ii

Foreword

The Highway Safety Improvement Program (HSIP) Manual updates the 1981 HSIP User’s 

Manual (FHWA-TS-81-218) to reflect current law, regulations and new and emerging technologies and noteworthy practices regarding state and local highway safety improvement programs 

and related activities. The HSIP consists of three main components that are essential to the success of the program: planning, implementation and evaluation.

The process and procedures outlined in the Manual can be used by state agencies to administer the 

HSIP, as required by 23 CFR 924. In addition, transportation planning organizations, as well as 

county and local government agencies can use the HSIP Manual to plan, implement, and evaluate 

highway safety improvement programs and projects that best meet their capabilities and needs.

For additional information, please contact the HSIP Team in the Office of Safety. We wish you 

continued success in implementing programs and projects to reduce the number of fatalities and 

serious injuries on our nation’s roadways.

Joseph S. Toole

Associate Administrator

Office of 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. This report does not constitute a standard, specification, 

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

or manufacturers’ names may 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.
iii

Technical Report Document Page

1. Report No.

FHWA-SA-09-029

2. Government Accession No.

 

3. Recipient’s Catalog No.

 

4. Title and Subtitle

Highway Safety Improvement Program (HSIP) Manual

5. Report DateJanuary 2010

6. Performing Organization Code

7. Author(s) Susan Herbel, Lorrie Laing, Colleen McGovern 8. Performing Organization Report 

No.

9. Performing Organization Name and Address

Cambridge Systematics, Inc.

100 Cambridge Park Drive, Suite 400

Cambridge, MA 02140

10. Work Unit No.

11. Contract or Grant No.

DTFH61-05-D-00026

12. Sponsoring Agency Name and Address

Department of Transportation

Federal Highway Administration

Office of Safety

400 Seventh Street S.W.

Washington, DC 20590

13. Type of Report and Period 

Covered Technical Manual

14. Sponsoring Agency Code

HSSP

15. Supplementary Notes

FHWA COTM: Karen Yunk, Office of Safety

Technical oversight working group members: Bryan Allery (Colorado Department of Transportation), 

Roya Amjadi (TFHRC), Thomas Elliott (National Highway Institute), Reed Henry (Arizona Department 

of Transportation), Dan Magri (Louisiana Department of Transportation and Development), Bonnie 

Polin (Massachusetts Highway Department), Jacinda Russell (FHWA NH Division), Joseph Santos 

(Florida Department of Transportation), Kurt Smith (Alaska Department of Transportation and Public 

Facilities), Betsey Tramonte (FHWA LA Division), and Rudolph Umbs (FHWA Resource Center). 

16. Abstract

This HSIP Manual describes the overall Highway Safety Improvement Program and provides a 

roadway safety management process which focuses on results by emphasizing a data-driven, strategic 

approach to improving highway safety through infrastructure-related improvements. Current laws 

and regulations, new and emerging technologies, and noteworthy practices are presented for each of 

the HSIP’s four basic steps – analyze data, identify potential countermeasures, prioritize and select 

projects and determine effectiveness.

This comprehensive highway reference is intended for state and local transportation safety practitioners 

working on HSIPs and safety projects. 

17. Key Words

Highway Safety Improvement Program (HSIP), 

safety management, countermeasure identification, project prioritization, Safety Performance 

Functions (SPF), Crash Modification Factors 

(CMF).

18. Distribution Statement

No restrictions. This document is available to the 

public through the National Technical Information 

Service, Springfield, VA 22161.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page) 

Unclassified

21. No. of Pages 

161

22. 

Price

Form DOT F 1700.7 (8-72) Reproduction of completed pages authorized

v

Highway Safety Improvement Program Manual

Report No. FHWA- SA-09-029

Prepared by

Cambridge Systematics Inc.

Chicago, Illinois

Prepared for

Federal Highway Administration

U.S. Department of Transportation

January 2010

vii

Preface

The Safe, Accountable, Flexible, Efficient Transportation Equity Act – a Legacy 

for Users (SAFETEA-LU) established the Highway Safety Improvement Program 

(HSIP) as a core Federal-aid highway program. SAFETEA-LU reinforced the 

need for strategic planning and data-driven decisions. The Federal Highway 

Administration (FHWA) provided clarifying guidance to the States via updates 

to the Federal regulation that supports the HSIP (23 CFR 924). However, these 

actions require additional guidance for state departments of transportation and 

local government agencies to implement programs that will achieve a significant 

reduction in traffic fatalities and serious injuries on public roads.

The Highway Safety Improvement Program (HSIP) Manual provides an overview of the HSIP and outlines procedures and tools to assist transportation professionals with the planning, implementation and evaluation phases of the HSIP. 

The HSIP Manual was developed based on the latest research, as well as state and 

local practices, pertaining to roadway safety management processes. Hyperlinks 

throughout the document connect the user to valuable resources to assist with 

their decision-making processes. The HSIP Manual is a valuable tool and a 

comprehensive reference for state and local transportation safety practitioners 

working to advance the HSIP and other safety projects.

A technical oversight working group, consisting of Federal and state representatives, guided the development of the HSIP Manual. The primary role of the 

working group was to review various aspects of the HSIP Manual for technical 

accuracy and recommend best practices and procedures to ensure the Manual 

meets practitioner needs. Their gracious contributions and expertise will support 

the development of many life-saving programs resulting in fewer fatalities and 

serious injuries on our nation’s roadways.

1

 All hyperlinks in this document were tested and operational in October 2009.

ix

Table of Contents

1.0 HSIP Foundations............................................................................................... 1-1

1.1 HSIP Manual Purpose and Contents....................................................... 1-1

1.2 The Nature of Road Safety ........................................................................ 1-3

1.3 Background and History of the HSIP...................................................... 1-8

1.4 Current Legislation and Agency Guidelines........................................ 1-10

1.5 Integrating Safety into the Project Development Processes............... 1-13

1.6 Safety Goals, Objectives, and Performance Measures ........................ 1-18

1.7 Resources and Technologies ................................................................... 1-21

1.8 Summary.................................................................................................... 1-21

2.0 Planning: Problem Identification ................................................................... 2-1

2.1 Nominal and Substantive Safety.............................................................. 2-1

2.2 Data Collection............................................................................................ 2-2

2.3 Data Analysis Concepts........................................................................... 2-11

2.4 Network Screening Process..................................................................... 2-17

2.5 Summary.................................................................................................... 2-31

3.0 Planning: Countermeasure Identification..................................................... 3-1

3.1 Step 1 – Analyze the Data.......................................................................... 3-1

3.2 Step 2 – Assess Site Conditions ................................................................ 3-9

3.3 Step 3 – Identify Potential Countermeasures......................................... 3-10

3.4 Step 4 – Assess Countermeasure Effectiveness.................................... 3-11

3.5 Engineering Case Study .......................................................................... 3-15

3.6 Summary.................................................................................................... 3-20

4.0 Planning: Project Prioritization.......................................................................... 4-1

4.1 The Objective Approach............................................................................ 4-1

4.2 Benefit/Cost Analysis................................................................................ 4-3

4.3 Countermeasure Evaluation Methods..................................................... 4-8

4.4 Prioritization Methods............................................................................. 4-10

4.5 Approaches Addressing Current and Future Safety Problems......... 4-14

4.6 Summary.................................................................................................... 4-16

5.0 Implementation................................................................................................... 5-1

5.1 HSIP Funding Requirements .................................................................... 5-1
x

5.2 Federal Safety Funding Sources ............................................................... 5-2

5.3 Funding Allocation Issues......................................................................... 5-6

5.4 Programming Projects ............................................................................... 5-8

5.5 Evaluation Plan Development.................................................................. 5-9

5.6 Summary...................................................................................................... 5-9

6.0 Evaluation ............................................................................................................ 6-1

6.1 Project Evaluation....................................................................................... 6-1

6.2 Program Evaluation ................................................................................. 6-13

6.3 Feedback to Future Planning.................................................................. 6-20

6.4 Summary.................................................................................................... 6-21

Appendices

A. Multidisciplinary Case Study ......................................................................... A-1

B. Resources..............................................................................................................B-1

B.1 Unit 1 ............................................................................................................B-1

B.2 Unit 2 ............................................................................................................B-2

B.3 Unit 3 ............................................................................................................B-3

B.4 Unit 4 ............................................................................................................B-4

B.5 Unit 5 ............................................................................................................B-5

B.6 Unit 6 ............................................................................................................B-5

C. The Haddon Matrix........................................................................................... C-1

D. Glossary...............................................................................................................D-1

E. References ............................................................................................................E-1
xi

List of Tables

Table 1.1 Potential Safety Tasks in the Preliminary Design Process ................ 1-15

Table 2.1 Summary of Problem Identification Methodologies.......................... 2-22

Table 2.2 Screening Method Applications............................................................ 2-24

Table 3.1 Intersection Collision Summary.............................................................. 3-7

Table 3.2 Collision Summary ................................................................................. 3-16

Table 4.1 Relative Disutility Factors by Injury Severity Level (MAIS) .............. 4-4

Table 4.2 Crash Costs by Injury Severity Level ..................................................... 4-5

Table 6.1 Safety Evaluation Method Data Requirements................................... 6-12

Table C.1 Haddon Matrix ..........................................................................................C-1

xiii

List of Figures

Figure 1.1 Highway Safety Improvement Program Components........................ 1-2

Figure 1.2 Per Person Cost of Crashes versus Congestion .................................... 1-4

Figure 1.3 Relationships of HSIP Programs........................................................... 1-10

Figure 1.4 Relationships between the SHSP and HSIP ........................................ 1-12

Figure 1.5 Coordinated Transportation Safety Planning..................................... 1-14

Figure 2.1 Variations in Crash Frequency.............................................................. 2-12

Figure 2.2 Data Series for Example Intersection ................................................... 2-13

Figure 2.3 Example of Regression to the Mean ..................................................... 2-14

Figure 2.4 SPF with Individual Site Data ............................................................... 2-15

Figure 2.5 Empirical Bayes Method ........................................................................ 2-16

Figure 3.1 Crash Types at an Intersection................................................................ 3-2

Figure 3.2 Crash Factors.............................................................................................. 3-3

Figure 3.3 Collision Diagram ..................................................................................... 3-8

Figure 3.4 Intersection Collision Diagram ............................................................. 3-17

Figure 6.1 Simple Before/After Evaluation ............................................................. 6-4

Figure 6.2 Empirical Bayes Method .......................................................................... 6-6

Figure 6.3 Before/After Evaluation Using the EB Method.................................... 6-8

Figure 6.4 Before/After Evaluation Using a Comparison Group ........................ 6-9

Figure 6.5 Cross-Sectional Evaluation .................................................................... 6-11

Figure 6.6 General Statistics ..................................................................................... 6-14

Figure 6.7 Trend Analysis......................................................................................... 6-15

Figure 6.8 SHSP Emphasis Area.............................................................................. 6-17

Figure 6.9 HSIP Subprogram ................................................................................... 6-18

Figure 6.10 Systemic Treatment................................................................................. 6-19

xv

Abbreviations

AADT – Annual Average Daily Traffic

AASHTO – American Association of State Highway Transportation Officials

ADT – Average Daily Traffic

ATSSA – American Traffic Safety Services Association

BAC – Blood Alcohol Concentration

BCR – Benefit/Cost Ratio

CFR – Code of Federal Regulations

CMAQ – Congestion Mitigation and Air Quality Improvement Program

CMF – Crash Modification Factors

CMV – Commercial Motor Vehicle

CODES – Crash Outcome Data Evaluation System

CRF – Crash Reduction Factor

CVSP – Commercial Vehicle Safety Plan

DMV – Department of Motor Vehicles

DOT – Department of Transportation

DUI – Driving Under the Influence

EB – Empirical Bayes

EMS – Emergency Medical Services

EPDO – Equivalent Property Damage Only

FARS – Fatality Analysis Reporting System

FHWA – Federal Highway Administration

FMCSA – Federal Motor Carrier Safety Administration

FTA – Federal Transit Administration

FTYROW – Failed to Yield Right-of-way

FY – Fiscal Year

GAO – Government Accountability Office

GES – General Estimates System

GHSA – Governors Highway Safety Association

GIS – Geographic Information System
xvi

GPS – Global Positioning Systems

GR – Governors Representative for Highway Safety

HPMS – Highway Performance Monitoring System

HRRRP – High-Risk Rural Roads Program

HSIP – Highway Safety Improvement Program

HSM – Highway Safety Manual

HSP – Highway Safety Plan

IDIQ – Indefinite Delivery/Indefinite Quantity

IHSDM – Interactive Highway Safety Design Model

ISTEA – Intermodal Surface Transportation Efficiency Act

ITS – Intelligent Transportation System

LOSS – Level of Service of Safety

MAIS – Maximum Abbreviated Injury Scale

MCMIS – Motor Carriers Management Information System

MCSAP – Motor Carrier Safety Assistance Program

MIRE – Model Inventory of Roadway Elements

MMUCC – Model Minimum Uniform Crash Criteria

MOE – Measure of Effectiveness

MPO – Metropolitan Planning Organization

MUTCD – Manual on Uniform Traffic Control Devices

MVMT – Million Vehicle Miles Traveled

NACE – National Association of County Engineers

NCHRP – National Cooperative Highway Research Program

NEMSIS – National Emergency Medical Services Information System

NEPA – National Environmental Policy Act

NHS – National Highway System

NHTSA – National Highway Traffic Safety Administration

NPV – Net Present Value

NPW – Net Present Worth

NSC – National Safety Council

OST – Office of the Secretary of Transportation

PDO – Property Damage Only
xvii

RHGCP – Railway-Highway Grade Crossing Program

RITA – Research and Innovative Technology Administration

RSA – Road Safety Audit

RSI – Relative Severity Index

RTM – Regression to the Mean

SAFETEA-LU – Safe, Accountable, Flexible, Efficient Transportation Equity Act: 

A Legacy for Users

SHSO – State Highway Safety Office

SHSP – Strategic Highway Safety Plan

SMS – Safety Management System

SPF – Safety Performance Function

SRTS – Safe Routes to School

STIP – Statewide Transportation Improvement Program

TEA-21 – Transportation Equity Act for the 21st Century

TEV – Total Entering Volume

TIP – Transportation Improvement Program

TRCC – Traffic Records Coordinating Committee

TTI – Texas Transportation Institute

U.S.C. – United States Code

VMT – Vehicle Miles Traveled

VSL – Value of Statistical Life

Highway Safety Improvement Program Manual 1-1

HSIP Foundations

1.0 HSIP Foundations

Unit 1 of the Highway Safety Improvement Program (HSIP) Manual lays the 

foundation for understanding road safety and HSIP. The unit explores the costs 

of motor vehicle crashes to our society and provides the building blocks for 

understanding road safety as a discipline. The background, history, purpose, 

and contents of the Highway Safety Improvement Program are described. The 

unit also introduces the HSIP legislative requirements and guidance documents, 

the HSIP’s relationship to other safety plans, and the relationship between the 

HSIP and the project development process within a department of transportation 

(DOT), including transportation planning, design, construction, maintenance, and 

operations.

1.1 HSIP Manual Purpose and Contents

The purpose of the HSIP Manual is to provide an overview of the HSIP and present 

state and local agencies with tools and resources to implement the HSIP. The 

manual provides information related to planning, implementation, and evaluation 

of state and local HSIPs and projects.

The manual’s first unit provides a foundation for understanding the HSIP. 

Basic concepts in road safety; the history of the HSIP and current legislation and 

guidelines; addressing road safety within all phases of the project development 

process; setting safety goals, objectives, and performance measures; and identifying available resources and technologies that support the HSIP process, provide 

the context to study the various components of the HSIP detailed in the remainder 

of the manual.

Figure 1.1 illustrates the various components of the HSIP process: planning, 

implementation and evaluation. The planning component consists of processes 

for problem identification, countermeasure identification, and project prioritization. Once projects are identified and funding secured, HSIP projects are designed 

and constructed as part of the implementation component. Finally, HSIP projects 

and programs are evaluated to determine the effectiveness of highway safety 

improvements.

While the HSIP is a Federally funded, state-administered program, the HSIP 

components shown in Figure 1.1 are applicable to road safety management 

processes at all levels of government.
1-2 Highway Safety Improvement Program Manual

HSIP Foundations

Figure 1.1 Highway Safety Improvement Program Components

Data/Design Standards Feedback

Evaluation 

Determine Effects of Highway Safety Improvements

Implementation

Schedule and Implement Projects

STIP

HSIP Project List

Project Prioritization

Countermeasure Identification

Problem Identification

HSIP

The remaining sections of the HSIP Manual address these components, as follows:

•	 Planning:

– Unit 2: Problem Identification – Examines the processes for collecting 

and managing crash and other data needed for identifying highway safety 

problems.

– Unit 3: Countermeasure Identification – Describes how to identify the 

factors or variables which contribute to crashes, and countermeasures for 

preventing those crashes and mitigating crash severity.

Planning
Highway Safety Improvement Program Manual 1-3

HSIP Foundations

– Unit 4: Project Prioritization – Addresses the application of project prioritization processes to identified locations with safety improvement 

potential. It also demonstrates how to calculate the benefit/cost ratio for 

projects using Crash Modification Factors (CMF) and other information.

•	 Implementation:

– Unit 5: Implementation – Addresses funding sources, allocation issues and 

solutions states have implemented to address funding challenges. Project 

programming and the development of evaluation plans is also discussed.

•	 Evaluation:

– Unit 6: Evaluation – Provides information for conducting project evaluations and developing CMFs. It addresses program evaluation and the 

importance of inputting evaluation results back into the HSIP and Strategic 

Highway Safety Plan (SHSP) planning processes to aid future decisionmaking.

The following section defines road safety and discusses the use of actual numbers 

versus rates to measure road safety. These basic concepts of road safety provide a 

foundation for the overall Highway Safety Improvement Program.

1.2 The Nature of Road Safety

Although the United States and other industrialized nations have made substantial progress over the past 30 years, the United States has experienced more than 

40,000 motor vehicle-related deaths, and more than two million injuries annually 

between 1993 and 2006. These deaths are the leading cause of unintentional injury 

deaths in the United States for ages 1 year through 34 years (CDC WISQARS web 

site). Motor vehicle crashes place millions of people at risk for death or injury, 

disproportionately strike the young, and are the leading cause of lost years of 

productive life.

In addition to the resulting injuries and lives lost, crashes also result in significant economic consequences. In 2000, the National Highway Traffic Safety 

Administration (NHTSA) estimated traffic crashes in the United States accounted 

for over $230 billion in economic losses (Blincoe et al., 2002).

Two intertwined issues that transportation officials must deal with are safety and 

congestion. For example, a heavily congested highway may present little risk of 

high-speed crashes; however, to avoid congestion drivers often seek alternative 

routes, such as local roads which present much higher risks to drivers. Likewise, 

poor incident management can often cause unnecessary delay and congestion 

on our roads. The 2008 AAA study, Crashes versus Congestion: What’s the Cost 

to Society? sheds light on the relationship between congestion and safety by 

examining the relative economic impact. It begins with the Urban Mobility Report 

published each year by the Texas Transportation Institute (TTI).
1-4 Highway Safety Improvement Program Manual

HSIP Foundations

The authors for AAA calculated the cost of crashes for the same urban areas included in the TTI report. The AAA study findings suggest congestion costs are 

not nearly as great as the costs and consequences of motor vehicle crashes.

Figure 1.2 shows in the urban areas studied the cost of fatal and injury traffic 

crashes is more than two and one-half times the cost of congestion – $164.2 billion for traffic crashes and $67.6 billion for congestion. The study concludes that 

improving safety may also improve congestion because, while it varies from 

community to community, 40 to 50 percent of all nonrecurring congestion may be 

associated with traffic incidents.

Figure 1.2 Per Person Cost of Crashes versus Congestion

0

200

400

600

800

1,000

1,200

1,400

1,600

Very Large Large Medium Small All Cities

962

523

376

1,063

276

1,204

1,359

189

430

1,051

Cost of Crashes Cost of Congestion

Source: Adapted from AAA, Crashes versus Congestion: What’s the Cost to Society?, 2008.

Both congestion and safety pose a substantial cost to the public, with safety estimated as over two and half times more than the cost associated with congestion. 

Designers and planners need to recognize these costs and define solutions that do 

not inadvertently adversely impact the other.

 Size of Metropolitan Area

Cost per Person (in 

Dollars)
Highway Safety Improvement Program Manual 1-5

HSIP Foundations

Defining Road Safety

Road safety is typically defined in terms of the injuries and fatalities that occur on 

the roadway system. Therefore, definitions of road safety are often based on crash 

outcomes such as “...the number of accidents (crashes),2 or accident consequences, 

by kind and severity, expected to occur on the entity during a specific period”

(Hauer, 1997).

The science of safety has evolved over the past several years and is focusing more 

on data and analysis, rather than solely adhering to standards. For example, it was 

commonly assumed when road safety improvements met the standards contained 

in the Manual of Uniform Traffic Control Devices (MUTCD) and the American 

Association of State Highway Transportation Officials (AASHTO) – A Policy on 

Geometric Design of Highway and Streets (also known as the “Green Book”) they 

were considered safe. However, most of those standards have not been evaluated 

specifically for their impact on safety. Crashes may occur on a roadway designed 

to meet standards, and this does not necessarily mean the roadway is unsafe.

