional 

signalized intersection crossing conflict point Trad-2.

Figure 87. Equation. Conflicting traffic complexity factor example for traditional 

signalized intersection crossing conflict point Trad-5.

Nonmotorized Movement Complexity Factor

The nonmotorized movement complexity factor, L2, is also computed for each conflict point in 

addition to the conflicting traffic complexity factor. However, for vehicle-vehicle conflict points 

the nonmotorized movement complexity factor is set to 1, as described in section 3.7.3. 

Additionally, the nonmotorized movement complexity factor is only applied to nonmotorized 

conflict points with movements that are part of indirect pedestrian movements or that 

encounter nonintuitive motor vehicle movements. None of the nonmotorized conflict points at 

the traditional signalized intersection exhibit these characteristics, so the value of L2 is equal to 

one for all nonmotorized conflict points at a traditional signalized intersection. 

Roundabout

Conflicting Traffic Complexity Factor

Traffic Control. In the case of the traffic control parameter for the roundabout intersection 

design, none of the movements at the roundabout are signal- or stop-controlled (but rather, 

yield controlled). Therefore, the traffic control parameter at all roundabout conflict points is 

simply 1. 

Conflicting Lanes. For the conflicting lanes parameter, first consider crossing conflict point 

RAB-1 (northeast quadrant, northbound exiting at westbound entering). The lower priority 

movement at a roundabout is the entering movement. At this entry of the 2x1 roundabout, the 

traffic entering from the major road and continuing in the circulatory roadway is crossing the 

conflicting exiting movement that is being carried by one circulating lane. Therefore, the cross 

score for crossing conflict point RAB-1 is 1. The merge score does not apply at crossing 

conflict point RAB-1. The value of M is 0 and the merge score for crossing conflict point RAB-1 

is also 0. The conflicting lanes parameter for crossing conflict point RAB-1 is the cross score 

plus the merge score, which is 1. 
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Next, consider merging conflict point RAB-2 (southeast quadrant, northbound right-turning and 

eastbound exiting). In this case, the entering movement is once again the lower-priority 

movement. But in this case, there are two circulating lanes in the roundabout due to the 

geometry of a 2x1 roundabout at this entry. In this case, the lower-priority movement is not 

crossing the exiting movement being carried by these two lanes, so the cross score is 0. The 

merge score does apply and is calculated as shown in figure 88 with M = 1 and NM = 2.

Figure 88. Equation. Merge score example for roundabout intersection merging 

conflict point RAB-2.

As an example of a nonmotorized conflict point, examine conflict point RAB-3 (nonmotorized 

movement crossing the north leg). The nonmotorized movement passing through this conflict 

point is the lower movement on the list of movements, and it is crossing both the entering and 

exiting traffic streams on the north leg. However, the SSI method assumes that all roundabouts 

have pedestrian refuge islands (i.e., splitter islands) on all approaches (as stated in appendix A). 

Therefore, the nonmotorized movement must only cross one of these traffic streams at a time. 

Since the nonmotorized road user at this point is crossing the minor approach of a 2x1 

roundabout, there is only one lane in each direction on the approach, and thus the cross score 

for this conflict point is equal to 1. The conflicting lanes parameter for nonmotorized conflict 

points uses the nonmotorized turn score in place of the merge score. In this case, due to the 

geometry of roundabouts, the nonmotorized road user at conflict point RAB-3 is not scanning 

any other approaches for oncoming traffic beyond the approach being crossed. Therefore, the 

nonmotorized turn score is 0, and the conflicting lanes score for conflict point RAB-3 is 1 + 0 = 

1. 

Conflicting Speed. In most cases at a roundabout, the conflicting vehicle speed that applies to 

the lower-priority movement is the circulating speed (here assumed to be 25 mph). This is the 

case for conflict points RAB-1, RAB-2, and RAB-4. The conflicting speed parameter is computed 

by plugging this conflicting vehicle speed into figure 89.

Figure 89. Equation. Conflicting speed parameter example for roundabout 

intersection conflict points RAB-1, RAB-2, and RAB-4. 