Science-based road safety management is referred to as data-driven or evidencebased. This approach to road safety emphasizes estimates of the effect on safety 

(data and analysis), rather than adherence to standards based on personal experience, beliefs, and intuition. The safety metrics (e.g., fatalities and serious injuries) 

of a roadway are compared to roadways with similar characteristics to evaluate 

its safety performance. The goal of the evidence-based approach is to understand 

and quantify the expected consequences and outcomes of our actions (e.g., changes 

in the expected number of crashes/injuries/fatalities); the resulting calculations 

become the experience or evidence on which future decisions are made.

Measuring Road Safety

Road safety is usually measured in terms of fatalities and injuries involving motor 

vehicles and roadway users (i.e., pedestrians and bicycles) on the road system. 

Outcome measures should be used whenever possible to quantify safety. Some 

competing metrics for measuring safety, as well as the pros and cons of each are 

outlined below:

•	 Fatalities – Safety can be measured by tracking the number of fatalities on the 

roadway system. This number emphasizes lives lost, but does not address the 

loss in quality of life and medical costs associated with serious injuries. The 

definition of fatality can vary between states and/or the Federal government, 

from a death within 30 days of the crash to a death within one year of the 

crash. These discrepancies often result in variances of the number of reported 

fatalities. However, the fatal crash report dataset is almost always complete 

and often provides the greatest amount of crash detail.

2

 Many safety professionals and some in the media believe we should consistently use the term 

“crash” which implies these events are preventable as opposed to “accident” which implies the 

incidents are unintentional.
1-6 Highway Safety Improvement Program Manual

HSIP Foundations

•	 Fatalities and Serious Injuries – Safety can be measured by tracking the 

number of fatalities and serious or incapacitating injuries. This number is 

more comprehensive but is more difficult to measure because definitions of 

“serious injury” vary from state to state and even among crash investigators. 

The designation of what constitutes a “serious injury” is most likely made by a 

police officer who is not medically trained.

•	 Fatalities and All Injuries – This is a comprehensive measure but is difficult to 

track, since minor injuries are not always recorded by law enforcement.

•	 Crashes – The most inclusive measure encompasses all crashes, even those 

where no injury or fatality occurred (property damage-only crashes). This 

metric does not emphasize the human toll and is difficult to track, since crashes 

where no injury or fatality occurred may not be reported. Additionally, 

including property damage-only crashes may result in diverting scarce safety 

resources to areas where the safety problem is minimal compared to other sites.

The metrics listed above are not always adequate to measure changes in safety, 

since traffic crashes are relatively rare events, and changes in their numbers over 

time may be due to a wide range of factors, including statistical randomness. 

To address this issue, surrogates are sometimes used to measure safety. Some 

examples of surrogate measures include the following:

– Number of Near-Misses3 – Near-misses are conflicts which occur between 

road users but do not result in a crash. The frequency of near-misses is 

sometimes used as a rough proxy for safety. The advantage of this metric 

is it allows for analysis of a large number of events, since near-misses are 

much more frequent than crashes. On the other hand, collecting near-miss 

data is labor-intensive, and usually is collected only at select locations. 

Moreover, near-misses do not reflect fatality and injury outcomes.

– Evidence of Unreported Crashes – Many fixed object collisions with 

property damage only are not reported to the police. These crashes can 

be identified by physical evidence at the site (e.g., car parts in grass near 

curves, utility poles, trees, or median barriers; damaged sign posts, mailboxes, or fences) and through maintenance records. Repeat evidence of 

unreported crashes could be used to identify existing safety problems and 

sites for potential safety enhancement. Similar to near-misses, observation of 

3 Although these incidents are near-collisions, the incidents are commonly referred to as 

“near-misses.”
Highway Safety Improvement Program Manual 1-7

HSIP Foundations

vehicle debris associated with unreported crashes does not reflect fatality 

and injury outcomes.

– Safety Belts Use – This measure includes the percent of motor vehicle 

drivers and passengers wearing safety belts in general, by time of day, 

and/or for those involved in crashes. Safety belt use is highly correlated 

with the likelihood of surviving a crash, and is a general indicator of one 

important dimension of safety. However, it does not capture many other 

influences on safety such as engineering countermeasures, vehicle safety 

improvements, and so forth.

– Number of Driving Under the Influence (DUI) Arrests – Because 

impaired driving is a factor in many fatal crashes, the number of DUI 

arrests is sometimes used as an early indicator of safety, since a greater 

number of DUI arrests should result in fewer traffic crashes. However, this 

is an output measure and used primarily to track level of effort rather than 

safety outcomes.

Rates versus Numbers

Safety can be measured over time by tracking the raw number of fatalities, injuries, or crashes. It can also be measured by calculating injury, fatality, or crash 

rates, (e.g., fatalities per million miles of travel, per 100,000 population, per number of licensed drivers, etc.), which are normalized for exposure to crash risk. For 

example, crash rates can control for general increases in incidents at locations 

where people drive more often and travel more miles.

Important tradeoffs exist when selecting whether to use rates or numbers. Numbers have the advantage of conveying the magnitude of the crash problem, and the 

fact that every fatality or injury is important. Numbers also are better understood 

by the public.

Crash rates are better for identifying crash risk, but can be misleading. The 

assumption behind crash rates is that the number of collisions at a site is directly 

proportional to the amount of exposure. In other words, as vehicle, pedestrian, 

or bicycle volumes increase, the number of collisions increases proportionally. 

However, research has consistently shown the relationship between collisions and 

volumes to be nonlinear. As vehicle, pedestrian, or bicycle volumes increase, the 

number of crashes may increase, but in a nonlinear fashion.

Safety Performance Functions (SPFs) can be used to better portray the expected 

safety of a site. SPFs estimate the average crash frequency for a specific site type 

as a function of annual average daily traffic (AADT). SPFs are described in more 

detail in Unit 2.

An understanding of road safety builds the foundation for the HSIP. The background and history of the HSIP are summarized in the following section.
1-8 Highway Safety Improvement Program Manual

HSIP Foundations

1.3 Background and History of the HSIP

While safety has long been a consideration in transportation project development, the role and significance of safety in transportation policy has evolved over 

time. One of the first major efforts at the Federal level to reduce the number and 

severity of highway-related crashes was the 1966 Highway Safety Act (23 U.S. Code 

(U.S.C.) 402). Passed by Congress on September 9, 1966, the Act required states 

to develop and maintain a highway safety program in accordance with uniform 

standards established by the Secretary of Transportation. The primary purpose of 

this legislation was to provide for a coordinated national highway safety program 

through financial assistance to the states to accelerate highway traffic safety 

programs. The Act established 18 standards with responsibility for implementing 

these standards divided between the FHWA and the NHTSA. These standards 

were later replaced by priority program areas in the 1973 Act.

The Highway Safety Act of 1973 (Title II of Public Law No. 93‐87) established categorical funding for the following five safety improvement program areas:

1. Rail-highway grade crossing;

2. Pavement marking demonstration programs;

3. High-hazard locations;

4. Roadside obstacle elimination; and

5. Federal-aid safer roads demonstration.

These five programs were eventually consolidated by the Surface Transportation 

Assistance Act of 1978 (Public Law No. 95‐599) into the Railway-Highway Grade 

Crossing and Hazard Elimination Programs.

The Railway-Highway Grade Crossing Program was intended to reduce the 

number and severity of train collisions with vehicles and pedestrians at public 

highway-rail grade crossings and established Federal funding for projects aimed 

at improving rail-highway crossing safety. Typical projects eligible for this program include (but are not limited to):

•	 Installation or upgrade of new/additional signing and pavement markings at 

crossings;

•	 Installation or upgrade of active warning devices (i.e., lights and gates);

•	 Crossing surface improvements;

•	 Sight distance improvements;

•	 Geometric improvements to the roadway approaches;

•	 Grade separations; and

•	 Closing and/or consolidating crossings.
Highway Safety Improvement Program Manual 1-9

HSIP Foundations

The Hazard Elimination Program was intended to reduce the number and severity of fatalities and serious injuries resulting from crashes on all public roads and 

provide funding for projects to mitigate or eliminate hazardous sections, locations, 

or elements on any public road. Typical projects include, but are not limited to:

•	 Intersection improvements (channelization, traffic signal installation, sight 

distance increases);

•	 Pavement and shoulder widening;

•	 Guardrail and barrier improvements;

•	 Crash cushion installation;

•	 Roadway alignment modification;

•	 New/additional signing, pavement marking and delineation installation;

•	 Breakaway utility poles and sign posts installation;

•	 Pavement grooving and skid-resistant overlays;

•	 Shoulder rumble strip installation; and

•	 Minor structure replacements or modifications.

The evolution of highway safety continued with passage of the Intermodal Surface 

Transportation Efficiency Act (ISTEA) of 1991. ISTEA required states to develop 

and implement a series of management systems, including a safety management 

system (SMS). SMS was envisioned to be a systematic process designed to assist 

a broad-based coalition of safety stakeholders in selecting effective strategies to 

improve the efficiency and safety of the transportation system. A comprehensive 

crash database was to serve as the basis for these decisions, and safety performance measures were to be defined and used to monitor safety progress over 

time. SMS resulted in the improvement of crash databases in many states. Only 

a few states maintained or expanded their collaborative interagency efforts when 

the requirement was made optional in 1995.

In 1998, the Transportation Equity Act for the 21st Century (TEA‐21) provided more 

focus by including “safety and security” as a transportation planning priority. 

Prior to TEA‐21, safety may have been incorporated into the vision or goals of 

a state or metropolitan transportation planning organization (MPO) long-range 

transportation plan, but specific strategies to increase safety were seldom included 

in statewide and metropolitan planning processes or documents. More than two 

dozen states participated in safety conscious planning forums which, in most 

cases, started a dialogue between transportation planners and safety stakeholders.

TEA‐21 also provided guidance on a wide range of planning, policy and safety 

issues affecting bicycling and walking. Bicyclists and pedestrians were to be given 

due consideration in state and MPO long-range transportation plans. Bicycle and 

pedestrian projects were to be considered, where appropriate, in conjunction with 

all new construction and reconstruction of transportation facilities (except where 

bicycle and pedestrian use is not permitted). Additionally, transportation plans 
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HSIP Foundations

and projects were to provide consideration for safety and contiguous routes for 

bicyclists and pedestrians.

1.4 Current Legislation and Agency Guidelines

In 2005, the Safe, Accountable, Flexible, Efficient Transportation Equity Act – A Legacy 

for Users (SAFETEA‐LU) established the HSIP as a core Federal-aid program under 

23 U.S.C. 148. SAFETEA-LU nearly doubled the funds for infrastructure safety, 

allowed increased flexibility in program funding, and required a focus on results. 

In addition, SAFETEA‐LU elevated the highway safety program even further by 

separating safety and security into individual planning factors.

The specific purpose of the HSIP is to achieve a significant reduction in traffic 

fatalities and serious injuries on public roads. This is to be accomplished through 

the development and implementation of Strategic Highway Safety Plans (SHSP). 

SHSPs are intended to drive states’ HSIP investment decisions. In addition to the 

Railway-Highway Grade Crossing Program (23 U.S.C. 130), SAFETEA‐LU also 

established the High-Risk Rural Roads Program (HRRRP). Figure 1.3 diagrams 

the relationship among the various HSIP programs as presented in the Code of 

Federal Regulations, Title 23, Part 924 (23 CFR 924).

Figure 1.3 Relationships of HSIP Programs

Highway Safety Improvement Program

Railway-Highway Grade 

Crossing Program

State Strategic Highway 

Safety Plan

State Highway Safety 

Improvement Program 

Highway Safety 

Improvement Projects 

(Former Hazard 

Elimination Program)

High-Risk Rural 

Roads Program

Details on each of the programs, the relationship among them, and the new reporting requirements established under SAFETEA‐LU are provided below.
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Strategic Highway Safety Plans

23 U.S.C. 148 requires states to develop and implement a SHSP. The state SHSP is 

required to be:

•	 Data-driven, i.e., the use of crash and other data analyses on all public roads to 

identify safety issues;

•	 Developed in collaboration with a broad range of stakeholders, including 

Governors Representatives for Highway Safety (GR), MPOs, major transportation modes, state and local law enforcement, Operation Lifesaver, Motor 

Carrier Safety Assistance Program (MCSAP) personnel, Departments of Motor 

Vehicles (DMV), emergency response personnel, and others;

•	 Multidisciplinary addressing the 4Es of Safety – engineering, enforcement, 

education, and emergency medical services (EMS);

•	 Performance-based with the adoption of strategic and performance goals 

which focus resources on the areas of greatest need; and

•	 Coordinated with other state highway safety programs.

State Highway Safety Improvement Program

The state HSIP should be consistent with the SHSP emphasis areas and strategies. 

Requirements for an HSIP are defined in 23 CFR 924. While states may develop 

their HSIPs to best serve their needs, it must include the following components:

•	 Planning – Collect and maintain data, identify hazardous locations and elements, conduct engineering studies, and establish priorities;

•	 Implementation – Schedule and implement projects; and

•	 Evaluation – Determine the effectiveness of safety improvements.

The remainder of the HSIP Manual addresses the various processes associated 

with HSIP planning, implementation and evaluation efforts.

Relationship between the SHSP and HSIP

Figure 1.4 illustrates the relationship between the HSIP and the SHSP.

The SHSP influences decisions made during each step of the state HSIP process. 

SHSP emphasis areas influence problem identification in the HSIP. The SHSP action 

plans, which detail the strategies the state will implement to address its motor 

vehicle-related fatalities and injuries, link directly to the HSIP countermeasure 

identification process. Projects prioritized during HSIP planning align with the 

SHSP priorities and action plans. Many of the infrastructure-related elements of 

the SHSP can be implemented via the state’s HSIP. Evaluation of highway safety 

improvement projects informs tracking and updating of the SHSP. The results of 

HSIP evaluations feed back into both the SHSP and the HSIP planning processes.
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Figure 1.4 Relationships between the SHSP and HSIP

SHSP

Data/Analysis

Goals

Emphasis Areas

Implementation

Evaluation & Update

Data/

Design 

Standards Feedback

Evaluation 

Determine Effects of Highway Safety 

Improvements

Implementation

Schedule and Implement Projects

STIP

HSIP Project List

Project Prioritization

Countermeasure Identification

Problem Identification

Planning

HSIP

Strategies

Priorities & Action 

Plans

High-Risk Rural Roads Program

The High-Risk Rural Roads Program (HRRRP) provides set aside funds for construction and operational improvements on high-risk rural roads. High risk rural 

roads are defined as roadways with crash rates for fatalities and incapacitating 

injuries exceeding the statewide average on rural major or minor collectors, or 

rural local roads, or roadways likely to have increases in traffic volume which are 

likely to create a crash rate above the statewide average for the respective roadway 

functional classes. Implementation of the HRRRP requires comprehensive crash 

data for all public roads.
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Railway-Highway Grade Crossing Program

SAFETEA‐LU continued the Railway-Highway Grade Crossing Program 

(RHGCP) essentially intact, with the primary changes involving program 

funding. The program reduces the number of fatalities and injuries at public 

railway-highway grade crossings through the elimination of hazards and/or the 

installation/upgrade of protective devices at crossings. Each state is required 

to conduct and systematically maintain a survey of all highways to identify 

those railroad crossings which may require separation, relocation, or protective 

devices, and establish and implement a schedule of projects for this purpose. At 

a minimum, this schedule is to provide standard signing for all railway-highway 

crossings.

Reporting Requirements

State DOTs are required to submit reports to the FHWA on several elements of the 

HSIP. Reporting requirements include:

•	 Annual assessments of the progress and effectiveness of HSIP and HRRRP;

•	 Progress on implementing the RHGCP; and

•	 A Transparency Report (Five Percent Report) which includes a description of not 

less than five percent of locations exhibiting the most severe safety needs, an 

assessment of potential remedies for these locations, estimated costs associated 

with remedies, and impediments to implementation other than cost.

Reporting guidance for the HSIP, RHGCP and the 5% reports are provided on the 

FHWA Office of Safety web site. Direct links to the guidance documents can be found 

in the References appendix.

Other Federal Safety Programs

In addition to the funding in 23 U.S.C. 148, SAFETEA‐LU increased funds for 

highway safety grants (23 U.S.C. 402) and several other behavior-oriented grant 

programs through the NHTSA; established new programs, including traffic 

records systems improvements (23 U.S.C. 408) and Safe Routes to School; and 

continued to emphasize truck and transit safety through the Federal Motor Carrier 

Safety Administration (FMCSA) and the Federal Transit Administration (FTA), 

respectively.

1.5 Integrating Safety into the Project

Development Processes

States and local agencies are working to coordinate the various transportation 

and safety planning documents to ensure a systematic (collaborative) approach to 

addressing highway safety. Achieving this goal requires a fundamental change 

in the transportation culture which entails reaching out to other safety planning 
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entities and working with all phases of the transportation project development 

process, including planning, design, construction, operations, and maintenance. 

While this manual is focused on the HSIP, there are many ways to incorporate 

safety into an agency’s overall project development processes.

In a January 7, 2005 memorandum, the FHWA Associate Administrator for Safety 

said reaching the national safety goal requires safety consideration:

“... in every aspect of our business, from planning and programming, 

environmental analysis, project design, construction, to maintenance and 

operations. We must use data-driven decision-making and assure that 

safety is a key input in any decision made in the project development 

process.”

Safety in Planning

Figure 1.5 shows, in theory, how the various safety plans influence and affect 

each other. The diagram shows the relationship flowing from the Metropolitan 

Transportation Plans and the Statewide or Long-Range Transportation Plans to 

the Transportation Improvement Programs (TIP) at the metropolitan and state 

level. It also demonstrates how the individual safety plans such as the HSIP the 

Highway Safety Plan (HSP), the Commercial Vehicle Safety Plan (CVSP), and 

other plans and programs, such as freight and the pedestrian/bicycle plan, are 

interrelated. Coordinating all of these efforts is the Strategic Highway Safety 

Plan, out of which come the types of projects to be incorporated into the HSIP and 

statewide TIP (STIP). Likewise, these safety plans influence the strategies and 

action plans contained in the SHSP.

Figure 1.5 Coordinated Transportation Safety Planning

Metropolitan 

Transportation Plans

Statewide Transportation Plan 

(Long Range Plan)

State Strategic Highway 

Safety Plan (SHSP)

Statewide Transportation 

Improvement Program (STIP)

Commercial 

Vehicle Safety 

Plan (CVSP)

Other State 

Plans

(e.g. Freight 

Plan 

Ped/Bike 

Plan)

Highway Safety 

Plan (HSP)

Highway Safety 

Improvement 

Program (HSIP)

Aligning safety plans provides a more unified process which can reduce administrative burden, ensure common data and analysis methods, and align scarce 

resources to more effectively produce safety improvements.

TIP

(Metropolitan)
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Safety in Design

In addition to considering safety in identifying strategies and projects, safety 

should be considered in the preliminary design phase of all highway improvement projects as project options are being evaluated and environmental analysis 

is underway. Table 1.1 identifies potential safety tasks in the preliminary design 

process.

Table 1.1 Potential Safety Tasks in the Preliminary Design Process

Step Potential Safety-Related Task

Preliminary Design 

Conference

Document safety needs and identify atypical conditions, complex elements, and 

high-cost components.

Data Collection/

Preliminary Design 

Preparation

Diagnose safety data to identify crash patterns and refine project scope, if 

necessary.

Preliminary Schematic Perform preliminary level of safety analysis for “key” design elements.

Geometric Schematic Perform detailed level of safety analysis for “key” design elements.

Value Engineering Compare cost of specific elements and overall roadway with safety and 

operational benefits.

Geometric Schematic 

Approval

Document safety of design choices (use results for design exception request, if 

necessary).

Source: Adapted from Bonneson et al. 2005.

“Key” design elements are those associated with the 13 controlling criteria which 

dictate the need for a design exception or have a known impact on safety. The 13 

controlling criteria include: design speed, lane width, shoulder width, horizontal 

alignment, vertical alignment, grades, stopping sight distance, cross slope, superelevation, and horizontal clearance; and for bridges: lane and shoulder width, 

structural capacity, and vertical clearance.

The following recommendations are applicable to the design phase:

•	 Consider safety when design exceptions are being considered for any of the 

13 controlling criteria. Several low-cost safety countermeasures (additional 

information on low-cost safety improvements can be found in Unit 3) can be 

used to mitigate potential impacts of a design exception.

•	 Ensure safety is not compromised when considering Context-Sensitive 

Solutions. Low-cost safety enhancements should be considered and incorporated in those locations where design standards cannot be met.

•	 Use crash data to create a quantifiable basis for enhancing safety on all projects, 

especially when safety is identified in the Purpose and Need statement of an 

environmental document.
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•	 Emphasize safety when evaluating alternatives. Safety benefits should be 

quantified for each alternative during the alternatives selection process. 

Although right-of-way costs or other constraining factors may play a significant 

role in the project alternatives selection process, the safety benefits associated 

with each alternative should be considered in the overall evaluation. Texas 

Transportation Institute (Bonneson et al., 2005) developed the Interim Road 

Safety Design Workbook to assist engineers with evaluating potential safety 

tradeoffs associated with various design alternatives.

•	 Conduct Road Safety Audits (RSA) during the design phase of new and existing 

facilities, especially if crash data suggest a significant safety problem exists.

•	 Address safety at public outreach meetings to ensure the public understands 

safety issues in the context of overall needs. Since perceptions of safety may 

vary, quantifiable information should be used to differentiate the safety impacts 

of various alternatives to give the public a better understanding of the issue.

•	 Assure current analysis methods use crash and traffic data to demonstrate 

potential adverse safety impacts when considering operational performance 

and improvements, and ensure the action will not compromise safety.

For example, a state proposes a design exception for a horizontal curve because 

of excessive right-of-way costs. The safety solutions considered for the design 

exception include strategies to mitigate potential safety effects (e.g., raised 

pavement markers, high-performance pavement markings, paved shoulders, 

milled rumble strips, flattened fore slopes, larger and brighter warning signs and 

chevrons, and remediation of fixed objects) and/or adding high type skid resistance pavement overlay.

In addition, the Interactive Highway safety Design Model (IHSDM) is a suite of 

software analysis tools for evaluating safety and operational effects of geometric 

design decisions on highways. IHSDM evaluates existing and proposed alternative highway geometric designs and provides quantitative information on their 

expected safety and operational performance. Decision-makers can use the 

IHSDM quantitative information to help make, justify, and defend geometric 

design decisions throughout the highway design process.

Safety in Construction and Maintenance

Safety should be a key factor in any decision made during construction and 

maintenance. Agencies can use the following strategies to incorporate safety into 

the construction and maintenance phases:

•	 Incorporate low-cost safety improvements into resurfacing, restoration, or 

rehabilitation (also known as “3R”) projects;

•	 Conduct RSAs during the construction phase to examine temporary traffic 

management plans, changes in design during construction, or before a roadway is opened to traffic;
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HSIP Foundations

•	 Use contract options to allow for accelerated completion or full closure to 

improve safety;

•	 Use Intelligent Transportation System (ITS) technologies for work zones to 

improve safety;

•	 Ensure safety features remain operative and/or are upgraded during construction, utility, and maintenance activities;

•	 Train construction, maintenance, and utility personnel to understand safety 

concepts such as recovery areas and breakaway devices;

•	 Ensure construction, maintenance, and utility personnel do not make field 

changes which might adversely affect safety;

•	 Advise maintenance of the special importance of insuring proper drainage, 

snow and ice removal, signing and markings, and shoulder and pavement 

maintenance; and

•	 Implement timely application of preventive maintenance treatments to extend 

the service life of roadways and bridges, help maintain skid-resistant properties 

of pavements and bridges, and reduce motorist exposure to work zones.

One state DOT incorporates safety projects into its daily business through a policy 

to include low-cost safety improvements into all resurfacing projects using other 

highway funds.

Safety in Operations

Agencies are increasingly finding ways to incorporate safety into their traffic 

operations. To include safety in traffic operations an agency can:

•	 Use advanced traveler information systems to warn drivers of upstream 

hazards (e.g., obstruction in road, adverse weather conditions);

•	 Use dynamic or variable message signs to warn drivers of upstream hazards;

•	 Provide uniform traffic control (e.g., signage, signal phasing) to reduce driver 

confusion;

•	 Install variable speed limit signs to adjust based on traffic conditions;

•	 Provide emergency vehicle preemption at signalized intersections to improve 

response times;

•	 Implement a Speed Management Program;

•	 Coordinate signal timing and travel speeds; and

•	 Utilize emergency service patrols.

In some states, various state and local representatives collaborate regularly to 

keeps safety in focus as other activities progress. Networking opportunities raise 

visibility and awareness of safety issues, educate state and local employees about 
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HSIP Foundations

safety issues and programs, and provide reinforcement as to how their jobs are 

related to safety.

HSIP program managers and state safety engineers each play a critical role and 

must work together to integrate safety into the project development process. 

Transportation professionals may not be familiar with safety data location and 

availability; safety data analysis and forecasting techniques; organizational and 

collaboration structures; or safety stakeholders and networks. Safety engineers 

should communicate with transportation professionals to ensure they are aware 

of the expertise and experience available to them both within and outside their 

own agencies.

1.6 Safety Goals, Objectives, and Performance

Measures

Safety goals, objectives, and performance measures provide details on desired 

outcomes and measures of performance for HSIPs. Goals and objectives should 

be clear, concise, and quantifiable.

Goals

A goal is a general statement of a desired state or ideal function of a transportation system. Strategic Highway Safety Plans identify state transportation safety 

goals and provide a comprehensive framework for reducing highway fatalities 

and serious injuries on all public roads. The goals are generally based on number, 

proportion, or rate of crashes, fatalities, and/or serious injuries.

Examples of state safety goals include the following:

•	 Reduce the number of highway fatalities by 20 percent by 2015; and

•	 Reduce the fatal crash rate per 100 million vehicle miles traveled to 0.75 by 

December 31, 2014.

Objectives

An objective is a concrete step toward achieving a goal, stated in measurable terms. 

Objectives may have specific performance targets which set out in clear, numerical 

terms a desired or required degree of achievement. Examples of objectives include:

•	 Reduce serious (fatal/incapacitating injury) fixed-object crashes by 15 percent 

by 2010; and

•	 Reduce roadway departure-type crashes by 12 percent by 2015.

Clearly defining the goals and objectives is critical for identifying the different 

types of performance measures to incorporate into the planning process.
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Safety Performance Measures

Performance measures communicate the priorities, results, and value to society of 

various transportation safety programs and activities. Clearly defining goals and 

objectives is critical for identifying the different types of performance measures to 

incorporate into the planning process.

Performance measures are used for several different purposes. They are used 

to connect goals to actions, allocate resources, and to monitor and evaluate 

progress. Most importantly, performance measures determine the effectiveness 

of safety policies and countermeasures and how changes in the system may affect 

performance.

Output performance measures identify the progress in utilizing resources, such 

as the total number of projects, total funding, and related output measures (e.g., 

the number of traffic signals installed, the number of intersections with improved 

pavement markings, etc.). Outcome performance measures are focused on the 

intended results of the program. General statistics (e.g., the number of crashes 

and crash rates), trend analysis, and benefit/cost analysis are used to measure 

performance outcomes.

Safety performance measures should be:

•	 Important, valid, and ensure the quantity measured substantially impacts 

traffic safety;

•	 Sensitive to actual trends (a change in the measure will provide useful and 

meaningful traffic safety information);

•	 Measurable for many years;

•	 Accurate, reliable, and repeatable over time;

•	 Understandable and easily communicated to decision-makers and the public;

•	 Timely; and

•	 Cost reasonable for the value of information obtained.

When incorporating safety into system performance measures, a number of issues 

should be considered. Performance measures must be sensitive enough to assess 

changes in safety performance after strategies are implemented. Agencies also 

should be capable of collecting or accessing timely and accurate data relevant to 

the performance measures. Finally, the safety performance measures should be 

linked to evaluation criteria for assessing the relative benefits of one project or 

strategy over another.
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Following are examples of performance measures used for various safety 

improvements:

•	 The number of fatal or serious injuries resulting from a particular crash type;

•	 The number of fatal or serious injury crashes occurring on a particular facility 

type;

•	 The number of intersections with improved pavement markings;

•	 The number of intersections with enhanced signal head visibility;

•	 The number of rural intersections upgraded with sight distance improvements;

•	 The number of rural intersections upgraded with access improvements;

•	 The number of medians installed or upgraded;

•	 Miles of median cable barriers installed;

•	 Miles of rumble strips or stripes installed;

•	 Miles with new or upgraded installation of raised pavement markers (RPM) to 

improve nighttime visibility;

•	 The number of rural intersections with post mounted delineation signage 

upgrades; and The number of intersections with upgraded sign replacement.

The following example demonstrates how goals, objectives, and performance 

measures are used. A state selects a goal to reduce the number of motor vehicle 

fatalities by 20 percent by 2015. To reach this goal, one objective the state will 

aggressively pursue is to reduce fatal rural intersection crashes by 15 percent by 

2012. As a result, the state designs a five-year program to increase visibility of 

roadway signs, signals, and markings. To assess progress and evaluate success of 

the rural intersection program the performance measures will include:

•	 The number of fatal rural intersection crashes each year;

•	 The number of fatal nighttime rural intersection crashes each year;

•	 The number of angle collision fatalities at rural intersections each year;

•	 The number of barrier reflectors upgraded in the entire district system over 

five years;

•	 The number of sign post/drive post delineators installed to 100 percent of all 

applicable sign posts within one year;

•	 The number of dual stop and “stop ahead” signs installed in the entire district 

system within two years; and

•	 The number of flashing LED stop signs installed in the entire district system 

within two years.
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4 The HSM referenced herein refers to Draft 3.1 of the First Edition of the Highway Safety 

Manual (April 2009), as developed under NCHRP Project 17-36: Production of the First Edition 

of the Highway Safety Manual.

1.7 Resources and Technologies

As technology and safety research continue to advance, so will the available 

resources to support HSIP implementation. This section identifies the tools available to support the HSIP process.

Highway Safety Manual4

The Highway Safety Manual (HSM) provides practitioners with the best factual 

information and tools to facilitate roadway design and operational decisions 

based on explicit consideration of the safety consequences. The HSM serves as 

a resource for information related to the fundamentals of road safety, road safety 

management processes, predictive methods, and CMFs. The road safety management process outlined in the HSM aligns very closely with the HSIP process. 

Related to the HSIP, the HSM guides safety practitioners in several applications, 

including: identifying sites with potential for safety improvement, identification 

of contributing factors and potential countermeasures; economic appraisals and 

prioritization of projects; and evaluation of implemented improvements.

SafetyAnalyst

SafetyAnalyst provides a set of software tools used by state and local highway 

agencies for highway safety management. SafetyAnalyst incorporates state-of-theart safety management approaches into computerized analytical tools for guiding 

the decision-making process to identify safety improvement needs and develop a 

systemwide program of site-specific improvement projects. SafetyAnalyst includes 

modules for identifying locations for potential safety improvement, diagnosis 

and countermeasure selection, economic appraisal and priority ranking, and 

evaluation of implemented improvements.

1.8 Summary

Unit 1 serves as a foundation for the remainder of the HSIP manual. The cost of 

motor vehicle crashes to our society and the building blocks of road safety were 

discussed to provide a basic understanding of the transportation safety discipline. 

The relationship between the HSIP and other programs, and integrating safety 

into the planning, design, construction, operations, and maintenance processes, is 

critical to maximizing resources and the potential to impact motor vehicle crashes.

One challenge in reducing crashes and injuries is clearly understanding the crash 

problem(s). Unit 2 begins the HSIP planning process by addressing the importance 

of quality data, as well as data collection and problem identification processes.

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2-1

2.0 Planning: Problem 

Identification

Unit 2 addresses the problem identification step in the HSIP planning process. 

It begins by clarifying the difference between nominal safety (based on design 

standards) and substantive safety (based on roadway safety performance). 

Since the state HSIP is data driven, quality data and data collection processes 

are important aspects of the problem identification process. This unit identifies 

potential data challenges and methods for addressing them. It also outlines how 

to apply safety data in the network screening process to identify safety issues to 

address with systemic improvements or sites with potential for safety improvement. Several alternative methods are presented to identify locations or roadway 

segments with potential for safety improvement.

2.1 Nominal and Substantive Safety

Roadway safety can be characterized as nominal or substantive. Nominal safety 

is based on design standards, while substantive safety is based on roadway safety 

performance.

Nominal Safety

Nominal safety refers to whether or not a design (or design element) meets 

minimum design criteria based on national or state standards and guidance documents such as the AASHTO Green Book and the MUTCD. If a roadway meets 

minimum design criteria, it can be characterized as nominally safe. However, 

nominal safety does not characterize the actual or expected safety of a roadway.

Substantive Safety

Conversely, substantive safety refers to the actual or expected safety on a roadway. Substantive safety may be quantified in terms of:

•	 Crash frequency (number of crashes for a given road segment or intersection 

over a specified time period);

•	 Crash rate (normalized to account for exposure);

•	 Crash type; and/or

•	 Crash severity (i.e., fatality, injury, or property damage only).
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A roadway can be characterized by its safety performance relative to an expected 

value for the facility type; this could include regional, state, or national averages, 

or some other measurement. It is important to compare a road to similar roads 

because the expected safety performance of the road is strongly related to its 

context (e.g., traffic volume, location, design type, terrain, etc.). If the roadway 

in question has a significantly higher incidence or severity of crashes than other 

roads of its kind, it may have a substantive safety problem. Also, unusual crash 

patterns, such as more angle or nighttime crashes than on other facilities with 

similar characteristics, may indicate a problem, such as insufficient signage or 

lighting.

Relating Nominal and Substantive Safety

A direct correlation does not exist between nominal and substantive safety. A 

roadway may be characterized as nominally safe (meets minimum design criteria), while having higher than expected crash experience. Similarly a roadway not 

meeting minimum design criteria may still function at a high level of substantive 

safety.

Substantive safety requires an evidence-based approach to estimate the expected 

safety of a roadway through data and analysis rather than focusing solely on 

standards. This requirement creates a need for quality data and data systems.

Since the state HSIP is data-driven, quality data and data collection processes are 

important. The next section focuses on the data collection process and sources, 

data issues and challenges, and methods for overcoming those challenges.

2.2 Data Collection

Crash data systems are used by local, state, and Federal agencies as the basis of 

road safety and injury prevention programs. However, other data systems are 

important for managing road safety, including roadway, emergency medical 

services (EMS), hospital outcome, and enforcement data (e.g., citations, convictions, and sentencing outcomes). The data are used by transportation design, 

operations, and maintenance personnel as well as safety professionals in 

enforcement, education, emergency medical services, and public health communities to identify problem areas, select countermeasures, and monitor countermeasure impact.

This section outlines the data collection process as well as current and potential 

deficiencies in the data. It concludes with methods for addressing data challenges.

Data Collection and Management Methods

The path of crash data from the point of collection to analysis is complicated and 

varies from state to state and even within local governments. Crash data are 

originally collected either by state or local law enforcement officers in the field or 

are self-reported by vehicle owners.
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When crashes occur, state or local law enforcement is called to the scene. The 

officer completes a crash report (commonly referred to as police accident reports 

or PAR) documenting the specifics of the crash. The contents of the crash report 

are predetermined by the local or state government. The report documents 

information related to the location of the crash, vehicles involved, and drivers and 

passengers in the vehicles. (NHTSA maintains a catalog of state crash forms.)

While some states are collecting crash reports electronically, most data are entered 

into a state crash database manually or through a scanning process. Typically the 

state agency responsible for maintaining the crash database uses the crash report to 

identify and record the crash location. Reports with missing or unclear information 

are handled manually to determine if the information can be recovered. The time 

from which crash data are collected until they are available for analysis varies 

depending on the type of crash reporting system, and state and local government 

database capabilities. While some states are close to providing data with a very 

short turnaround (e.g., real time to a month); others may not have complete data 

available for up to two years.

The state crash database usually is maintained by the state DOT, state law 

enforcement agency or the Department of Motor Vehicles (DMV). Various programs and departments, such as local governments, metropolitan planning 

organizations (MPO), advocacy groups, and private consultants request state 

crash data to conduct various planning activities and analyze projects. The agency 

maintaining the database generally fills the requests by providing raw or filtered 

datasets.

Additional Data Sources

In addition to state-level crash data systems, agencies frequently use information 

from the following national databases: Fatality Analysis Reporting Systems 

(FARS), the Motor Carriers Management Information System (MCMIS), and in 

some states, the Crash Outcome Data Evaluation System (CODES).

Crashes involving fatalities are reported to NHTSA and further investigated for 

inclusion in FARS, which contains annual data on a census of fatal traffic crashes 

within the 50 states, the District of Columbia, and Puerto Rico. According to 

NHTSA, “...to be included in FARS, a crash must involve a motor vehicle traveling 

on a traffic way customarily open to the public, and must result in the death of an 

occupant of a vehicle or a nonmotorist within 30 days of the crash.” FARS data 

are available annually back to 1975. FARS contains more than 100 data elements 

related to the driver, vehicle, involved persons, and the crash itself. The FARS 

web site allows users to run national or state-specific reports on multiple factors 

related to trends, crashes, vehicles, people, and states. It also provides a query 

tool which allows users to download raw data for individual analysis. FARS is a 

widely used information source for research and program evaluation focusing on 

fatal crashes.
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NHTSA’s State Traffic Safety Information (STI) web site provides quick and easy 

access to state traffic facts, including: fatalities for years 2004-2008; by the various 

performance measures; by county; and economic impact of motor vehicle crashes. 

The STSI web site now has FARS-based GIS fatal traffic crash maps.

MCMIS is the U.S. DOT Federal Motor Carrier Safety Administration’s (FMCSA) 

central repository of data concerning the safety and operation of Interstate, and 

some intrastate, commercial motor vehicles on the nation’s highways. MCMIS 

data are the primary safety data used by FMCSA and state motor carrier safety 

staff in all safety-related efforts. State-based crash tables can be used to look at 

major factors associated with truck crashes, and comparisons can be made among 

states.

CODES links statewide crash and injury data that match vehicle, crash, and 

human behavior characteristics to their specific medical and financial outcomes. 

As a minimum, states must have computerized statewide crash, hospital, and 

either EMS or emergency department data that have sufficient information to 

discriminate among the crash events and persons involved in each event. Medical information is linked to crash and driver data through probabilistic linkage 

technology since direct linkage often is not possible due to missing personal 

information and privacy concerns.

Additional data sources for use in safety planning include:

•	 State Roadway Inventory Data Files;

•	 Aerial Photography;

•	 Asset Management Databases;

•	 Driver History Files;

•	 Vehicle Registration Databases;

•	 Traffic Volume Data;

•	 Highway Performance Monitoring System (HPMS);

•	 Maintenance Databases;

•	 Statewide Injury Surveillance Data;

•	 Crash Reports from Local Law Enforcement;

•	 Occupant Protection Use Surveys;

•	 Citation and DUI Tracking;

•	 Court Records;

•	 National Emergency Medical Services Information System (NEMSIS);

•	 National Driver Register;
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•	 General Estimates System; and

•	 Population Census.

Linking the crash data to these other data sources can supplement the crash 

database with additional information on the characteristics of the roadway, 

vehicle, driver experience, or medical consequences.

Data Quality Measures

Highway safety analysts need to be aware of several quality measures when 

working with data. These measures, commonly referenced as the “six pack,”

include timeliness, accuracy, completeness, uniformity, integration, and accessibility and can be used to identify data issues and deficiencies.

Timeliness

Timeliness is a measure of how quickly an event is available within a data system. 

Available technologies allow automated crash data collection and processing 

of police crash reports; however, many agencies rely on traditional methods of 

data collection (i.e., paper reports) and data entry (i.e., manual entry). The use of 

traditional data collection and entry methods can result in significant time lags. 

By the time data are entered in the data system, they may be unrepresentative 

of current conditions. If this is the case, project development is responding to 

historical crashes which may be out of date. Many states are moving closer to 

real-time data through the use of technology.

Accuracy

Accuracy is a measure of how reliable the data are, and if the data correctly 

represent an occurrence. Crash data are reported by various agencies within a 

state and various officers within an agency. Aside from inconsistencies due to 

multiple data collectors, some error in judgment is likely to occur. The description of the crash and contributing factors are based on the reporting officer’s 

judgment. Since the reporting officer typically does not witness the crash, the 

officer must rely on information gathered from the scene of the crash and those 

persons involved or nearby. Witness accounts may not be consistent (or available in the event of a serious injury or fatality) and vehicles or people may have 

been moved from the original location of the crash. In addition, without use of 

advanced technologies (e.g., global positioning systems (GPS), it is uncertain how 

the officer determines the location of the crash. All of these factors contribute to 

inaccuracies in the data.

Completeness

Completeness is a measure of missing information, including missing variables 

on the individual crash forms, as well as underreporting of crashes. Underreporting, particularly of noninjury crashes (i.e., property damage only (PDO) 

crashes) presents another drawback to current crash data. Each state has a specific 
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reporting threshold where fatal and injury crashes are required to be reported, but 

PDO crashes are reported only if the crash results in a certain amount of damage 

(e.g., $1,000) or if a vehicle is towed from the scene. Underreporting PDO crashes 

hinders the ability to measure the effectiveness of safety countermeasures (e.g., 

safety belts, helmets, and red light cameras) or change in severity.

Uniformity

Uniformity is a measure of how consistent information is coded in the data system, and/or how well it meets accepted data standards. Numerous agencies 

within each state are responsible for crash data collection, some of which are not 

the primary users of the crash data. In some states, little consistency exists in 

how the data are collected among agencies. Lack of consistency includes both 

the number and types of variables collected and coded by each agency as well as 

the definitions used to define crash types and severity. Data collection managers 

should continually work with their partners in other state and local agencies to 

improve data uniformity. This may require some negotiation but, in some cases, 

training may prove to be the only solution needed.

Integration

Data integration is a measure of how well various systems are connected or linked. 

Currently, each state maintains its own crash database to which the local agencies 

submit their crash reports. However, crash data alone do not typically provide 

sufficient information on the characteristics of the roadway, vehicle, driver 

experience, or medical consequences. If crash data are linked to other information 

databases such as roadway inventory, driver licensing, vehicle registration, 

citation/conviction, EMS, emergency department, death certificate, census, 

and other state data, it becomes possible to evaluate the relationship among the 

roadway, vehicle, and human factors at the time of the crash. Linkage to medical 

information helps establish the outcome of the crash. Finally, integrating the 

databases promotes collaboration among the different agencies, which can lead to 

improvements in the data collection process.