The exceptions to this are the nonmotorized conflict points. Due to the placement of 

crosswalks and presence of splitter islands for pedestrian refuge at roundabouts, the 

nonmotorized movements have a conflicting vehicle speed equal to either the entering or 
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exiting speed. In the case of conflict point RAB-3, where the nonmotorized movement conflicts 

with the southbound entering movement, the entering speed is applied. This results in a 

conflicting speed parameter as shown in figure 90. 

Figure 90. Equation. Conflicting speed parameter example for roundabout 

intersection nonmotorized conflict point RAB-3.

Computing the Conflicting Traffic Complexity Factor. The traffic control parameter, 

conflicting lanes parameter, and conflicting speed parameter are multiplied together to produce 

the conflicting traffic complexity factor, as shown in figure 17. 

The results of the conflicting traffic complexity factor for the four roundabout example conflict 

points are shown in figure 91, figure 92, figure 93, and figure 94. 

Figure 91. Equation. Conflicting traffic complexity factor example for roundabout 

intersection crossing conflict point RAB-1.

Figure 92. Equation. Conflicting traffic complexity factor example for roundabout 

intersection merging conflict point RAB-2.

Figure 93. Equation. Conflicting traffic complexity factor example for roundabout 

intersection nonmotorized conflict point RAB-3.

Figure 94. Equation. Conflicting traffic complexity factor example for roundabout 

intersection merging conflict point RAB-4.
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Nonmotorized Movement Complexity Factor

As an example of the nonmotorized movement complexity factor, consider the nonmotorized

movement crossing the north leg of the 2x1 roundabout at conflict point RAB-3. Due to the 

geometry of a modern roundabout and the placement of crosswalks, nonmotorized road users 

travel around the perimeter of the roundabout. For this reason, the calculations in this report 

apply the indirect paths indicator to all nonmotorized conflict points at roundabouts. The

nonintuitive vehicle movements indicator does not apply to roundabouts, so it is set to zero.

The value of the nonmotorized movement complexity factor for conflict point RAB-3 (and all 

other nonmotorized roundabout conflict points) is therefore 2, as shown in figure 95.

Figure 95. Equation. Nonmotorized movement complexity factor example for 

roundabout intersection nonmotorized conflict point RAB-3. 

Unsignalized RCUT

Conflicting Traffic Complexity Factor

Traffic Control. To demonstrate the traffic control parameter for the unsignalized RCUT 

intersection, first consider merging conflict point RCUT-1 (westbound left-turn and eastbound 

right-turn). The left-turn movements at unsignalized RCUTs are typically stop-controlled, so 

the two movements in question operate under stop-control. Using the BTCAV of 0.45 for stopcontrolled movements and (once again) a weighting factor, f, of 0.5, the traffic control 

parameter is computed as shown in figure 96.

Figure 96. Equation. Traffic control parameter example for unsignalized RCUT

intersection merging conflict point RCUT-1. 

Conflict point RCUT-2 (eastbound through and eastbound U-turn) is a diverging conflict point, 

and thus does not have any traffic control applied to it, so the traffic control parameter is equal 

to 1. 

Conflict point RCUT-3, where the nonmotorized movement crossing the major road conflicts 

with the westbound through movement, does not have any traffic control adjustment applied to 

it. This is because at the unsignalized RCUT there is no stop control or signal control applied to 

through-traffic on the major road. In some cases, a pedestrian signal or other measure may be 

installed to control vehicle traffic while nonmotorized road users cross the major road, but that 
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is not considered for the purpose of this example. Therefore, the traffic control parameter for 

conflict point RCUT-3 is also equal to one.

Finally, examine conflict point RCUT-4, where the U-turning traffic east of the main 

intersection meets the westbound through traffic. The U-turns at unsignalized RCUTs are 

typically stop-controlled, so the traffic control parameter is computed the same way as in figure 

96 and is equal to 0.725.

Conflicting Lanes. For the first example of the conflicting lanes parameter at the unsignalized 

RCUT, examine conflict point RCUT-1 (westbound left-turn merging with eastbound rightturn). In this case the westbound left movement is the lower movement. It crosses one 

approach (the eastbound approach) carrying conflicting traffic. The eastbound approach has two 

lanes. The cross score for this conflict point is 2. the merge score does not apply to this 

conflict point, therefore M = 0 and the merge score also equals 0. The conflicting lanes 

parameter is computed as shown in figure 97.