Accessibility

Accessibility is a measure of how easy it is to retrieve and manipulate data in 

a system, in particular by those entities that are not the data system owner. 

Safety data collection is a complex process requiring collaboration with a range 

of agencies, organizations, modes of transportation, and disciplines. Successful 

integration of safety throughout the transportation project development process 

(planning, design, construction, operations, and maintenance) and meaningful 

implementation of safety improvements demand complete, accurate, and timely 

data be made available to localities, MPOs, and other safety partners for analysis.
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Liability

Liability associated with data collection and data analysis is an issue which is 

often a concern of practitioners. 23 U.S.C. 409 in its entirety states “Notwithstanding any other provision of law, reports, surveys, schedules, lists, or data 

compiled or collected for the purpose of identifying, evaluating, or planning the 

safety enhancement of potential accident sites, hazardous roadway conditions, 

or rail-way-highway crossings, pursuant to sections 130, 144, and 148 [152] 

of 23 U.S.C. or for the purpose of developing any highway safety construction 

improvement project which may be implemented utilizing Federal-aid highway 

funds shall not be subject to discovery or admitted into evidence in a Federal or 

state court proceeding or considered for other purposes in any action for damages 

arising from any occurrence at a location mentioned or addressed in such reports, 

surveys, schedules, lists, or data.”

In 2003, the U.S. Supreme Court upheld the Constitutionality of 23 U.S.C. 409, 

indicating it “protects all reports, surveys, schedules, lists, or data actually compiled or collected for Section 152 purposes” (Pierce County, Washington v. Guillen). 

Some states consider information covered by 23 U.S.C. 409 as an exemption to its 

public disclosure laws.

States have developed procedures for managing the risk of liability. For 

example, many states have developed some form of a release agreement which 

is required to obtain data. NCHRP Research Results Digest 306: Identification of 

Liability-Related Impediments to Sharing Section 409 Safety Data among Transportation 

Agencies and Synthesis of Best Practices documents multiple examples of risk 

management practices states have incorporated to reduce the risk of liability.

Overcoming Data Challenges

Congress’ greater focus on safety has given rise to institutional and technical crash 

data collection and management innovations.

Funding and Institutional Support

Improving the timeliness, accuracy, completeness, uniformity, integration, and 

accessibility of data requires adequate funding and institutional support. Funding 

mechanisms may require the support of several agencies. Program managers 

should market improved safety data to other agencies to demonstrate the benefits 

of greater accessibility to reliable safety data. Asset management, maintenance, 

planning, emergency management, and legal departments may need access to 

safety data, and these groups may be able to provide resources.

SAFETEA‐LU authorized funding through the 23 U.S.C. 408 State Traffic Safety 

Information System Improvement Grants. 23 U.S.C. 408 is a data improvement 

incentive program administered by NHTSA and the state highway safety offices. 

The 23 U.S.C. 408 grant program encourages states to improve the timeliness, 

accuracy, completeness, uniformity, integration, and accessibility of their state 
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safety information; link their data systems; and improve the compatibility of state 

and national data. To receive 23 U.S.C. 408 grant funds, states must establish a 

Traffic Records Coordinating Committee (TRCC), participate in a traffic records 

assessment at least once every five years, develop a strategic data improvement 

plan, and certify it has adopted and uses the model data elements contained in the 

Model Minimum Uniform Crash Criteria (MMUCC) and the National Emergency 

Medical Services Information Systems (NEMSIS) or will use 23 U.S.C. 408 grant 

funds to adopt and use the maximum number of model data elements.

NHTSA encourages states to establish a two-tiered TRCC: an executive TRCC with 

policy and funding authority and a working-level TRCC to implement the tasks 

associated with the strategic data improvement plan. The TRCC plays a key role 

in identifying the appropriate data improvement methods based on an agency’s 

available resources. The TRCC is a source for identifying actions to improve the 

data system.

States can take advantage of a NHTSA’s Traffic Records Assessment process 

(State Assessments) where a team of national highway safety data experts 

reviews all components of a state traffic safety data program and compares it to 

NHTSA guidelines. The team provides the state with a report detailing the status of the state’s traffic records program, identified deficiencies in the system, and 

recommendations for program improvements. States can use the report to develop 

a plan of action and identify traffic records improvement projects that correspond 

to their needs.

Guidance on the State Traffic Safety Information Systems Improvement grants 

may be obtained on-line. Detailed information on all projects contained in the 

strategic data improvement plans submitted by the states and U.S. territories for 

23 U.S.C. 408 grants to help fund the improvement of their safety data systems 

can be found within NHTSA’s Traffic Records Improvement Program Reporting 

System (TRIPRS). The web site is intended to provide a clearinghouse for information on traffic safety data system improvement efforts and may provide useful 

information for agencies desiring to improve their traffic data systems.

To aid states with data deficiencies, additional funding sources for traffic safety 

data initiatives beyond the 408 grants have been identified by the Federal TRCC.

The goal of the Federal TRCC is to “ensure that complete, accurate, and timely 

traffic safety data are collected, analyzed, and made available for decision-making 

at the national, state, and local levels to reduce crashes, deaths, and injuries on 

our nation’s highway.” The Federal TRCC includes members from OST, NHTSA, 

FHWA, FMCSA, and the Research and Innovative Technology Administration

(RITA).

Uniform Data Elements

Uniform coding and definition of data elements allows states to compare their 

crash problems to other states, regions, and the nation; Interstate information 
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exchange; and multiyear data analysis to detect trends, and identify emerging 

problems and effective highway safety programs.

States are incorporating MMUCC into the data review process. It is a voluntary set 

of guidelines developed by a team of safety experts to promote consistency in crash 

data collection. It describes a minimum, standardized dataset for describing motor 

vehicle crashes which generate the information necessary to improve highway 

safety. MMUCC helps states collect consistent, reliable crash data effective for 

identifying traffic safety problems, establishing goals and performance measures, 

and monitoring the progress of programs.

A national effort currently is underway to standardize the data collected by EMS 

agencies through the NEMSIS, which is the national repository used to store 

EMS data from all states. Since the 1970s, the need for EMS information systems 

and databases has been well established, and many statewide data systems have 

been created. However, these EMS systems vary in their ability to collect patient 

and systems data and allow analysis at a local, state, and national level. For this 

reason, the NEMSIS project was developed to help states collect more standardized elements and eventually submit the data to a national EMS database.

Roadway inventory and traffic data are essential for the next generation of safety 

analysis tools. The Model Inventory of Roadway Elements (MIRE) is being developed to define the critical inventory and traffic data elements needed by agencies to 

meet current safety data analysis needs as well as the data needs related to the next 

generation of safety analysis tools.

Technology and Training

Any agency wanting to improve the accuracy and reliability of its crash data should 

consider implementing strategies that offer training, funding, collaboration, and 

policy revisions to support electronic data collection, transfer, and management.

Data collection technologies offer improvements in the collection process and 

range from electronic crash report systems to barcode or magnetic strip technologies used to collect vehicle and license data. NCHRP Synthesis 367 Technologies for 

Improving Safety Data provides a comprehensive summary of crash data collection 

innovations.

The National Model for the Statewide Application of Data Collection and Management 

Technology to Improve Highway Safety has been developed for states who have not 

yet implemented a statewide electronic data collection system. As an outgrowth 

of Iowa’s TraCS integrated system, the model demonstrates how new technologies and techniques can be cost-effectively used in a statewide operational environment to improve the safety data collection and management processes. The 

model provides tools by which information is quickly, accurately, and efficiently 

collected, and is subsequently used for analysis, reporting, public and private 

dissemination, and data-driven decision-making.

Many states provide frequent training to law enforcement as a means to improve 

the accuracy and integrity of crash data, which is most vulnerable at the crash site. 
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Law enforcement officers benefit from training on the importance of the crash data 

and techniques to ensure accurate data collection. Alternatively, the importance of 

crash data collection and issues can be provided through a series of short roll-call 

videos. When new equipment is provided, such as GPS devices, training should 

be provided on proper use.

The review and processing of crash reports provides opportunities for errors and 

inaccuracies. Training crash report system administrators to properly handle 

reports with inaccurate or missing information can result in more accurate data. 

Proper protocols should be developed to address crash reports that need additional investigation. In addition, some agencies are beginning to explore the possibility of using insurance data as often the companies have a larger database of 

crashes.

An incentive program could encourage agencies to collect and submit their data 

in a timely fashion to a central repository. The program might provide funding 

to a department or agency to improve an existing data collection platform so 

additional data can be collected with a minimal increase in expenses. In some 

cases, incentives may appear to be unrelated to crash data improvement (e.g., 

radars, DUI training, etc.); however, if law enforcement is willing to participate in 

the program and it accomplishes the desired objectives, it may be considered an 

appropriate technique.

The state TRCC provides leadership for addressing traffic safety data issues 

through coordination between agencies and stakeholders. The TRCC provides 

a forum for review and endorsement of programs, policy recommendations, 

funding, projects, and methodologies to implement improvements for the traffic 

safety data or systems.

Data for Local Roads

Often crash data are not available for local (nonstate-owned and operated) roads. 

Even when crash data are available, some road safety issues cannot be identified 

using crash data due to low exposure. In rural areas, potential safety improvement locations may not be identified through the data analysis process because 

low-traffic volumes lead to low-crash frequencies. For these specific situations, 

local engineers, police officers, and maintenance staff may be aware of high-risk 

locations not revealed by data analysis. Physical evidence at the site and maintenance records could be used to identify existing safety problems and sites for 

potential safety enhancement. System users may report problem locations to the 

local engineer and public officials can identify locations based on citizen complaints. Road safety audits can be used to identify and correct the issues identified by these special circumstances. While it may take more effort to collect data 
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from the aforementioned sources, methods exist to address lack of complete data. 

Although the data may not achieve the preferred “data-driven” level of analysis, 

waiting for “state” data may not be necessary to identify safety problems on local 

roads.

Data Collection Considerations

Data sharing and collaboration will become easier as more agencies adopt standard data elements and practices. It may be necessary to change policies and 

procedures to promote more accurate and timely safety data collection. Specific 

activities that states should consider for improving their data system include 

developing several elements:

•	 Policies to make it easier to collect, manage, and use data. With so many 

agencies involved in the process, a standard set of procedures can provide a 

clear expectation of each agency’s roles and responsibilities.

•	 A data standards manual to identify data streams, data definitions, and the 

agencies responsible for data collection and management.

•	 Data submission protocols for all agencies providing data to the management 

system.

•	 A schedule for data dissemination that includes a standard procedure for 

handling data requests.

Quality data and data collection support the network screening element of the 

HSIP problem identification process. These data are used by agencies to identify 

sites with potential for safety improvement. Basic data analysis concepts are 

summarized in the next section to prepare agencies for this phase of the problem 

identification process.

2.3 Data Analysis Concepts

The network screening process requires basic knowledge of key concepts associated 

with safety data analysis. Key concepts range from the analysis period and defining 

a site, to more advanced statistical concepts such as regression to the mean, safety 

performance functions, and Empirical Bayes theory.

Analysis Period

Crashes are random events that naturally fluctuate over time at any given site. 

Figure 2.1 illustrates how over a span of several years crash data fluctuates between 

several high and low points around an expected average crash frequency. If you 

consider a short-term average crash frequency, it may be significantly higher or 

lower than the long-term average crash frequency. The crash fluctuation over time 

can make it difficult to determine whether changes in observed crash frequency 

are due to changes in site conditions or natural fluctuations.
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Figure 2.1 Variations in Crash Frequency

Short-Term Average Crash Frequency 

Year

Short-Term Average Crash Frequency

Expected Average

Crash Frequency

Observed Crash Frequency

Regardless of the problem identification method used to identify locations or road 

segments with potential for improvement, an appropriate time period needs to 

be defined for the analysis. As discussed, crash experience can vary at a location 

from year to year, so it is important that more than one year of data is used for the 

analysis.

Typically a minimum of three years of crash data is used for analysis. Multiple years 

of data are preferable to avoid the regression to the mean phenomenon. However, 

the use of multiple years of data can be misguided because the facility itself may 

have changed (e.g., adding a lane), the travel volume may have increased, or some 

other change has taken place that skews the analysis. In addition, it is sometimes 

difficult to obtain adequate multiple years of data; therefore, it is often necessary 

to use a method for enhancing the estimate for sites with few years of data. The 

problem can be addressed by supplementing the estimation for a site with the 

mean (and standard deviation) for comparable sites using safety performance 

functions and empirical bayes.

Regression to the Mean

When identifying potential safety issues, the analyst must be aware of the statistical phenomenon of regression to the mean (RTM). RTM describes a situation in 

which crash rates are artificially high during the before period and would have 

been reduced even without an improvement to the site. Programs focused on 
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high-hazard locations, such as the HSIP, are vulnerable to the RTM bias which is 

perhaps the most important cause of erroneous conclusions in highway-related 

evaluations. This threat is greatest when sites are chosen because of their extreme 

value (e.g., high number of crashes or crash rate) in a given time period.

When selecting high-hazard locations; the locations chosen are often those with 

the worst recent crash record. It is generally true that crash frequency or rate at 

a given location, all things remaining equal, will vary from year to year around 

a fairly consistent mean value. The mean value represents a measure of safety at 

the location. The variations are usually due to the normal randomness of crash 

occurrence. Because of random variation, the extreme cases chosen in one period 

are very likely to experience lower crash frequencies in the next period, and vice 

versa. Simply stated; the highest get lower and the lowest get higher.

The specific concern in road safety is that one should not select sites for treatment if 

there is a high count in only one year because the count will tend to “regress” back 

toward the mean in subsequent years. Put more directly, what happens “before”

is not a good indicator of what might happen “after” in this situation.

Figure 2.2 shows an example to demonstrate this concept. It shows the history 

of crashes at an intersection, which might have been identified as a high-hazard 

location in 2003 based upon the rise in crashes in 2002.

Figure 2.2 Data Series for Example Intersection

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

0

5

10

15

20

25

30

35

40

45

Frequency Average

Year

Number of Crashes
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Even though a treatment may have been introduced early in 2003, any difference 

between the frequencies of crashes in 2002 and those in 2003 and 2004 (see 

Figure 2.3 would, to some unknown degree, not be attributed to the treatment, 

but to the RTM phenomenon. The RTM phenomenon may cause the perceived 

effectiveness of a treatment to be overestimated. Thus, there would be a “threat to 

validity” of any conclusions drawn from a simple comparison of conditions before 

and after a change at a site.

Figure 2.3 Example of Regression to the Mean

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

0

5

10

15

20

25

30

35

40

45

Frequency Average

Year

Before After

Before and After Years

Number of Crashes

In fact, if a decision is made to forgo safety improvements at the site (e.g., due to 

lack of funds), the site would still be likely to show a reduction in crashes due to 

the natural variation in crash frequency. However, one would not be inclined to 

conclude doing nothing is beneficial where a safety problem truly exists.

Safety Performance Functions

Safety performance functions (SPFs) are frequently used in the network screening 

and evaluation processes and can be used to reduce the effects of RTM. They can 

be used to estimate the expected safety of a roadway segment or location based on 

similar facilities.

SPFs represent the change in mean crash frequency as ADT (or other exposure 

measure) increases or decreases. The sites contained in an SPF are called comparable sites, because they are sites that are generally comparable to the site of interest.
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SPFs are constructed using crash and exposure data from multiple comparable 

sites. SPFs are constructed by plotting the crash and exposure data and then fitting a curve through the data using a negative binomial regression formula. The 

resulting curve (or equation) is the SPF.

Numerous studies have been conducted to estimate SPFs for different types 

of facilities. These SPFs have been compiled into safety analysis tools, such as 

SafetyAnalyst and the Highway Safety Manual (HSM). However, since crash patterns may vary in different geographical areas, SPFs must be calibrated to reflect 

local conditions (e.g., driver population, climate, crash reporting thresholds, etc.). 

Different entities have SPFs with different curves and use differing measures to 

represent exposure (e.g., annual average daily traffic, total entering vehicles, etc.).

Figure 2.4 depicts a typical SPF and shows crashes per mile per year for three 

data points (using triangles, squares, and diamonds as icons). The small icons 

represent values for individual years while the large comparable icon represents 

the mean for several years. Only three “sites” are shown in the figure, but a typical SPF may have from 100 to thousands of sites involved in its estimation. One of 

the advantages of displaying data in this way is to show sites that exceed the mean 

crash frequency for comparable sites at the same level of exposure (AADT in this 

case). One can think about sites with mean risk above the SPF as those with higher 

than average risk and those below the line as those with lower than average risk.

Figure 2.4 SPF with Individual Site Data

AADT

Expected Crash Frequency per Mile per Year
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Note that the large triangle and large square lie above the SPF indicating mean 

expected crash frequency in excess of the average for comparable sites. The large 

diamond lies directly on the SPF so for this site the expected crash frequency is 

virtually the same as the comparable sites.

Empirical Bayes

The Empirical Bayes (EB) method is a statistical method that combines the observed 

crash frequency with the predicted crash frequency using the SPF to calculate the 

expected crash frequency for a site of interest. The EB method pulls the crash 

count towards the mean, accounting for the RTM bias.

The EB method is illustrated in Figure 2.5, which illustrates how the observed 

crash frequency is combined with the predicted crash frequency based on the SPF. 

The EB method is applied to calculate an expected crash frequency or corrected 

value, which lies somewhere between the observed value and the predicted value 

from the SPF. The EB method is discussed in more detail in Section 6.1.

Figure 2.5 Empirical Bayes Method

AADT

Crash Frequency

Predicted Number from SPF

SPF

Observed Number

Expected Number Using EB
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Defining a Site

Sites identified for safety improvements are either 

intersections or segments of roads; however, there is 

no clear definition of what length of a road segment 

should be considered as a site. Typically roadways 

are sectioned off into segments of a fixed length, 

which varies from agency to agency. The segment 

length used to identify potential sites for safety 

improvement is left to the agency’s discretion and does not need to be consistent 

for the entire data set, as long as the analysis accounts for segment length. Many 

states are now implementing systemic improvements, which identify sites based 

on roadway characteristics, rather than individual sites.

2.4 Network Screening Process

Network screening is conducted to identify key crash types to address with systemic 

improvements or to identify specific sites with potential for safety improvement. 

The process will vary depending on whether the network screening is being 

conducted to identify systemic improvements or to identify sites with potential 

for improvement.

Identifying Safety Issues to Address with Systemic Safety 

Improvements

Analysis now focuses more on road segments, corridors, and even entire networks. 

Analysts look beyond a particular location and concentrate on surrounding road 

segments for more efficient and effective countermeasure implementation. Some 

states are implementing systemic improvements using countermeasures known 

to be effective.

A systemic highway safety improvement is a particular countermeasure, or set 

of countermeasures, implemented on all roadways or roadway sections where a 

crash type is linked with a particular roadway or traffic element. Locations for 

implementing improvements are NOT based on the number or rate of crashes at 

particular locations, but on an analysis of what roadways share the “dangerous”

elements that may be mitigated by the improvement.

The process for identifying potential safety issues to address with systemic 

improvements should build on the analysis used to develop the emphasis areas in 

the state Strategic Highway Safety Plan (SHSP). The actual identification process 

may vary among states but typically involves the following three steps:

1. First, identify key crash types to address (e.g., run-off-road, median crossover), which is similar to selecting emphasis areas in the SHSP. Typically the 

key crash types are selected based on the number and severity of crashes.

Caution: A small

denominator (very short 

section length or little traffic) 

can lead to extremely high 

rates even if the actual crash 

frequency is low.
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2. Next, identify characteristics of the facilities on 

which key crash types occur (e.g., rural versus 

urban, two-lane versus four-lane, divided 

versus undivided, on curve versus on tangent, 

type of intersection control, etc.).

3. Finally, set thresholds that further define the 

“high-risk” facilities on which to implement 

the countermeasures (e.g., AADT greater than 

20,000 vehicles per day, horizontal curves 

greater than 7 degrees, median widths less than 

50 feet, etc.).

As an example, through data analysis one state has identified a significant number of severe run-off-the-road crashes occurring on their rural two-lane roadways 

with horizontal curves. After further looking into the analysis, they discovered 

most of these crashes were occurring on horizontal curves greater than seven 

degrees. Based on their findings, they decided to look into proven effective 

countermeasures on horizontal curves and to implement them on all two-lane 

rural roadways with horizontal curves greater than seven degrees.

States should use the SHSP to guide or influence systemic improvements in their 

HSIP project selection process. The emphasis areas identified in the SHSP can 

help states identify systemic improvements to include in the HSIP project selection process and, in some cases, address safety problems before they occur.

Once the key crash types and key characteristics are identified, the next step is to 

identify the appropriate countermeasure(s) for systemic improvements. This step 

will be discussed in Unit 3.

Identifying Sites with Potential for Safety Improvement

The network screening process for identifying sites with potential to benefit from 

a safety improvement involves a comprehensive review of a selected roadway 

network to identify locations with a potential safety problem. This process is 

typically conducted in four steps:

1. Identify and group the network elements;

2. Select problem identification methodology;

3. Select screening method; and

4. Screen and evaluate results.

The remainder of this section provides more detail on each of the four steps in the 

site identification process.

Identify and Group the Network Elements

The first step is to identify the network elements to be screened and group them 

into reference populations. Elements that might be considered for the screening 

process include: intersections, segments, facilities, ramps, ramp terminals, or 

As an example, a state that 

has identified run-off-theroad crashes as an emphasis 

area in their SHSP, Should 

consider incorporating 

a systemic improvement 

project in their HSIP to 

address this crash type.
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at‐grade crossings which are then grouped by reference population or sites with 

similar characteristics.

By establishing a reference population, the performance at a particular site is 

compared to the expected safety of the reference population, yielding a relative 

measure of comparison for determining sites with potential for improvement. 

Reference populations can be established based on several characteristics.

Intersections potentially may be grouped into reference populations based on:

•	 Traffic control (signalized, two-way or all-way stop control, yield control, 

roundabout);

•	 Number of approaches (three-leg, four-leg intersection);

•	 Cross-section (number of through and turning lanes);

•	 Functional classification (arterial, collector, local);

•	 Area type (urban, suburban, rural);

•	 Traffic volumes (million entering vehicles (MEV), peak hour volumes, or 

average daily traffic; including pedestrian, bicycle, trucks, bus volumes);

•	 Terrain (flat, rolling, or mountainous); and

•	 Turning movements.

Similarly, roadway segments may be grouped into reference populations based 

on:

•	 Area type (urban, suburban, rural);

•	 Number of lanes per direction;

•	 Functional classification (arterial, collector, local);

•	 Area type (urban, suburban, rural);

•	 Access density (driveway or intersection spacing);

•	 Traffic volumes (peak hour traffic, average annual daily traffic (AADT); 

including pedestrian, bicycle, trucks, bus volumes);

•	 Median type and/or width of median;

•	 Operating or posted speed; and

•	 Terrain (flat, rolling, or mountainous).

Intersections and roadways may be grouped based on multiple reference populations, which will depend on the available data. For example, intersections might 

be grouped as urban signalized intersections of two arterials or urban signalized 

intersections of an arterial with a collector roadway. Once the network elements 

have been grouped by reference populations, problem identification methods are 

selected to use in the evaluation.
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Select Problem Identification Methodology

Selecting a problem identification methodology to use for the analysis of the 

network elements is the second step in the network screening process. The evaluation can be based on one or multiple problem identification methods. The use 

of multiple problem identification methods may provide more certainty in the 

evaluation, if the same sites are ranked among the top sites with multiple methods.

Several problem identification methodologies can be used to identify sites for 

safety improvements, and the specific problem identification method used varies 

from agency to agency. Agencies should use problem identification methods in 

the network screening process that suit their specific purpose and available data.

The following are the 13 problem identification methods5 identified in the Highway 

Safety Manual (HSM); however, states are using additional methods not included 

in the HSM:

1. Average Crash Frequency – Sites are ranked based on the total number of 

crashes or by a particular crash severity or type during a given time period. 

The site with the highest number of crashes is ranked first.

2. Crash Rate – The crash rate normalizes the crash frequency based on exposure.

3. Equivalent Property Damage Only (EPDO) Average Crash Frequency – Each 

crash is weighted based on the crash severity and the equivalent property 

damage only crash cost.

4. Relative Severity Index – Average monetary crash costs are assigned to each 

crash at a site, and the total average crash cost for a site is compared to the 

average crash cost for the reference population.

5. Critical Crash Rate – A critical crash rate or threshold value is calculated for 

each site and compared to the observed crash rate. Sites with an observed 

crash rate greater than their critical crash rate are flagged for further investigation.

6. Excess Predicted Average Crash Frequency Using Method of Moments – 

With this method, the observed crash frequency for a site is adjusted based 

on the variance in the crash data and the average crash counts for a site’s reference population, which is then compared to the average frequency of crashes 

for the reference population.

7. Level of Service of Safety (LOSS) – This method compares the observed 

crash frequency and/or severity to the mean value predicted for the reference population using a SPF. The difference between the two values yields a 

performance measure that ranges between LOSS I and LOSS IV, with LOSS I 

indicating a low potential for crash reduction and LOSS IV indicating a high 

potential for crash reduction.

5 Referred to as performance measures in the HSM.
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8. Excess Predicted Average Crash Frequency Using SPFs – This method 

represents the difference between the observed crash frequency for the site 

and the predicted crash frequency based on the SPF with information specific 

to the site.

9. Probability of Specific Crash Types Exceeding Threshold Proportion – This 

method is based on the probability that the long-term proportion of a specific 

crash type exceeds a threshold proportion for the site’s reference population.

10. Excess Proportion of Specific Crash Types – This is the difference between 

the observed proportion of a specific crash type for a site and the threshold 

proportion for the reference population.

11. Expected Average Crash Frequency with EB Adjustment – The expected 

crash frequency is calculated using a calibrated SPF, which is then weighted 

with the observed crash frequency using the EB method. The EB method 

accounts for regression to the mean bias and is discussed in detail in Unit 6.

12. EPDO Average Crash Frequency with EB Adjustment – This method combines the expected crash frequency method with EB adjustments and the 

EPDO crash frequency method. The expected crash frequency is calculated 

using a calibrated SPF and weighted with the observed crash frequency using 

EB, which is then weighted based on crash severity and the equivalent property damage only cost.

13. Excess Expected Average Crash Frequency with EB Adjustment – The 

expected crash frequency determined from a SPF is weighted with the observed 

crash frequency using the EB method. The resulting weighted crash frequency 

is then compared to the expected crash frequency using the SPF to determine 

the difference between the two values.

Each of these problem identification methodologies has different data needs, 

strengths, and weaknesses. Table 2.1 summarizes the data needs, strengths, and 

weaknesses of the 13 problem identification methods.

Once the problem identification method(s) has been chosen for the evaluation, the 

next step is to select the screening method.
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Table 2.1 Summary of Problem Identification Methodologies

Problem Identification Method Data Inputs and Needs Strengths Weaknesses

Average Crash Frequency •	 Crashes by type and/or severity and 

location.

•	 Simple; and

•	 May be applied to crashes by 

type and severity.

•	 Does not account for RTM bias;

•	 Does not account for exposure;

•	 May overlook low-volume sites and 

overemphasize high-volume sites; and

•	 Does not identify a performance 

threshold.

Crash Rate •	 Crash counts and location; and

•	 Average Daily Traffic Volumes 

(ADT), Total Entering Volume (TEV), 

or Annual Average 

Daily Traffic Volumes (AADT).

•	 Simple; and

•	 Can modify to account for 

severity if EPDO or RSI-based 

crash count is used.

•	 Does not account for RTM bias;

•	 Does not identify a performance 

threshold;

•	 May overemphasize sites with low 

volumes; and

•	 Comparisons cannot be made across 

sites with significantly different volumes.

Equivalent Property Damage 

Only (EPDO) Average Crash 

Frequency

•	 Crashes by severity and location; 

and

•	 Fatal, injury, and PDO crash 

weighting factors.

•	 Simple; and

•	 Considers crash severity.

•	 Does not account for RTM bias;

•	 May overemphasize locations with a 

small number of severe crashes;

•	 Does not identify a performance 

threshold; and

•	 Does not account for traffic volume.

Relative Severity Index (RSI) •	 Crashes by type and location; and

•	 Crash costs by type.

•	 Simple; and

•	 Considers crash type and crash 

severity.

•	 Does not account for RTM bias;

•	 May overemphasize locations with small 

number of severe crashes; and

•	 Does not account for traffic volumes.

Critical Crash Rate •	 Crash counts and location; and

•	 Annual Average Daily Traffic Volumes 

(AADT).

•	 Reduces exaggerated effect of 

sites with low volumes;

•	 Considers variance in crash data;

•	 Establishes a threshold for 

comparison; and

•	 Can be applied to specific crash 

type or severity.

•	 Does not account for RTM bias.

Excess Predicted Average 

Crash Frequency Using Method 

of Moments

•	 Crashes by type and location; and

•	 Traffic volume (AADT or ADT).

•	 Establishes a threshold of 

expected performance for a site;

•	 Considers variance in crash 

data; and

•	 Allows sites of all types to be 

ranked in one list.

•	 Does not account for RTM bias;

•	 Does not account for traffic volumes; and

•	 Ranking results are influenced by 

reference populations.
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Problem Identification Method Data Inputs and Needs Strengths Weaknesses

Level of Service of Safety •	 A minimum of three years crash data;

•	 Crashes by location; and

•	 SPF, overdispersion parameter, and 

all variable required for SPF.

•	 Considers variance in crash data;

•	 Accounts for volume; and

•	 Establishes a threshold for 

comparison.

•	 Effects of RTM bias may still be present.

Excess Predicted Average 

Crash Frequency Using SPFs

•	 A minimum of three years crash data;

•	 Crashes by type, severity, and 

location; and

•	 Calibrated SPF.

•	 Accounts for volume; and

•	 Establishes a threshold for 

comparison.

•	 Requires calibrated SPF; and

•	 Effects of RTM may still be present in the 

results.

Probability of Specific Crash 

Types Exceeding Threshold 

Proportion

•	 Crashes by type, severity, and 

location.

•	 Also can be used as a diagnostic 

tool;

•	 Not affected by RTM bias; and

•	 Considers variance in crash data.

•	 Does not account for traffic volumes; and

•	 Some sites may be identified for unusually 

low numbers of nontarget crash types.

Excess Proportion of Specific 

Crash Types

•	 Crashes by type, severity, and 

location.

•	 Also can be used as a diagnostic 

tool;

•	 Not affected by RTM bias; and

•	 Considers variance in crash data.

•	 Does not account for traffic volumes; and

•	 Some sites may be identified for unusually 

low numbers of nontarget crash types.

Expected Average Crash 

Frequency with EB Adjustment

•	 A minimum of three years crash data;

•	 Crashes by type, severity, and 

location; and

•	 Calibrated SPFs and overdispersion 

parameters.

•	 Accounts for RTM. •	 Requires locally calibrated SPF;

•	 Requires rigorous analysis; and

•	 Data intensive.

EPDO Average Crash 

Frequency with EB Adjustment

•	 A minimum of three years crash data;

•	 Crashes by type, severity, and 

location;

•	 Calibrated SPFs and overdispersion 

parameter; and

•	 Fatal, injury, and PDO crash weighting 

factors.

•	 Accounts for RTM; and

•	 Considers crash severity.

•	 May overemphasize locations with a small 

number of severe crashes depending on 

weighting factors used.

•	 Requires rigorous analysis; and

•	 Data intensive.

Excess Expected Average Crash 

Frequency with EB Adjustment

•	 A minimum of three years crash data;

•	 Crashes by type, severity, and 

location; and

•	 Calibrated SPF and overdispersion 

parameter.

•	 Accounts for RTM; and

•	 Establishes a threshold for 

comparison.

•	 Requires locally calibrated SPF;

•	 Requires rigorous analysis; and

•	 Data intensive.

Source: Highway Safety Manual, First Edition, Draft 3.1, April 2009.
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Select Screening Method

Three screening methods can be used in the third step of the network screening 

process, including simple ranking, sliding window, or peak searching. The 

method chosen is dependent on the reference population and the selected problem 

identification methodology. Table 2.2 provides a summary of when each method 

is applicable.

Table 2.2 Screening Method Applications

Problem Identification Method

Segments Nodes Facilities

Simple 

Ranking

Sliding 

Window

Peak 

Searching

Simple 

Ranking

Simple 

Ranking

Average Crash Frequency Yes Yes No Yes Yes

Crash Rate Yes Yes No Yes Yes

Equivalent Property Damage Only 

(EPDO) Average Crash Frequency Yes Yes No Yes Yes

Relative Severity Index (RSI) Yes Yes No Yes No

Critical Crash Rate Yes Yes No Yes Yes

Excess Predicted Average Crash 

Frequency Using Method of Moments Yes Yes No Yes No

Level of Service of Safety Yes Yes No Yes No

Excess Predicted Average Crash 

Frequency Using SPFs Yes Yes No Yes No

Probability of Specific Crash Types 

Exceeding Threshold Proportion Yes Yes No Yes No

Excess Proportion of Specific 

Crash Types Yes Yes No Yes No

Expected Average Crash Frequency with 

EB Adjustment Yes Yes Yes Yes No

EPDO Average Crash Frequency with 

EB Adjustment Yes Yes Yes Yes No

Excess Expected Average Crash 

Frequency with EB Adjustment Yes Yes Yes Yes No

Source: Highway Safety Manual, First Edition, Draft 3.1, April 2009.

Simple Ranking

As the name suggests, simple ranking is the simplest of the three screening methods 

and may be applicable for roadway segments, nodes (intersections, at‐grade rail 

crossings), or facilities. The sites are ranked based on the highest potential for 

safety improvement or the greatest value of the selected problem identification 

methodology. Sites with the highest calculated value are identified for further 

study.

The sliding window and peak-searching methods are only applicable for segmentbased screening. Segment-based screening identifies locations within a roadway 
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segment that show the most potential for safety improvement on a study road 

segment, not including intersections.

Sliding Window

With the sliding window method, the value of the problem identification methodology selected is calculated for a specified segment length (e.g., 0.3 miles), and 

the segment is moved by a specified incremental distance (e.g., 0.1 miles) and 

calculated for the next segment across the entire segment. The window that 

demonstrates the most potential for safety improvement out of the entire roadway 

segment is identified based on the maximum value. When the window approaches 

a roadway segment boundary in the sliding window method, the segment length 

remains the same and the incremental distance is adjusted. If the study roadway 

segment is less than the specified segment length, the window length equals the 

entire segment length.

Peak Searching

Similar to the sliding window method, the peak-searching method subdivides the 

individual roadway segments into windows of similar length; however, the peaksearching method is slightly more meticulous. The roadway is first subdivided 

into 0.1-mile windows; with the exception of the last window which may overlap 

with the previous window. The windows should not overlap. The problem 

identification method is applied to each window and the resulting value is subject 

to a desired level of precision, which is based on the coefficient of variation of the 

value calculated using the problem identification method. If none of the 0.1-mile 

segments meet the desired level of precision, the segment window is increased 

to 0.2 miles, and the process is repeated until a desired precision is reached or 

the window equals the entire segment length. For example, if the desired level 

of precision is 0.2, and the calculated coefficient of variation for each segment is 

greater than 0.2, then none of the segments meet the screening criterion, and the 

segment length should be increased.

Screen and Evaluate Results

Finally, the selected problem identification method(s) and screening method(s) 

are applied to the study network. The result will be a list of sites identified with 

potential for safety improvement with the sites most likely to benefit at the top 

of the list. These sites should be studied further to determine the most effective 

countermeasures (discussed in Unit 3).

As mentioned previously, applying multiple problem identification methods 

to the same data set can improve the certainty of the site identification process. 

Sites listed at the top of the list based on multiple problem identification methods 

should be investigated further. To provide a better understanding of the network 

screening process, two example applications are provided.
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Network Screening Applications for Identifying Sites

This section provides two example applications of the network screening process 

for identifying sites with potential for safety improvement using the EPDO average crash frequency and the excess predicted average crash frequency using SPFs. 

The EPDO average crash frequency is included because it is a method currently 

used by many states in their screening process, and the excess predicted average 

crash frequency using SPFs was included because more states are starting to utilize 

SPFs in their screening process. The HSM will provide greater detail and several 

examples of all the problem identification and screening methods.

For the sample applications, it is assumed that the network elements have been 

identified and grouped into reference populations. All numbers used in the following examples are fictitious and provided for illustrative purposes only. We 

begin with an explanation of how to apply the EPDO crash frequency to screen and 

evaluate the network.

Equivalent Property Damage Only (EPDO) Average Crash Frequency

The EPDO average crash frequency identifies sites 

with potential for safety improvement for all reference populations. This method weights the frequency of crashes by severity to develop a score 

for each site. The weighting factors are calculated 

based on the crash cost by severity relative to the 

cost of a property damage only crash. The crash 

costs should include both direct (e.g., EMS, property damage, insurance, etc.) and 

indirect (e.g., pain and suffering, loss of life). This method provides a ranking of 

sites based on the severity of the crashes.

1. The first step is to calculate the weighting factors for fatal, injury, and PDO crash 

severities using local data (if local data sources are not available, references 

have been provided in Section 4.3). In some cases, fatal and injury crashes may 

be combined to avoid overemphasizing fatal crashes. The weighting factors 

are calculated as follows:

2. The weighting factors are applied to the sites based on the most severe injury 

for each crash to develop a score:

A limitation of the EPDO 

average crash frequency method 

is that it does not provide a 

threshold for comparing the 

crash experience with expected 

crash experience at similar sites.
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Where:

KF,i = crash frequency of fatal crashes on segment i;

KI,i = crash frequency of injury crashes on segment i; and

KPDO,i = crash frequency of PDO crashes on segment i.

3. The sites are then ranked from highest to lowest.

Example

The following is a short example applying the EPDO average crash frequency to a 

roadway segment using the sliding window method. The study roadway already 

is divided into segments of equal length. The average crash costs and segment 

crash information is as follows:

•	 Average fatal crash cost = $6,800,000;

•	 Average injury crash cost = $390,000; and

•	 Average PDO crash cost = $12,000.

Crash Count

Segment Fatal Injury PDO

1a 0 22 8

1b 1 8 3

1c 0 16 5

1d 1 14 2

1e 0 19 6

1f 0 20 3

1. The first step is to calculate the weighting factors based on the given crash cost:

2. Now the weighting factors are applied to each segment. For Segment 1a:

$12,000

$12,000

32.5

32
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The scores for the remaining segments are shown below.

Fatal Injury PDO

EPDO 

Segment Score

Crash 

Count

Weighted 

Value

Crash 

Count

Weighted 

Value

Crash 

Count

Weighted 

Value

Total 

Crashes

1a 0 0 22 715 8 8 723 30

1b 1 567 8 260 3 3 830 12

1c 0 0 16 520 5 5 525 21

1d 1 567 14 455 2 2 1,024 17

1e 0 0 19 618 6 6 624 25

1f 0 0 20 650 3 3 653 23

3. For this study roadway, Segment 1d is ranked first.

Alternatively, a weighted average of the fatal and injury crashes could be used 

so that sites with fatal injuries are not overemphasized in the analysis. If these 

crashes are weighted using the injury factor only, Segment 1a is ranked first as 

shown below.

Segment

Fatal and Injury PDO

EPDO 

Score

Total 

Crashes

Crash

Count

Weighted 

Value

Crash 

Count

Weighted 

Value

1a 22 715 8 8 723 30

1b 9 293 3 3 296 12

1c 16 520 5 5 525 21

1d 15 488 2 2 490 17

1e 19 618 6 6 624 25

1f 20 650 3 3 653 23

It should be noted this method does not account for RTM or provide a threshold 

for comparing the crash experience with expected crash experience at similar sites.

Excess Predicted Average Crash Frequency Using SPFs

The excess predicted average crash frequency using SPFs is another problem 

identification method that can be used in the network screening process to compare a site’s observed crash frequency to the predicted crash frequency from a 

SPF. The difference between the two values is the excess predicted average crash 

frequency. It is once again assumed the focus has been established as identifying 

sites with potential for safety improvement and the network has been identified 

and grouped into reference populations. In addition, it is assumed the appropriate calibrated SPFs have been obtained (SPFs can be obtained from the HSM and 

other research documents, but they should be calibrated to local conditions).
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1. The first step is to tabulate the crashes by type, severity, and total each site for 

each reference population being screened:

a. The crash counts are summarized as crashes per year at nodes; and

b. The crashes are tabulated on a per mile per year basis for segments, either 

for the entire site or for the window of interest.

2. Use the appropriate SPF to calculate the estimated number of crashes (Ny), for 

each year (y), for the analysis period (y = 1, 2, ..., Y). For segments, the crashes 

should be expressed on a per mile basis (calculated for the entire site or the 

window of interest). The number of estimated crashes for each year should 

then be summed together and divided by the number of years to summarize 

the crashes by year (or crashes per mile per year for segments).

3. The next step is to calculate the excess average crash frequency (Excess(K)) 

based on all the years of data:

Where:

Avg(Ki) = Average observed crash frequency for site (or window); and

Avg(N) = Average estimated crash frequency from SPF for site (or window).

4. The final step is to rank all of the sites in each reference population based on 

excess predicted average crash frequency.

Example

A numerical example is provided below using the excess predicted average crash 

frequency using SPFs as a problem identification method. The given reference 

population is signalized four-legged intersections with the following three years of 

AADT and crash data.

Year 1 Year 2 Year 3

AADT

Total 

Observed 

Crashes

AADT

Total 

Observed 

Crashes

AADT

Total 

Observed 

Intersection Crashes

Major

Street

Minor

Street

Major

Street

Minor

Street

Major

Street

Minor

Street

A 25,000 10,000 8 25,400 11,000 6 26,000 11,200 10

B 30,600 12,000 9 31,100 12,100 12 31,800 12,500 11

C 28,800 13,000 10 30,000 13,500 9 30,500 13,800 8

D 27,600 11,500 11 28,100 11,800 13 28,600 12,200 12
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The calibrated SPF for signalized four-legged intersections in the area is:

NTOT=e-3.47(AADTmaj)0.42(AADTmin)0.14

Where:

NTOT = The SPF predicted number of total crashes;

AADTmaj = Average annual daily traffic on major roadway; and

AADTmin = Average annual daily traffic on minor roadway.