Figure 97. Equation. Example of conflicting lanes parameter for unsignalized RCUT

intersection merging conflict point RCUT-1.

Conflict point RCUT-2 (where the east U-turn movement diverges from the eastbound 

through) is a diverging conflict point, so the conflicting lanes parameter is set to equal one.

At conflict point RCUT-3, where the nonmotorized movement crosses the westbound through 

movement, the nonmotorized movement crosses one major approach at a time due to the 

presence of median refuge inherent in the design of an RCUT (see appendix A). the major road 

carries two lanes in each direction in this example, so the cross score for conflict point RCUT3 is equal to 2. As with the roundabout, at this point the nonmotorized road user is not 

scanning any other approaches for oncoming traffic, so there is no pedestrian turn score 

applied to the conflict point. The conflicting lanes parameter for conflict point RCUT-3 is 

computed as shown in figure 98.

Figure 98. Equation. Example of conflicting lanes parameter for unsignalized RCUT

intersection nonmotorized conflict point RCUT-3.

Finally, the merge score comes into play for conflict point RCUT-4, where the westbound 

through movement meets the U-turn movement east of the main intersection. The U-turning 

movement is the lower movement on the list of movements. It does not cross any approaches 

carrying conflicting traffic, so the cross score is 0. The merge score applies to this conflict point, 
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so the merge score is computed as shown in figure 99 with M = 1 and NM = 2.

Figure 99. Equation. Merge score example for unsignalized RCUT intersection 

merging conflict point RCUT-4.

Conflicting Speed. All movements through crossing or merging conflict points at an RCUT 

interact with at least one major road through movement. This means that the conflicting vehicle 

speed for all of the vehicle-vehicle crossing and merging conflict points as well as the 

nonmotorized conflict points crossing the major road is equal to the major road through speed. 

In this case that is 45 mph. Therefore, the conflicting speed parameters for conflict points 

RCUT-1, RCUT-2, RCUT-3, and RCUT-4 are all equal, and are calculated as shown in figure 

100.

Figure 100. Equation. Conflicting speed parameter example for unsignalized RCUT

intersection conflict points RCUT-1, RCUT-2, RCUT-3, and RCUT-4.

Computing the Conflicting Traffic Complexity Factor. The traffic control parameters, 

conflicting lanes parameters, and conflicting speed parameters are multiplied together to 

produce the conflicting traffic complexity factor, as shown in figure 17. 

The results of the conflicting traffic complexity factor for the four unsignalized RCUT

intersection example conflict points used here are shown in figure 101, figure 102, figure 103, 

and figure 104.

Figure 101. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection merging conflict point RCUT-1.

Figure 102. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection diverging conflict point RCUT-2.
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Figure 103. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection nonmotorized conflict point RCUT-3.

Figure 104. Equation. Conflicting traffic complexity factor example for unsignalized 

RCUT intersection merging conflict point RCUT-4.

Nonmotorized Movement Complexity Factor

As an example of the nonmotorized movement complexity factor, consider the nonmotorized

movement crossing the major road and intersecting with the westbound movement at conflict 

point RCUT-3. Due to the Z-crossing pattern typically employed at RCUT intersections, 

nonmotorized road users who are crossing the major road may be required to take an indirect 

path. For this reason, the indirect paths indicator is applied to all nonmotorized conflict points 

crossing the major road at RCUTs. The nonintuitive vehicle movements indicator is not applied, 

so it is set to 0. The value of the nonmotorized movement complexity factor for conflict point 

RCUT-3 is therefore 2, as shown in figure 105. 

Figure 105. Equation. Nonmotorized movement complexity factor example for 

unsignalized RCUT intersection conflict point RCUT-3.
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SUMMARY OF EXAMPLE RESULTS

The information in table 43, table 44, and table 45 summarizes the inputs and results of the example calculations presented in this 

appendix. 

Table 43. Summary of exposure calculation example results. 