1. The first step is to total the crashes at each intersection during the study period 

and divide by the number of years. For intersection A:

» Observed crashes per year = (8 + 6 + 10) crashes/3 years = 8 crashes 

per year.

2. The SPF is used to calculate the estimated number of crashes for each year at 

each site. The estimated crashes for each year at a site are then added together 

and divided by the number of years. For intersection A:

Year 1:

NTOT=e-3.47(AADTmaj)0.42(AADTmin)0.14 = e-3.47(25,000)0.42(10,000)0.14 = 7.95

Year 2:

NTOT=e-3.47(25,400)0.42(11,000)0.14 = 8.11

Year 3:

NTOT=e-3.47(26,000)0.42(11,200)0.14 = 8.21

Estimated crashes per year = (7.95 + 8.11 + 8.21) crashes/3 years = 8.09 crashes 

per year.

3. The excess is then calculated for each intersection. For intersection A:

Excess(K)=Avg(Ki) - Avg(N) = 8.00 - 8.09 = -0.09

The first three steps are repeated for the remainder of the reference population, 

which is summarized in the following table.
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Year 1 Year 2 Year 3 Three-Year Total

Intersection

Observed 

Crashes

Predicted 

Crashes 

with SPF

Observed 

Crashes

Predicted 

Crashes 

with SPF

Observed 

Crashes

Predicted 

Crashes 

with SPF

Observed 

Crashes

Predicted 

Crashes 

with SPF

Observed 

Crashes 

per Year

Predicted 

Crashes 

per Year

Excess Crash 

Frequency

A 8 7.95 6 8.11 10 8.21 24 24.26 8.00 8.09 -0.09

B 9 8.87 12 8.94 11 9.07 32 26.89 10.67 8.96 1.70

C 10 8.75 9 8.95 8 9.04 27 26.73 9.00 8.91 0.09

D 11 8.45 13 8.54 12 8.64 236 25.63 12.00 8.54 3.46

4. Finally the sites are ranked based on their excess predicted average crash 

frequency.

Intersection Excess Crash Frequency

D 3.46

B 1.70

C 0.09

A -0.09

Sites with an excess crash frequency greater than zero experience more crashes 

than expected, while sites with a value less than zero experience fewer crashes 

than expected. Based on this method, intersection D has the greatest potential for 

safety improvement.

This section described the network screening process and many problem identification methodologies for use in identifying sites with potential for safety 

improvement, including example applications. The HSM and SafetyAnalyst are 

tools that can assist the safety practitioner in identifying sites with improvement 

potential.

2.5 Summary

In this unit, we discussed the importance of quality data in safety planning and 

outlined resources and methods for improving data. In addition, we addressed 

the network screening process for identifying potential safety issues to address 

with systemic improvements and for sites with potential for safety improvements. Once the system problems or sites with potential for safety improvement 

have been identified, the next step is identifying contributing crash factors and 

countermeasures for addressing the problem – the focus of Unit 3.

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3.0 Planning: Countermeasure 

Identification

Identifying high-risk corridors, road segments, locations, etc., is a critical part 

of the road safety improvement analysis process; however, the analysis task 

is not complete until contributing crash factors are identified and appropriate, 

effective countermeasures are selected and prioritized. The purpose of Unit 3 is 

to describe how to identify the factors or variables that contribute to crashes and 

countermeasures for preventing crashes and mitigating crash severity.

A common practice is to identify contributing crash factors through a post hoc 

analysis of all events, behaviors, and conditions preceding a crash to determine 

which specific events, behaviors, or conditions made the crash inevitable. Another 

approach is to search a crash database to determine if certain factors, variables or 

sites are more prevalent in the crash data than in the normal driving population or 

in other locations. An emerging approach is “naturalistic” studies where drivers 

and vehicles are monitored continuously to obtain objective information of the 

conditions preceding a crash.

For practical purposes, the analysis is typically conducted through an engineering study which may be supplemented by a road safety audit (RSA). Engineering studies review recent crash data and existing roadway/intersection 

characteristics (i.e., geometry, control, sight distance, travel speeds, lane widths, 

etc.) to characterize crash data specific to the location of interest. The studies are 

designed to accomplish four essential steps: 1) examine the crash data to develop 

an in‐depth analysis of the contributing crash factors; 2) conduct a field review; 

3) identify alternative solutions or countermeasures; and 4) assess the effectiveness 

of individual and groups of countermeasures. The unit describes these steps in 

more detail and concludes with a case study to demonstrate an application of the 

engineering study process.

3.1 Step 1 – Analyze the Data

A careful examination of the crash data will reveal contributing factors and patterns at sites and segments. The review may examine individual crash reports or 

an aggregate of all the data. It should result in:

•	 A list of crashes by crash type;

•	 A list of contributing crash factors;

•	 Crash pattern descriptions; and

•	 Collision diagrams.
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Crash Type

After the unit of analysis (e.g., hot spot, road segment, corridor, etc.) has been 

identified, the data are further examined to determine the types of crashes occurring at those locations. In some cases, a single crash type might be identified, such 

as rear-end collisions at specific intersections. Other types of crash types include 

side-swipe, run-off-road, head-on, right-angle, left-turn, etc.

Figure 3.1 demonstrates an example of crash types for an intersection collision 

study. It is obvious turning maneuvers and rear end crashes are important issues 

which need to be addressed at this particular intersection.

Just as identifying the high-risk 

locations does not complete the 

picture, focusing on solely the 

crash type may also be misleading. 

For example, a large number of 

rear-end crashes may be due to 

misleading signage or short sight 

distance, but it also could be related 

to driver behavior. Drivers may be 

distracted by a mixture of signs, 

billboards, etc., outside the vehicle 

or multitasking inside the vehicle 

(e.g., talking on cell phones, eating 

and drinking, etc.). Also, drivers 

may not be giving a clear signal 

of their intent, such as when they 

approach a light and then slam on 

the brakes at the last second.

Contributing Crash Factors

Crash factors may be related to roadway geometrics, condition, etc.; human factors, such as driver/pedestrian/motorcyclist behavior; vehicle factors which 

contribute to crash avoidance and survivability; and environmental conditions 

such as snow, ice, rain, and wind. Figure 3.2 illustrates an overall analysis of 

crash factors. While these percentages may not hold true for any specific situation; 

they generally show human factors are a significant component in all crashes, but 

other factors, such as roadway factors, are related as well. Engineers examine all 

crash factors to determine how human behavior and attributes can be affected by 

signage, roadway design, etc., to reduce crash risk.

Figure 3.1 Crash Types at an Intersection

Rear End 

33

32%

Approach Turn 

54

52%

Broadside

9

 9%

Sideswipe 

6

6% Fixed Object 

1

1%
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The Road Environment Factors in Figure3.2 

represent the surrounding environment, 

which includes both roadway factors and 

environmental factors.

The HSIP Manual focuses on addressing 

issues associated with roadway factors, 

but the others are important for 

developing a thorough understanding of 

the circumstances surrounding a crash.

Roadway Factors

The HSIP is focused primarily on roadway 

factors which may contribute to help 

avoid or mitigate the severity of crashes. However, other factors may interact 

with roadway factors. Figure 3.2 shows this interaction effect. For example, 

24 percent of crashes involve factors associated with both the roadway and road 

user behavior.

Roadway factors generally are grouped by the type of facility, including (but not 

limited to) interstates, freeways, intersections, rural highways, local roads, pedestrian facilities, and bicycle facilities. Safety on different facilities varies because 

they are built to different standards and different types of activities occur on them. 

Often simply knowing the type of facility provides an important safety indicator. 

For example, intersections may involve a large number of conflicting vehicle 

movements, which increases the opportunity for incidents to occur.

Some of the roadway factors which may impact the safety of a particular facility 

include:

•	 Access Control – Facility types are commonly classified based on the number 

of access points. Improving the access control reduces the number of potential 

conflict points.

•	 Speed – While, interstates and freeways have fewer conflict points because 

of controlled access, these facilities are associated with higher travel speeds, 

which may result in more severe injuries.

•	 Roadway Cross-Section – Roadways are designed to a minimum standard 

based on the facility type. The lane width, shoulder width, roadside clearance, 

cross-slopes, etc., may all impact the safety of a facility. For example, rural 

roads may be characterized by a lack of shoulders and unforgiving roadside 

environments.

•	 Traffic Volumes – One factor contributing to crashes on any road is the amount 

of exposure to risk for a given time period. Exposure relative to traffic volumes 

generally results in more crashes but they may be less severe due to slower 

speeds associated with congestion.

Figure 3.2 Crash Factors

4% 24%

4% 4%

Vehicle Factors (8%)

Human Factors 

(95%)

67%

Source: NSW Roads and Traffic Authority, 1996.

Road Environment 

Factors (28%)
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•	 Pavement Condition – Pavement resurfacing can improve skid resistance 

in locations where a high percentage of crashes occur on wet pavements or 

curves in the roadway. This action also may improve safety by eliminating 

ruts, potholes, and bumps which contribute to crashes.

Human Factors

As Figure 3.2 shows, most crashes involve one or more human factors. A host of 

behavioral factors are known to contribute to crashes. Some factors are attributes 

of drivers themselves, while others are related to the behavior of drivers. For 

example, advancing age is an unavoidable driver attribute, while driver intoxication is a behavioral choice. Some of the human factors that contribute to crashes 

include:

•	 Age – Older and younger drivers typically fall into higher crash risk groups. 

Older drivers frequently suffer from reduced reaction and perception times, 

reduced vision and flexibility (e.g., neck and back flexibility), and increasing 

fragility. Younger drivers lack experience and may be immature. This combination leads to excessive risk-taking and poor judgment.

•	 Gender – Men are more likely than women to be involved in fatal crashes, but 

women experience significant numbers of serious crashes as well and often for 

different reasons. In comparable crashes, some studies have shown women 

are more likely to be injured.

•	 Aggressive Driving – Various manifestations of aggressive driving include 

behaviors such as driving too fast for conditions, following too closely, inappropriate weaving in and out of traffic, and passing under unsafe conditions.

•	 Impaired Driving – Driving while intoxicated, under the influence of drugs 

(illegal, over-the-counter, and prescription), or fatigued are known to contribute to crashes.

•	 Occupant Protection – Drivers and passengers who choose not to use safety 

restraints and motorcyclists who choose not to use protective gear are at higher 

risk for injury and death.

•	 Driver Inattention – Distracted drivers do not give sufficient attention to the 

driving task. Distractions include factors both inside and outside the vehicle. 

Drivers may be distracted by billboards, other cars, people, noises, etc., outside the vehicle. Inside the vehicle, drivers are likely to multitask, e.g., talking 

or text messaging on cell phones, conversing with passengers, eating meals 

or snacks, changing the radio station or CD, shaving or putting on make-up, 

reading maps, etc.

Vehicle Factors

Vehicle design is a significant factor in road safety. Tradeoffs between large and 

small vehicles are complex and not well understood because we typically only 

observe crashes after they happen (and not crashes which are avoided). In general, 
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newer vehicles have better safety equipment and performance characteristics than 

older vehicles, and larger vehicles afford more protection in a crash.

Motorcycles and large displacement vehicles (e.g., trucks and buses) involve crash 

factors different from passenger vehicles. In both cases, crashes involving these 

vehicles tend to be more severe. Although motorcycles are highly maneuverable, 

crashes involving motorcycles tend to be more severe due to the lack of protection 

and, in some cases, the operator’s behavior. Trucks, on the other hand, have far 

less maneuverability, but provide a high degree of protection. Crashes between a 

passenger vehicle and a large truck tend to result in injury to the passenger vehicle 

occupants rather than the truck driver. The majority of these crashes are often 

attributable to driver error on the part of the passenger vehicle driver and not to 

the trucks’ maneuverability limitations.

Vehicle safety is generally approached from two perspectives:

1. Crash Avoidance – Numerous factors are incorporated into vehicles to avoid 

crashes. In general, the more maneuverable and agile a vehicle is the more 

likely it can avoid a crash. Also light, compact, and low vehicles offer superior 

maneuverability compared to heavy, large, and tall vehicles.

2. Crash Protection – Once a crash occurs, different vehicle factors become 

important (e.g., vehicle safety equipment, ability to absorb energy, etc.).

Environmental Factors

Environmental crash factors are usually weatherrelated and typically contribute to crashes through 

interactions with vehicle or driver-related factors, 

but sometimes these factors are responsible for 

crash occurrence. The following environmental 

factors contribute to crashes.

•	 Rain – Wet pavement has lower friction than dry pavement, so traction is 

reduced. Also, pooling of water can lead to hydroplaning and loss of vehicle 

control. Finally, rain reduces visibility. In most wet conditions, drivers can 

accommodate the reduced visibility; however, often a crash occurs in wet 

conditions due to drivers not accommodating sufficiently for the reduced 

friction between tires and pavement.

•	 Snow, Sleet, and Ice – Snow and ice can be hazardous due to extreme loss 

of traction. Ice is often more hazardous because it cannot be seen and anticipated. Also, ice often forms sporadically and catches drivers by surprise.

•	 Fog – Fog can reduce visibility to several feet, rendering a driver virtually 

blind.

Typically, crashes are the result 

of multiple crash factors. The 

engineering study must carefully 

analyze all possible crash factors 

to identify the most effective 

solution.
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•	 Wind – Windy conditions contribute to crashes, especially for large trucks, 

motorcycles and other small vehicles.

•	 Sun – The sun contributes to crashes because of glare and reduced visibility 

during periods of high glare.

In summary, crashes rarely involve a single crash factor; hence, careful analysis 

of all possible crash factors is imperative. The analysis is necessary for not only 

identifying all factors that contribute to a crash, but also to identify the most costeffective countermeasures.

Crash Pattern Analysis

Crash patterns should be identified through an analysis of the crash data for specific 

locations. The crash patterns can be identified using a collision diagram, collision 

summary, field reviews, input from other disciplines, and other information.

When conducting a crash analysis, it is useful to create a summary table of the 

crashes that occurred during the study period. The table could include a summary 

of the pavement conditions, crash type, lighting conditions, number of injuries 

or fatalities, and any other relevant information, such as driver-related facts (i.e., 

age, gender, restraint use). The summary table can provide insight for identifying 

crash patterns. An example collision summary is shown in Table 3.1.

Table 3.1 summarizes the date and time of each collision, the crash type, injuries, 

time of day (day or night), and the contributing cause reported by the law 

enforcement officer. This summary can help identify any dominant crash types 

or prevailing conditions. It may also be beneficial to summarize driver-related 

information such as age, gender, restraint use, level of impairment, etc.

As shown in Table 3.1, left turn collisions appear to be a significant problem at 

this intersection, comprising 60 percent of the crashes during the one-year time 

period shown. In addition, it is sometimes helpful to compare site specific crash 

summaries to statewide averages to identify trends or overrepresentation. In this 

case, there were no apparent trends in crashes occurring at night (27 percent) or on 

wet pavement conditions (13 percent).

Although a crash summary provides some insight on potential issues, the next 

step is to develop a collision diagram to better understand what is occurring on a 

study roadway segment or intersection.
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Table 3.1 Intersection Collision Summary

STUDY PERIOD: 1/1/08-12/31/08 CITY: Springfield

ROADWAY: Center Street COUNTY: Orange

INTERSECTION: Main Street SOURCE OF DATA: Local Law Enforcement

No. Date Time Type

Ped

Bike Fatal Injuries

Property 

Damage

Day/

Night

Wet/

Dry

Contributing 

Cause

1 1/6/2008 7:30 p.m. Left Turn 0 0 1 $2,500 Night Dry FTYROW*

2 1/21/2008 12:15 p.m. Rear End 0 0 2 $1,500 Day Dry Followed too 

Closely

3 2/6/2008 2:30 p.m. Left Turn 0 0 1 $3,000 Day Dry FTYROW

4 4/1/2008 4:50 p.m. Angle 0 0 0 $2,000 Day Dry FTYROW

5 4/20/2008 8:25 p.m. Left Turn 0 0 0 $2,500 Night Dry FTYROW

6 5/16/2008 5:30 p.m. Rear End 0 0 2 $1,000 Day Wet Followed too 

Closely

7 5/26/2008 9:00 p.m. Angle 0 0 1 $2,500 Night Dry FTYROW

8 6/9/2008 6:10 p.m. Left Turn 0 0 0 $3,000 Day Dry FTYROW

9 7/19/2008 5:00 p.m. Left Turn 0 0 1 $2,000 Day Dry FTYROW

10 9/1/2008 10:00 a.m. Left Turn 0 0 0 $2,500 Day Dry FTYROW

11 9/8/2008 4:45 p.m. Left Turn 0 0 2 $2,500 Day Dry FTYROW

12 10/30/2008 3:25 p.m. Rear End 0 0 1 $1,000 Day Dry Followed too 

Closely

13 11/11/2008 6:30 p.m. Rear End 0 0 0 $1,500 Night Wet Followed too 

Closely

14 1/21/2008 5:00 p.m. Left Turn 0 0 0 $3,000 Day Dry FTYROW

15 12/19/2008 4:55 p.m. Left Turn 0 0 3 $2,000 Day Dry FTYROW

Total 

No.

Ped/

Bike Fatal Injuries Angle

Left 

Turn

Rear

End

Side

Swipe

Out of

Control Night Wet

15 0 0 9 2 9 4 0 0 4 2

100% 0% 0% 60% 13% 60% 27% 0% 0% 27% 13%

* FTYROW – Failed to Yield Right-of-Way.

Collision Diagram

Transportation professionals prepare collision diagrams to demonstrate the flow 

and direction of travel to further illuminate the circumstances surrounding crashes. 

The collision diagram provides a visual representation of the crash data and can 

help identify crash patterns. Figure 3.3 shows an example collision diagram.
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Figure 3.3 Collision Diagram

First Avenue

Western

Driveway

Central 

Driveway

Eastern

Driveway

Atlantic Boulevard

N

LEGEND

Rear End Collision

Left Turn Collision

Right Angle Collision

Sideswipe

9

10

12

13

19 7

15

4

8

11

3

16

14

6

2

5

1

18

17

Figure 3.3 illustrates 19 crashes occurring during the study time period. The diagram shows the location of each crash, as well as the crash type. The crashes are 

numbered in sequential order, starting with the most recent.

As shown in Figure 3.3, there are multiple driveways on the south side of the 

study roadway (First Avenue). The collision diagram identifies the majority of 

the crashes are rear end collisions or left turn collisions with vehicles entering the 

driveways.

The collision diagram helps with identifying patterns, but it may not provide 

enough information to identify the contributing factors. The next step is to conduct a field investigation to determine what might be causing these crashes.
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3.2 Step 2 – Assess Site Conditions

After thorough analyses of the data, transportation professionals generally conduct 

a field or on‐site review of the identified crash sites. The purpose of this review 

is to confirm the previous analysis as well as to identify additional conditions 

which may have contributed to the crash and to begin the process of identifying 

countermeasures. The site is visited during the time of day representative of the 

safety problem to gather information. At this stage, additional partners may 

be involved, such as law enforcement, local officials and citizens, etc. The data 

gathered during the site visit includes, but is not limited to:

•	 Geometry, control, lane widths, etc.;

•	 Traffic counts (classification counts on 

roadways or turning movement counts 

at intersections);

•	 Sight distance at intersections and 

driveways;

•	 Segments/intersections from the point of 

view of users exiting and entering;

•	 Connections to existing infrastructure beyond the project limits;

•	 Land use activities in the vicinity (e.g., the presence of driveways, schools, 

shopping malls, etc.);

•	 Operations and road user interactions;

•	 Evidence of unreported crashes; and

•	 Future safety problems which might occur, especially under different weather, 

lighting, and traffic conditions

Viewing aerial photography prior to the site 

visit also can help assess the field conditions. 

In some cases, it may help identify a recent 

change in land use conditions or a potential 

issue to investigate further in the field.

Road safety audits (RSA) can be used to 

supplement the engineering study and provide a broader and more complete picture 

of the crash problem. The FHWA defines an RSA as “a formal and independent 

safety performance review of a road transportation project by an experienced team 

of safety specialists, addressing the safety of all road users.” RSAs provide an 

opportunity to improve safety by taking a detailed look at an existing or planned 

intersection or roadway segment and suggesting specific safety improvements. 

They are performed by a team of at least three people who represent different 

areas of expertise, such as engineering (e.g., design, traffic, maintenance, etc.), 

One state found the value of digging 

deeper when a review of the crash 

diagrams in combination with a field 

visit discovered the crashes were not 

occurring on the Interstate exit ramp, 

but were actually occurring at an 

off-system road in close proximity to 

the exit ramp.

RSAs can be integrated into Safety 

Circuit Rider programs which are 

aimed at improving safety 

on rural roads. This approach has 

proven successful for improving 

safety at low cost.
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law enforcement, public officials, community traffic safety advocates, and others. 

Interdisciplinary groups provide a more comprehensive view of road safety while 

the perspectives of individual disciplines may be more limited.

3.3 Step 3 – Identify Potential Countermeasures

Once the crash experience and site conditions have been characterized, the next 

step is to identify potential countermeasures. This is accomplished by identifying factors among the roadway, roadside, and operational features that are 

contributing to the crashes identified on the collision diagram. However, the 

process of identifying countermeasures is more complex and often involves 

engineering judgment. For each type of crash identified, you should ask these 

three questions:

1. What road user actions lead to the occurrence of crashes?

2. What site conditions contribute to these driver actions?

3. What can be done to reduce the chances of such actions or what are the potential 

countermeasures?

The words countermeasure or intervention are largely synonymous for a device, 

engineering improvement, program (e.g., law enforcement, public education and 

awareness, coalition building, etc.; Appendix B provides a case study on multidisciplinary approaches), policy, or investment intended to improve safety.

While diagnosing the problem and identifying countermeasures is a skill developed through experience, there are several resources available to assist in identifying appropriate countermeasures. The Resources section of this manual 

(Appendix E) outlines several of these resources and some of the documented 

best practices. New knowledge is continuously generated relative to the effectiveness of countermeasure approaches; hence, it is important to keep abreast of 

the available resources and tools.

Countermeasures may be identified during a field study, an RSA, a search of the 

literature on effective countermeasures, by agency policy, etc. It may prove fruitful 

to engage safety stakeholders and other partners when selecting potential solutions 

as they may provide unique perspectives. Involving local officials and citizens, as 

well as the safety partners will result in more comprehensive and potentially more 

effective multidisciplinary solutions as well as more practical and cost-effective 

approaches. For example, one study found a multimillion dollar engineering fix 

could be replaced with a few thousand dollars of law enforcement overtime and 

community education and achieve the same result.

Some states have initiated “fatality review committees.” They are typically comprised of multidisciplinary members from various agencies which may include 

metropolitan planning organization (MPO) officials, elected officials, highway 

safety practitioners, law enforcement, etc. The committees analyze the crash 

data for all traffic fatalities occurring in the jurisdiction and identify contributing 

crash factors and/or trends. The committees use their findings to offer recommendations for traffic safety improvements.
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Another tool that may support the countermeasure identification process is the 

Haddon Matrix. The Haddon Matrix is a two-dimensional model that applies 

basic principles of public health to motor vehicle-related injuries. It is widely 

used by the public health community and by some in the road safety community. 

Each cell of the matrix represents a different area in which countermeasures 

can be implemented to improve traffic safety. Those that apply to the pre-crash 

phase are designed to reduce the number of crashes, while on the other hand 

countermeasures that apply to the crash phase would not stop the crash, but could 

reduce the number or severity of injuries that occur as a result. Countermeasures 

focusing on the post-crash phase optimize the outcome for people with injuries, 

and prevent secondary events. (See Appendix C for more information on the 

Haddon Matrix.)

3.4 Step 4 – Assess Countermeasure Effectiveness

Countermeasure selection involves setting priorities. Step 4 of the engineering 

study process assesses the effectiveness of individual and groups of countermeasures. Once a set of countermeasures or potential solutions are identified, the list 

must be prioritized and pared to meet existing resources. Engineers generally 

accomplish this task by examining benefit/cost ratios (e.g., the amount of safety 

benefit gained compared to the cost of the improvement), which is discussed in 

great detail in Unit 4.

Crash Modification Factors (CMFs) are an excellent tool that can be used to estimate the expected safety benefits of various countermeasures and are available 

for many engineering improvements; however, the benefit/cost science concerning behavioral countermeasures is in its infancy. NCHRP 17‐33 Effectiveness of 

Behavioral Highway Safety Countermeasures (see Resources, Appendix E) is helpful 

for assessing the effectiveness of behavioral countermeasures.

Crash Modification Factors

Crash Modification Factors (CMF) and Crash Reduction Factors (CRF) provide 

agencies with a method for estimating the expected crash reduction and/or benefits associated with various countermeasures and may be useful in identifying 

appropriate countermeasures. These terms are different methods for expressing 

the expected effectiveness of various countermeasures. A CMF is a multiplicative factor used to compute the expected number of crashes after implementing 

a given countermeasure at a specific site, while a CRF is the percentage crash 

reduction that might be expected after implementing a given countermeasure. The 

relationship between a CMF and CRF is quite simple. The CMF is the difference 

between 1.0 and the CRF divided by 100 (e.g., CRF = 20 percent has a CMF equal 

to (1.0 ‐20/100) or 0.8).
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CMFs are developed based on research studies and program evaluations (e.g., 

before/after studies and cross-sectional studies). They can be used to compare 

safety conditions with or without a particular treatment, or they can be used to 

compare the safety outcomes of alternative countermeasures or treatments.

Generally, a CMF is determined by the ratio of the expected number of crashes 

with a countermeasure to the expected number of crashes under identical conditions without a countermeasure.

Where,

CMF = CMF for treatment ‘t’ implemented under conditions ‘a’;

Et = the expected crash frequency with the implemented treatment;

Ea = the expected crash frequency under identical conditions but with no 

treatment. In a simple before-after study, the conditions before the 

treatment are used.

This comparison with and without a treatment is traditionally conducted at one 

location and then aggregated across several locations to obtain a CMF estimate. 

The ratio involves expected values not counts. One method for developing CMFs 

uses Empirical Bayes (EB) analysis which determines the expected number of 

crashes which would have occurred at the site with no treatment. The expected 

value may be derived from the Safety Performance Function (SPF) value for a 

particular facility type and the average annual daily traffic (AADT) count. CMFs 

start with a 1.0 number which indicates no change occurred; CMFs greater than 

1.0 indicate an increase in the number of crashes and those less than 1.0 indicate a 

reduction in crashes can be expected.

In many cases, more than one treatment is implemented at the same time. CMFs 

are assumed to be multiplicative (CMFcombined = CMF1 x CMF2 x CMF3 x ...x CMFi), 

meaning that you simply multiply them by each other to calculate a combined 

CMF. However, it is important to realize CMFs multiplied together, assumes the 

effects of each CMF are independent. It is possible to overestimate the combined 

effect of multiple treatments, especially when more than one treatment is expected 

reduce the same crash type (e.g., widen lanes, widen shoulder). When using CMFs 

to estimate the effectiveness of multiple countermeasures, engineering judgment 

must be used to assess the interrelationship and/or independence of the various 

countermeasures, especially if more than three CMFs are considered.
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The following example demonstrates how to use CMFs to estimate the expected 

crash reduction associated with implementing two countermeasures:

Given a rural two-lane roadway segment with 19 single vehicle crashes in the 

last year, identify the expected crash reduction associated with increasing the 

pavement friction (CMF = 0.7) and installing shoulder rumble strips (CMF = 0.79).

1. The first step is to calculate the combined CMF:

CMFcombined = 0.7 x 0.79 = 0.55

2. Next, calculate the estimated reduction in single vehicle crashes:

Crash reduction = (19 crashes/year) x (1 – 0.55) = 8.55 crashes/year

Several states and local jurisdictions use CMFs, but the value of the CMF used for 

a particular countermeasure may vary by agency. In many cases, multiple CMFs 

exist for the same countermeasure, which may provide varying levels of effectiveness in improving safety. Multiple resources are available from which widely 

accepted CMFs can be obtained to provide safety practitioners with an estimate of 

countermeasure effectiveness (resources are presented later in this section). Even 

when using published CMFs, practitioners should make every effort to use a CMF 

applicable to their state and local roadway conditions.

Agencies can incorporate CMFs into safety tools to estimate the safety benefits 

associated with various countermeasures and to identify which countermeasure 

will provide the greatest return on the investment. However, agencies should use 

caution in selecting CMFs, as not all CMFs are equally reliable.

CMF Considerations

Several of the underlying problems with the reliability of CMFs can be attributed 

to the following issues (Harkey et al., 2008):

•	 Origins/Transferability – The origins of CMFs are not always known by the 

end user; some states develop their own based on crash data, while others 

simply adopt CMFs developed by other states. This transfer of CMFs may 

reduce their validity based on differences in crash investigation techniques as 

well as roadway, traffic, weather, drivers, and other characteristics.

•	 Methodological Issues – Many existing CMFs are derived from a before/after 

analysis of actual implemented countermeasures. Deriving CMFs from 

before/after analysis produces the best estimates if the study is conducted 

properly. Issues related to the methodology include:

– Use of a site with an unusually high-crash incidence in the before-treatment 

can yield significantly exaggerated CMF estimates due to the phenomenon 

of regression to the mean. (Discussed in Unit 2).

– Failure to properly separate the safety effects of other changes such as 

traffic volumes, impacts of other simultaneously implemented treatments, 

crash reporting differences, or underlying crash trends across time.
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– Use of a sample size too small for 

valid analysis (a large number of 

sites with the same combination of 

countermeasures are needed for 

a valid analysis). It is best to use a 

minimum of 10 to 20 sites.

– Comparison of unsuitable groups.

– Incorrect interpretation of estimates’

accuracy or presentation of results 

without statements of accuracy.

•	 Variability – CMFs may be dependent 

on a variety of factors such as traffic 

volumes, crash experience, and site 

characteristics which may limit the applicability of a single CMF value.

•	 Crash Migration and Spillover Effects – 

Some countermeasures may cause crashes to migrate to adjacent locations. 

For instance, converting a two-way stop-controlled intersection to all-way stop 

may increase crash frequency at nearby two-way stop-controlled intersections 

due to driver confusion and expectation. This phenomenon is rarely accounted 

for in existing CMFs.

•	 Lack of Effectiveness Information – CMFs have not been developed for 

many Intelligent Transportation System (ITS) improvements and operational 

strategies. While many of these strategies are focused on improving traffic 

flow, they also may benefit traffic safety. For example, improving traffic signal coordination on a corridor may not only improve traffic flow, it also might 

reduce the number of rear end collisions.

•	 Combination of Improvements – When a facility is rebuilt, multiple 

improvements are typically implemented; yet CMFs were developed for 

individual improvements. Typically the CMFs are assumed to be multiplicative 

(CMFcombined = CMF1 x CMF2 x CMF3 x ...x CMFi); however, very little sound 

research exists on the combination of treatments which leads to uncertainty in 

the accuracy of combining individual CMFs to capture a true combined effect.

Some CMFs were developed based on 

the reduction of all crash types and 

do not isolate the specific crash type 

being addressed with the selected 

countermeasure. These CMFs 

will generally result in a smaller 

reduction in crashes compared to one 

that isolates a particular crash type. 

Additionally, a specific countermeasure may have varying degrees of 

effectiveness based on severity. For 

example, installing a cable median 

barrier may be effective at preventing 

across median fatal and serious 

injury crashes, but PDO run-off the 

road crashes may increase.
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•	 Publication/Citation Issues – Another potential weakness is a tendency 

to publish studies which produce favorable results for the treatment being 

evaluated, as well as a tendency to ignore the negative aspects of results (i.e., 

declining effects over time or unintended consequences leading to increases in 

other crash types).

It is important to recognize the potential limitations and vulnerabilities associated 

with CMFs. Engineering judgment should always be applied when using CMFs. 

Despite the potential weaknesses, valid CMFs are a key component of existing 

safety tools and resources used to prioritize safety programs.

Countermeasure Research

Staying current on effective countermeasures requires research, continuing education, and peer networking. The research and literature are constantly changing 

as policies, procedures, engineering judgment, conventional wisdom, etc., are 

constantly evaluated to determine new and improved methods for improving 

road safety. The Resources section of this manual (Appendix E) provides several 

tools and references related to CMFs.

The CMF Clearinghouse is an example of an available tool to assist transportation 

professionals with assessing countermeasure effectiveness. It is a web site that 

contains a searchable database of CMFs. Users can search by countermeasure, 

crash type and severity, and other variables. Transportation professionals also can 

submit their own CMF studies to the Clearinghouse.

The four steps of the engineering study process (analyze the data, assess site 

conditions, identify potential countermeasures and assess countermeasure effectiveness) are demonstrated using a case study in the next section.

3.5 Engineering Case Study

This example case study is presented to 

provide a more thorough understanding of 

steps involved in an engineering study.

In this case study, a particular intersection 

already has been identified as having a greater 

than normal crash experience, compared to 

intersections on similar roadways in the state. 

To identify any potential safety problems, as 

well as potential countermeasures, the first 

step is further analysis of the intersection 

crash data.

When obtaining crash data, it is 

important to realize roadways may be 

referenced by several different names, 

depending on the reporting officer. 

They may be referred to by the state 

route number or by the local street 

name; additionally, abbreviations 

may be used to identify the roadway 

(e.g., State Road 400, SR 400, Center 

Street, Center St, Ctr St). The engineer should search for crash reports 

using all possible references for the 

desired location.
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Step 1 – Analyze the Data

Two years of crash reports were obtained from local law enforcement for the 

intersection. The major route in this study is State Road 400; however, this roadway 

is referenced locally as Center Street. Both roadway names and any variations 

should be used in the crash records search.

During the two-year study period a total of 17 crashes occurred at the intersection 

which is summarized in Table 3.2.

Table 3.2 Collision Summary

STUDY PERIOD: 1/1/07-12/31/08 CITY: Smithville

ROADWAY: State Road 400 COUNTY: Red River

INTERSECTION: Shopping Center Drive SOURCE OF DATA: Local Law Enforcement

No. Date Time Type Ped Bike Fatal Injuries

Property 

Damage Day/Night Wet/Dry

Contributing 

Cause

1 1/6/2007 3:25 p.m. Angle 0 0 0 $2,000 Day Dry FTYROW

2 1/21/2007 5:15 p.m. Rear 

End 0 0 0 $1,500 Day Dry Followed too Closely

3 2/6/2007 6:40 p.m. Angle 0 0 1 $3,000 Night Dry FTYROW

4 4/1/2007 4:50 p.m. Angle 0 0 0 $2,000 Day Dry FTYROW

5 4/20/2007 4:00 p.m. Left 0 0 2 $2,500 Day Dry FTYROW

6 6/9/2007 5:30 p.m. Angle 0 0 0 $1,500 Day Wet FTYROW

7 7/19/2007 7:00 p.m. Angle 0 0 0 $2,000 Night Dry FTYROW

8 10/30/2007 6:10 p.m. Angle 0 0 1 $3,000 Day Dry FTYROW

9 12/1/2007 5:00 p.m. Angle 0 0 0 $1,500 Day Dry FTYROW

10 12/19/2007 10:00 

a.m.

Rear 

End 0 0 0 $1,000 Day Dry Followed too Closely

11 1/2/2008 4:45 p.m. Rear 

End 0 0 1 $1,500 Day Dry Followed too Closely

12 1/9/2008 5:25 p.m. Rear 

End 0 0 0 $1,000 Day Dry Followed too Closely

13 2/19/2008 6:30 p.m. Rear 

End 0 0 0 $1,500 Night Wet Followed too Closely

14 4/27/2008 5:00 p.m. Angle 0 0 3 $3,000 Day Dry FTYROW

15 6/21/2008 4:55 p.m. Angle 0 0 1 $2,000 Day Dry FTYROW

16 10/9/2008 6:15 p.m. Angle 0 0 0 $2,000 Day Dry FTYROW

17 11/23/2008 5:30 p.m. Angle 0 0 0 $1,500 Night Dry FTYROW

Total No. Ped Bike Fatal Injuries Angle Left Turn Rear End

Side 

Swipe

Out of 

Control Night Wet

17 0 0 6 12 0 5 0 0 4 2

100% 0% 0% 35% 71% 0% 29% 0% 0% 24% 12%
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3-17

As shown in Table 3.2, angle collisions appear to be a significant problem at this 

intersection, comprising 71 percent of the crashes during the two-year time period. 

In this case, no apparent trends in crashes occurred at night (24 percent) or on wet 

pavement (12 percent); however, further analysis of this crash data reveals the 

majority of these collisions occur during the evening peak period.

To better understand the crash experience at this intersection, the next step is to 

develop a collision diagram. In most cases, the crash reports will provide sufficient information to develop the collision diagram; however, if the engineer is 

unfamiliar with the area or if the intersection is complex, a preliminary field visit 

may be required to determine the layout of the intersection.

The collision diagram for the study intersection is shown in Figure 3.4. The diagram shows the location of each crash, as well as the crash type (the crash numbers 

on the diagram correspond to the crash number in Table 3.2).

Figure 3.4 Intersection Collision Diagram

Shopping Center 

Driveway

Auto Repair

N

Fast Food 

Restaurant

Center Street

10

7

6

8

4

3

5

1

17

9

12 2

13 11

15

14

LEGEND

Rear End Collision

Left Turn Collision

Right Angle Collision

16
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Planning: Countermeasure Identification

3-18

The collision diagram identifies the majority of angle collisions occur in median 

of this intersection, but based on the data, it is unclear why so many collisions 

are occurring in the median. The next step is to conduct a field investigation to 

determine what might be causing these crashes.

Step 2 – Assess Site Conditions

The study intersection is unsignalized and located in a suburban area. The intersection is at the connection of a shopping center with Center Street (State Road 

400), which is an east-west four-lane divided roadway with a striped median. The 

shopping center driveway connects on the south side of Center Street (State Road 

400) and has a two-lane approach – one left turn lane and one right turn lane. A 

major signalized intersection is located approximately 500 feet east of the study 

intersection.

As part of the field review, the following data were collected by the study engineer:

•	 A.M. and p.m. peak hour turning movement counts and 72-hour approach 

counts;

•	 Lane geometry and traffic control;

•	 Site distance (found to be adequate); and

•	 Surrounding land use.

Since the majority of the crashes occurred during the p.m. peak hour, the site was 

observed during this time period to identify operational issues. The field observations revealed significant vehicle queues resulting from the major signalized 

intersection located to the east. The queues extended almost a mile beyond the 

intersection. Several drivers were observed using the striped median as a travel 

lane to bypass the queue and enter the left-turn lane at the adjacent intersection. 

The site visit also revealed several near-misses between vehicles exiting the shopping center driveway to turn left and vehicles driving in the median.

No sight distance issues were identified based on the roadway alignment at the 

intersection, but the vehicle queues limit the sight distance of the vehicles turning 

left out of the shopping center driveway. The limited sight distance, in combination with illegal use of the median as a travel lane, were identified as factors contributing to crashes occurring at the intersection.

Now that the problem has been identified, the next step is to identify countermeasures to address the safety issue.
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3-19

Step 3 – Identify Potential Countermeasures

A number of countermeasures could be selected to improve safety at this intersection. Some options include:

•	 Prohibit left turns out of the shopping center driveway. This could be accomplished by adding a raised or striped median to the driveway and signage.

•	 Install a raised median in place of the striped median on the major roadway 

to completely remove the potential conflict by prohibiting left turns out of the 

driveway and restricting vehicles from driving in the median; however, it will 

limit access to the adjacent businesses.

•	 Add signage restricting vehicles from traveling in the median.

•	 Implement enforcement campaign(s) targeting drivers illegally driving in 

median.

•	 Develop and conduct a public awareness campaign, including partnering with 

local businesses, to educate drivers on the dangers of driving in a designated 

median.

Each of these countermeasures would have a different impact. The next step is to 

assess their effectiveness.

Step 4 – Assess Countermeasure Effectiveness

CMFs can be used to estimate the expected safety benefits of various countermeasures. The countermeasure with the lowest CMF will be the most effective; 

however, when CMFs are not available, engineering judgment should be used.

In this case study, locally calibrated CMFs were not available, so engineering 

judgment was used to assess the effectiveness of the various countermeasures. 

Since installing a raised median completely removes the potential conflict, it is 

the most effective alternative for addressing the problem. The next best option 

is to prohibit left turns from the driveway by adding channelization and signage; 

however, since access is not restricted in the median, some vehicles will still try to 

make the turn. Increased enforcement is likely to work when law enforcement is 

observed but will be less likely to address the problem long term. Finally, adding 

signage to restrict vehicles from the median or implementing a public awareness 

campaign will have less of an impact on addressing the issue compared to the 

other options, since both of these options are reliant on driver decisions.

Although installing the raised median is the most effective option in this case in 

terms of reducing crashes, the most effective countermeasure may not always 

be feasible because of funding limitations or political constraints. The next unit 

demonstrates how to prioritize countermeasures and projects based on available 

resources.
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3.6 Summary

In this unit, we learned how to identify contributing crash factors, as well as 

potential countermeasures for preventing crashes and mitigating crash severity. 

An engineering case study illustrated the process. This unit also described how 

CMFs can be used to assess the effectiveness of various countermeasures; however, other factors need to be considered, such as costs and available funding. 

Unit 4 provides guidance on how to establish priorities for project implementation 

based on available resources.
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Planning: Project Prioritization

4.0 Planning: Project Prioritization

After contributing crash factors and potential countermeasures have been identified, the next step is to prioritize countermeasures and projects for implementation. Unit 4 focuses on project prioritization processes and applying them to the 

locations identified with potential for safety improvement. A variety of methods 

for prioritizing safety projects are presented, including benefit/cost analysis, 

ranking, and optimization approaches.

4.1 The Objective Approach

Once locations with potential for safety improvement and potential countermeasures have been identified, the next step is to establish priorities for implementing these projects.

Safety is a complex issue and usually no single solution can completely solve an 

identified road safety problem. Solutions may vary in cost; involve an educational, engineering, or enforcement approach; or be categorized as a “quick fix” or 

a long-term strategy. Safety professionals are constantly challenged to weigh the 

menu of possible solutions and prioritize those which best address the problem 

given existing constraints and resources.