Intersection 

Type 

Conflict 

Point 

Name

Q1 Q2 I 

Traditional 

Signalized

T-1 6,250 2,500 15,625,000 

T-2 5,000 2,500 12,500,000 

Roundabout 

RAB-1 8,125 9,375 76,171,875 

RAB-2 8,750 2,500 21,875,000 

RAB-3 600 10,000 6,000,000 

Unsignalized 

RCUT

RCUT-1 3,125 8,125 25,390,625 

RCUT-2 11,250 7,500 84,375,000 

RCUT-3 1,200 8,750 10,500,000 

 
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Table 44. Summary of severity calculation example results. 

Intersection 

Type 

Conflict 

Point 

Name

V1 V2 Angle ΔV P(FSI)one veh P(FSI)

Traditional 

Signalized

T-2 15 25 230 18.25 0.00712 0.0142 

T-3 15 15 10 1.31 0.000000326 0.000000652 

T-4 -- 15 -- -- -- 0.121 

Roundabout 

RAB-1 30 20 60 13.23 0.00210 0.00420 

RAB-2 30 20 45 10.62 0.000916 0.00183 

RAB-3 -- 20 -- -- -- 0.203 

Unsignalized 

RCUT

RCUT-1 20 15 45 7.08 0.000197 0.000394 

RCUT-3 -- 45 -- -- -- 0.849 

RCUT-4 45 15 45 18.00 0.00675 0.0135 

Note: -- represents calculation steps that were not necessary for a given conflict point (e.g., ΔV is not calculated for 

nonmotorized conflict points and the pedestrian complexity indicators iindirect and inonintuitive do not apply to vehicle-vehicle conflict 

points).
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Table 45. Summary of complexity calculation example results.

Intersection 

Type 

Conflict 

Point 

Name

BTCAV f atraffic 

control

aconflicting 

lanes

Vc 

aconflicting 

speed

L1 iindirect inonintuitive L2 

Traditional 

Signalized

T-1 0.01 0.5 0.505 1.75 45 0.833 0.736 -- -- 1 

T-2 0.85 0.5 0.925 4.75 45 0.833 3.66 -- -- 1 

T-5 0.01 0.5 0.505 4 45 0.833 1.68 -- -- 1 

Roundabout 

RAB-1 1 0.5 1 1 25 0.611 0.611 -- -- 1 

RAB-2 1 0.5 1 1.75 25 0.611 1.07 -- -- 1 

RAB-3 1 0.5 1 1 20 0.556 0.556 1 0 2 

RAB-4 1 0.5 1 1.75 25 0.611 1.07 -- -- 1 

Unsignalized 

RCUT

RCUT-1 0.45 0.5 0.725 2 45 0.833 1.21 -- -- 1 

RCUT-2 1 0.5 1 1 45 0.833 0.833 -- -- 1 

RCUT-3 1 0.5 1 2 45 0.833 1.67 1 0 2 

RCUT-4 0.45 0.5 0.725 1.75 45 0.833 1.06 -- -- 1 

Note: -- represents calculation steps that were not necessary for a given conflict point (e.g., ΔV is not calculated for nonmotorized conflict 

points and the pedestrian complexity indicators iindirect and inonintuitive do not apply to vehicle-vehicle conflict points).
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COMPUTATION OF THE SSI SCORE

Once these calculations have been performed for all the conflict points at a given intersection 

alternative, the SSI score can be computed for that alternative according to the procedure 

outlined in section 3.7. This section of appendix B will display how to compute the SSI score for 

one alternative, the unsignalized RCUT.

The following tables (Table 46, Table 47, Table 48, Table 49) contain the full results for the 

exposure index (I), probability of fatality or serious injury (P(FSI)), conflicting traffic complexity 

factor (L1), and nonmotorized movement complexity factor (L2) for all 24 conflict points at an 

unsignalized RCUT (depicted in figure 39). The rightmost column in these tables shows the 

exposure-severity-complexity product for each conflict point, computed by multiplying the 

contents other four columns as described in section 3.7. At the bottom of each table, the sum of 

the exposure-severity-conflict points is shown for each conflict point type. This represents Et. 

Table 46. Exposure-severity-complexity product results for unsignalized RCUT 

crossing conflict points.

Conflict 

Point 

Type 

Conflict 

Point 

Name

I P(FSI) L1 L2 

ExposureSeverityComplexity 

Product

Crossing -- 27,343,750 0.0903 1.208 1 2,983,102 

Crossing -- 27,343,750 0.0903 1.208 1 2,983,102 

Sum: 5,966,203

Note: -- represents conflict points that were not included in the example calculations in 

appendix B.
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Table 47. Exposure-severity-complexity product results for unsignalized RCUT 

merging conflict points.

Conflict 

Point 

Type 

Conflict 

Point 

Name

I P(FSI) L1 L2 

ExposureSeverityComplexity 

Product

Merging -- 87,500,000 0.0134 1.057 1 1,237,263 

Merging RCUT-1 25,390,625 0.000390 1.208 1 11,972 

Merging -- 87,500,000 0.0134 1.057 1 1,237,263 

Merging -- 25,390,625 0.000390 1.208 1 11,972 

Merging RCUT-4 93,750,000 0.0134 1.057 1 1,325,639 

Merging -- 93,750,000 0.0134 1.057 1 1,325,639 

Sum: 5,149,750

Note: -- represents conflict points that were not included in the example calculations in 

appendix B.

Table 48. Exposure-severity-complexity product results for unsignalized RCUT 

diverging conflict points.

Conflict 

Point 

Type 

Conflict 

Point 

Name

I P(FSI) L1 L2 

ExposureSeverityComplexity 

Product

Diverging -- 52,734,375 0.00365 1 1 192,385 

Diverging -- 71,093,750 0.00701 1 1 498,056 

Diverging RCUT-2 84,375,000 0.00365 1 1 307,817 

Diverging -- 52,734,375 0.00365 1 1 192,385 

Diverging -- 71,093,750 0.00701 1 1 498,056 

Diverging -- 84,375,000 0.00365 1 1 307,817 

Sum: 1,996,516

Note: -- represents conflict points that were not included in the example calculations in 

appendix B.
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Table 49. Exposure-severity-complexity product results for unsignalized RCUT 

nonmotorized conflict points.

Conflict 

Point Type

Conflict 

Point 

Name

I P(FSI) L1 L2 

ExposureSeverityComplexity 

Product

Nonmotorized -- 4,875,000 0.121 3.750 1 2,202,898 

Nonmotorized -- 1,875,000 0.321 2.719 1 1,634,659 

Nonmotorized -- 6,000,000 0.121 2.166 1 1,565,978 

Nonmotorized -- 9,750,000 0.121 1.667 2 3,916,263 

Nonmotorized -- 10,500,000 0.849 1.667 2 29,699,369 

Nonmotorized RCUT-3 10,500,000 0.849 1.667 2 29,699,369 

Nonmotorized -- 9,750,000 0.121 1.667 2 3,916,263 

Nonmotorized -- 4,875,000 0.121 3.750 1 2,202,898 

Nonmotorized -- 1,875,000 0.321 2.719 1 1,634,659 

Nonmotorized -- 6,000,000 0.121 2.166 1 1,565,978 

Sum: 78,038,336

Note: -- represents conflict points that were not included in the example calculations in 

appendix B.

The conflict point type SSI score, SSIt, can be computed for each of the four conflict point types

t according to figure 15. For this unsignalized RCUT example, these calculations are carried out 

in figure 106, figure 107, figure 108, and figure 109. 

Figure 106. Equation. Example conflict point type SSI score for unsignalized RCUT 

crossing conflict points.

Figure 107. Equation. Example conflict point type SSI score for unsignalized RCUT 

merging conflict points.
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Figure 108. Equation. Example conflict point type SSI score for unsignalized RCUT 

crossing conflict points.

Figure 109. Equation. Example conflict point type SSI score for unsignalized RCUT 

crossing conflict points.

Based on these conflict point type SSI scores, the SSI intersection score for the unsignalized 

RCUT in this example can then be computed according to the equation in figure 16. The result 

of this calculation is shown in figure 110. This score represents the overall Safe System 

performance of the unsignalized RCUT in this example.

Figure 110. Equation. Example intersection SSI score for unsignalized RCUT.
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