Quantitative analysis should be used whenever possible in the prioritization 

process, which typically involves identifying and comparing cost, effectiveness, 

and resilience (i.e., length of effectiveness) for each countermeasure or program 

based on the latest research.

Quantitative information lends objectivity to a decision-making process which 

might otherwise be dominated by subjective judgment or political considerations. 

It helps ensure the maximum safety benefit will be obtained for the amount of 

funds invested.

Various quantitative project prioritization methods (or project selection methods) 

can be used to compare alternative projects for a single site, across multiple sites, 

or for an entire network. Projects can be prioritized by simply ranking them based 

on specified factors (e.g., project cost, total number of crashes reduced, etc.) or a 

project’s benefit/cost ratio (discussed later in this unit). Alternatively, projects can 

be prioritized using an optimization process which maximizes the safety benefits 

based on budget and other constraints.

Challenges to the Objective Approach

Many considerations may enter into project selection beyond safety. These considerations, some of which may be quantified, play an important role in the project 

selection process and include the following:
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•	 Design Standards – Some safety countermeasures, especially untested or 

innovative ones, may conflict with established design standards. Decisionmakers may avoid these countermeasures due to liability concerns.

•	 Project Programming – In some instances, higher priority projects may 

require more effort in project development (i.e., NEPA, right-of-way, design). 

This delay may promote projects of lesser priority through to implementation 

earlier than may have been warranted through a quantitative analysis.

•	 Tradeoffs – In transportation organizations, safety must compete with other 

concerns and priorities, such as improving mobility or reducing the environmental impact of transportation systems. Resistance to countermeasures 

perceived to conflict with other priorities may exist. For example, opposition 

to installation of a protected left-turn signal arrow may appear because it 

increases the time drivers wait at an intersection; hence, it may be perceived to 

hamper mobility.

•	 Familiarity – Some individuals or organizations may oppose implementation 

of certain countermeasures simply because they are unfamiliar with them. 

Decision-makers and stakeholders often have different perspectives on solving 

problems, and may have a vested interest in a specific solution. For example, 

maintenance engineers might oppose cable barriers because they are unsure 

how much effort is needed to maintain them.

•	 Constituent Concerns – Elected officials may favor or oppose certain 

countermeasures because of constituent concerns or demands. If constituents 

demand a particular solution to a safety problem, politicians may support it 

regardless of cost-effectiveness. Most transportation decisions are ultimately 

political in nature. For this reason, it is imperative to provide information 

derived from data-driven, quantitative analysis to officials so they have the 

facts to make an informed decision.

All these factors may play a role in project prioritization, but transportation safety 

professionals generally prioritize projects based on what will achieve the greatest 

results within the available funding constraints. Some safety investment outcomes 

are more easily measured than others. As an example, a reduction in the number 

of crashes with an intersection improvement is more easily measured than a 

public awareness campaign focused on deterring driving under the influence of 

alcohol. In any event, every attempt should be made to establish the quantitative 

benefit of expected outcomes and these metrics should at least provide weight, if 

not determine, project selection.

Quantifying these benefits can be accomplished as part of a benefit/cost analysis. 

Benefit/cost analysis is a quantitative measure commonly used in prioritizing 

projects and countermeasures. The next section provides guidance on how to 

estimate project costs and benefits.
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Planning: Project Prioritization

4.2 Benefit/Cost Analysis

A benefit/cost analysis compares all of the benefits associated with a countermeasure (e.g., crash reduction, etc.), expressed in monetary terms, to the cost of 

implementing the countermeasure. A benefit/cost analysis provides a quantitative measure to help safety professionals prioritize countermeasures or projects 

and optimize the return on investment.

Some safety countermeasures have a higher-cost value than others. Geometric 

improvements to the road, such as straightening a tight curve to reduce runoff-road crashes, tend to be very expensive. Installing a “curve warning” sign 

and in‐curve delineation addresses the same problem, but at a much lower cost. 

Although both countermeasures address the same problem, the actual safety 

benefit will not be the same. Straightening the curve would be expected to provide a greater benefit compared to installing the sign and delineation, since it is 

removing the potential hazard. While the sign provides the driver with advanced 

warning of the curve and delineation can help the driver recognize and negotiate 

through the curve, it is still up to the driver to reduce speed. Safety professionals 

take the relative costs and benefits into consideration when prioritizing among 

countermeasures.

Part of calculating the cost of a countermeasure is considering how those costs 

vary over time, including any maintenance costs, as well as the relative resilience 

or “lasting power” of the countermeasure. One countermeasure may be just as 

effective as another in the short term, but less cost-effective over a longer time 

period. For example, installing speed cameras along a corridor requires significant up-front cost, but over time may be less expensive than an aggressive law 

enforcement program. Formal benefit/cost analysis takes resilience into account 

by calculating all of the project benefits and costs over a given time period. This 

allows comparison of countermeasures even though the timing of their impact 

varies.

Safety countermeasures have many direct safety benefits, including reductions in 

injuries, fatalities, and damage to personal property. Other direct benefits may 

occur, such as reduced queuing through signal synchronization.

Converting Benefits to a Monetary Value

A benefit/cost analysis expresses benefits in monetary terms, which requires 

an estimate of the number of crashes avoided as a result of the countermeasure, 

and the monetary value of each avoided crash. When available, CMFs should be 

used to determine the expected reduction in crashes. When CMFs from a quality 

study are not available, especially for nonengineering countermeasures such as 

educational or enforcement strategies or for experimental engineering treatments, 

safety professionals should use their subjective judgment and research evaluations 

when selecting countermeasures. Proven treatments should be considered along 

with experimental/untried treatments.
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Planning: Project Prioritization

One limitation to using benefit/cost analysis is fewer crashes may not always 

result in a positive outcome. For instance, cable median barriers are an accepted 

strategy for reducing the incidence of head-on collisions in run-off-road crashes. 

They do not necessarily reduce the number of run-off-road crashes, but do improve 

safety by reducing crash severity. Safety practitioners should consider both the 

likely change in number of crashes and the likely change in crash severity when 

calculating the benefits of a safety countermeasure.

The monetary value of crashes avoided is based on a dollar value of crashes by 

type and severity which many states and local agencies have developed. Costs can 

also vary by the type of vehicle involved (motor carrier versus personal vehicle).

Another way to determine the cost of a crash is to use the U.S. DOT’s Value of 

Statistical Life (VSL). In 2009, the U.S. Office of the Secretary of Transportation 

(OST) issued a memorandum updating the cost to avert a fatality to $6.0 million. 

VSL provides fractional values for use when assessing the benefit of preventing 

an injury crash based on the Maximum Abbreviated Injury Scale (MAIS) developed by the Association for the Advancement of Automotive Medicine as shown 

in Table 4.1. The injuries are ranked on a scale of one to six, with one being minor 

and six being fatal.

Table 4.1 Relative Disutility Factors by Injury Severity Level (MAIS)

MAIS Level Severity Fraction of VSL

MAIS 1 Minor 0.0020

MAIS 2 Moderate 0.0155

MAIS 3 Serious 0.0575

MAIS 4 Severe 0.1875

MAIS 5 Critical 0.7625

MAIS 6 Fatal 1.0000

Source: Office of the Secretary of Transportation (2009).

Using the MAIS scale in combination with the VSL will result in an injury cost 

for the different severity levels. However, these injury costs must be converted 

to a crash cost. Usually more than one injury and/or severity is associated with 

a crash. Typically an average number of injuries and severities are weighted to 

determine an average crash cost. For example, in a fatal crash there will typically 

be other injuries associated with the crash which may not be fatal; therefore, an 

average cost must be developed to account for the other injuries.

The “KABCO” injury scale also can be used for establishing crash costs. This scale 

was developed by the National Safety Council (NSC) and is frequently used by 

law enforcement for classifying injuries:
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Planning: Project Prioritization

•	 K – Fatal;

•	 A – Incapacitating injury;

•	 B – Nonincapacitating injury;

•	 C – Possible injury; and

•	 O – No injury.

The 2005 FHWA study, Crash Cost Estimates by Maximum Police-Reported Injury 

Severity within Selected Crash Geometries, provides crash cost estimates for several 

combinations of KABCO injury severities for 22 injury crash types. The NSC is 

another source for obtaining crash cost information by severity.

Crash costs by severity level were estimated as part of the development of the 

HSM. These costs were developed based on the KABCO scale and are shown in 

Table 4.2. If a state has not developed their own crash costs, these costs could be 

used to calculate safety benefits.

Table 4.2 Crash Costs by Injury Severity Level

Injury Severity Level Comprehensive Crash Cost

Fatality (K) $4,008,900

Disabling Injury (A) $216,000

Evident Injury (B) $79,000

Fatal/Injury (K/A/B) $158,200

Possible Injury (C) $44,900

PDO (O) $7,400

Source: Highway Safety Manual, First Edition, Draft 3.1, April 2009.

Since the service life of countermeasures varies, the annual monetary safety benefit 

should be converted to a present value so projects can be compared over a given 

time period. States typically have a list of the service lives of countermeasures to 

use for estimating project costs. Two methods are presented here for converting 

benefits to a present value. The first method is used when the annual benefits are 

uniform throughout the service life of the project, and the second is used when the 

annual benefits vary throughout the service life of the project.

Method 1: Uniform Annual Benefits
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Planning: Project Prioritization

Where:

PVBv = present value of the safety benefits for a specific site, v.

(P/A,i,n) = is a factor that converts a series of uniform annual amounts to 

its present value.

i = minimum attractive rate of return or discount rate (i.e., if the 

discount rate is 4 percent, i = 0.04).

n = year in the service life of the countermeasure(s).

For example, if the expected lifespan of a project is five years, the discount rate is 

four percent, and the annual monetary benefit is $1,667,500, the present value of 

the safety benefits is calculated as follows:

(P / A,i,n) = (1+0.04)5 -1

0.04(1+0.04)5

= 4.452

PVBv

 = $1,667,500 x 4.452 = $7,423,414

Method 2: Nonuniform Annual Benefits

The safety effectiveness of some countermeasures is not consistent throughout 

the project, such as retroreflectivity of lane markings which change over time. 

When the benefit of the countermeasure varies over the service life of the project, 

nonuniform annual monetary values should be calculated for each year of service, 

which are then combined to determine a single present value. Start by calculating 

the present worth values for each year of service:

Where:

(P/F,i,n) = is a factor that converts a single future value to its present value.

i = discount rate.

n = year in the service life of the countermeasure(s).

The individual present worth values are then added together to develop a single 

present worth value for the safety benefits of the countermeasure.

For example, the annual monetary benefits associated with a safety improvement 

for each of the five years of a project’s service life are provided in the following 

table. This discount rate is four percent.
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Planning: Project Prioritization

Year in 

Service Life

Annual Monetary

Value of Benefits (P/F,i,n)

Present Value 

of Benefits

1 $923,237 0.962 $887,728

2 $929,655 0.925 $859,518

3 $935,235 0.889 $831,421

4 $912,879 0.855 $780,333

5 $931,880 0.822 $765,937

Total $4,124,937

The first step is to calculate the factor that converts the future value to a present 

value for each year. For the first year:

The factor is calculated for each of the years as shown in the above table, and then 

the annual monetary benefits are multiplied by this factor to obtain the present 

value of the benefits. For the first year:

The present value of the benefits is then summed for each year to obtain the total 

present value of benefits, which is $4,124,937 for the service life of this project.

Project Cost Estimation

The project cost estimation procedure for evaluating safety countermeasures 

follows the same process as cost estimates for other construction or program 

implementation projects. Project costs are unique to each site and proposed 

countermeasure and may include costs associated with: right-of-way acquisition, 

material costs, grading and earthwork, utility relocation, environmental impacts, 

maintenance, and cost related to planning and engineering design work prior to 

construction.

According to AASHTO, all of the costs incurred over the service life of a project 

should be incorporated in the present value cost calculation, including all future 

maintenance, construction, or operating costs expected to occur during a project’s 

lifespan. Chapter 6 of the AASHTO Redbook6 provides additional guidance on 

categories of costs and their treatment in a benefit/cost analysis for:

6 The AASHTO Redbook addresses benefit/cost analysis for highway improvement projects. 

It provides decision-makers with a clear description of the approach and understanding of the

results of project benefit/cost analyses along with sufficient detail for practitioners to perform

these technical analyses. Specifically, it concentrates on highway-user benefits and costs and 

on project-level analyses.

04
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•	 Construction and other development costs;

•	 Adjusting development and operating cost estimates for inflation;

•	 Cost of right-of-way;

•	 Measuring the current and future value of developed or undeveloped land;

•	 Placing a value on already owned right-of-way;

•	 Maintenance and operating costs; and

•	 Creating cost estimates.

To conduct a benefit/cost analysis, the project costs need to be expressed as 

present values. Typically construction and/or implementation costs already are 

expressed as present values; however, any future costs will need to be converted 

to present values using the methods presented in the benefits section.

Once the project benefits and costs have been estimated, they can be used to prioritize alternative countermeasures at a particular site or several projects across 

various sites. The next two sections focus on these prioritization methods.

4.3 Countermeasure Evaluation Methods

Economic evaluations should be conducted on alternative countermeasures to 

verify a project is economically justified, meaning the benefits are greater than 

the costs. The net present value method and a benefit/cost ratio are two methods 

for evaluating the economic effectiveness and feasibility of safety improvement 

projects at a particular site. The cost-effectiveness index can be used when it is not 

possible to express the benefits in monetary terms.

Net Present Value

The net present value (NPV) method, or net present worth (NPW) method, 

expresses the difference between the discounted costs and discounted benefits of 

a safety improvement project. The costs and benefits are “discounted” meaning 

they have been converted to a present value using a discount rate.

The NPV method has two basic functions. It can be used to determine which 

countermeasure(s) provides the most cost-efficient means based on the countermeasure(s) with the highest NPV. It also can determine if a project is economically 

justified meaning a project has a NPV greater than zero (or the benefits are greater 

than the costs).

The NPV is calculated based on the present value calculations of the project benefits and costs previously discussed.

NPV = PVB – PVC
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Where:

PVB = Present value of benefits; and

PVC = Present value of costs.

A project is economically justified if the NPV is greater than zero. This method 

identifies the most desirable countermeasure(s) for a specific site, and it also can 

be used to evaluate multiple projects across multiple sites.

Benefit/Cost Ratio

The benefit/cost ratio (BCR) is the ratio of the present value of the benefits of a 

project to the present value of costs of the project.

BCR = PVB/PVC

Where:

PVB = Present value of benefits; and

PVC = Present value of costs.

A project with a BCR greater than 1.0 is considered economically justified. However, the BCR is not applicable for comparing various countermeasures or multiple projects at various sites; this requires an incremental benefit/cost analysis.

Cost-Effectiveness

In situations where it is not possible or practical to monetize countermeasure 

benefits, a “cost-effectiveness” metric can be used in lieu of the net present value 

or benefit/cost ratio. Cost-effectiveness is simply the amount of money invested 

divided by the benefit in crash reduction. It is expressed as the cost for crash 

avoided with a certain countermeasure. In this case, the countermeasure with the 

lowest value is ranked first.

A cost-effectiveness Index can be calculated as follows:

Cost-Effective Index = PVC/AR

Where:

PVC = Present value of project cost; and

AR = Total crash reduction.

The present value of the project cost is calculated in the same manner as in 

benefit/cost analysis. This is a simple and quick method which provides a general 

sense of a project’s value and can be used to compare other safety improvement 

projects. However, this method does not account for value differences between 

reductions in fatal crashes as opposed to injury crashes, and whether a project is 

economically justified.
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4.4 Prioritization Methods

Once alternative countermeasures or projects have been determined to be economically justified, the next step is to prioritize them for implementation. Alternative countermeasures identified at one or several sites can be prioritized using 

ranking, incremental benefit/cost analysis, or optimization methods. Ranking 

is the simplest of the methods presented and is best for making decisions on a 

limited number of sites. While an incremental benefit/cost analysis allows the 

analyst to compare the economic effectiveness of one project against another, it 

does not consider budget constraints. Optimization methods are best for prioritizing projects based on monetary constraints.

Ranking

Ranking is the simplest method for prioritizing countermeasures at a site or prioritizing projects across multiple sites. Some economic effectiveness measures 

that can be used for ranking include:

•	 Project costs;

•	 Monetary value of project benefits;

•	 Total number of crashes reduced;

•	 Number of fatal and injury crashes reduced;

•	 Net present value; and

•	 Cost-effectiveness index.

Individually, these ranking measures will not help safety practitioners obtain 

the best return on investment. For example, ranking the countermeasures based 

solely on the number of fatal and injury crashes reduced does not account for 

the cost of each countermeasure. Additionally, the countermeasure with the least 

cost may not have as significant reduction in fatal and injury crashes compared 

to a slightly higher-cost project. It is best to account for multiple measures when 

ranking countermeasures such as using the net present value or cost-effectiveness 

methods.

Net Present Value

The following is an example using the net present value to rank four alternative 

countermeasures to improve safety at a site. The present value of the benefits and 

costs of each alternative are provided in the following table.
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Alternative

Countermeasure

Present Value 

of Benefits

Present Value 

of Costs

Net Present 

Value

Alternative

Rank

A $1,800,268 $500,000 $1,300,268 3

B $3,255,892 $1,200,000 $2,055,892 1

C $3,958,768 $2,100,000 $1,858,768 2

D $2,566,476 $1,270,000 $1,296,476 4

For Alternative A, the net present value is calculated:

NPV = $1,800,268-$500,000 = $1,300,268

This same step is repeated for the other three countermeasure alternatives, which 

are then ranked based on their net present value. As shown, all four alternatives 

are economically justified with a net present value greater than zero. However, 

Alternative B has the greatest net present value for this site based on this method.

Cost-Effectiveness Index

The following is an example of using the cost-effective index to rank alternative 

countermeasures, given the present value of the costs and the total crash reduction.

Alternative

Countermeasure

Present Value 

of Costs

Total Accident

Reduction Cost-Effective Index

Alternative

Rank

A $500,000 43 11,628 1

B $1,200,000 63 19,048 3

C $2,100,000 70 30,000 4

D $1,270,000 73 17,397 2

For Alternative A, the cost-effective index is calculated:

Cost-Effective Index = 500,000/43 = 11,628

With this method, the lowest index is ranked first. The cost-effective index is calculated for the remaining alternatives as shown in the table, and Alternative A is 

ranked first, since it has the lowest cost associated with each crash reduction.

The above example simply used the number of crashes. This method also could 

be used with Equivalent Property Damage Only (EPDO) crash numbers and has 

the advantage of taking severity into account.
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Incremental Benefit/Cost Analysis

The benefit/cost ratios of the individual safety improvement projects are the 

starting point for an incremental benefit/cost analysis. The process for conducting 

an incremental benefit/cost analysis is as follows:

1. Rank the individual projects with a BCR greater than 1.0 in increasing order 

based on cost, with the smallest cost listed first.

2. Starting from the top of the list, calculate the difference between the first and 

second project’s benefits, and then calculate the difference between the first 

and second project’s costs. Calculate an incremental benefit/cost ratio by 

dividing the difference in benefits of the two projects by the difference in costs 

of the two projects.

3. If the incremental BCR is greater than 1.0, the project with the higher cost is 

ranked higher and compared with the next project on the list, meaning the 

magnitude of the benefits of the higher-cost project outweighs the higher cost. 

However, if the incremental BCR is less than 1.0, the project with the lower 

cost is ranked higher and compared with the next project on the list.

4. Repeat this process for the entire list. The best economic investment is the 

project selected in the last pairing.

5. To produce a ranking of projects, repeat the entire process for the remaining 

unranked projects to determine the project with the next best economic 

investment until all of the projects are ranked.

In instances where two projects have the same cost, the project with the greater 

benefit should be selected.

Example

The following is an example application using the incremental benefit/cost analysis, using the same four alternative countermeasures.
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Alternative Countermeasure

Present Value 

of Benefits

Present Value 

of Costs

Benefit/Cost

Ratio

A $1,800,268 $500,000 3.60

B $3,255,892 $1,200,000 2.71

D $2,566,476 $1,270,000 2.02

C $3,958,768 $2,100,000 1.89

1. The first step is to rank the alternatives by the present value of the costs, from 

lowest to highest, which already has been done in the table.

2. The incremental difference is calculated for the benefits and the costs for 

Alternatives A and B.

Incremental Benefits = $3,225,892-$1,800,268 = $1,455,625

Incremental Costs = $1,200,000-$500,000 = $700,000

Incremental B/C = $1,455,625/$700,000 = 2.08

3. Since the incremental benefit/cost ratio is greater than 1.0, Alternative B should 

be compared to Alternative D.

4. The incremental benefit/cost ratio is calculated for Alternatives B and D:

Since the incremental benefits are negative, Alternative B should be compared to Alternative C.

Incremental B/C = $702,845/$900,000 = 0.78

Since the incremental BCR is less than one, Alternative B is then ranked 

first.

5. This same process is continued until all of the alternatives have been ranked. 

The ranking results are shown in the following table.

Alternative Countermeasure Benefit/Cost Ratio Alternative Rank

A 3.60 3

B 2.71 1

C 1.89 2

D 2.02 4

Notice although Alternative A had the highest individual project benefit/cost 

ratio, it was ranked third. In addition, it is also important to notice the alternative rankings are the same using the net present value method or the incremental 

benefit/cost analysis.
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Planning: Project Prioritization

An incremental benefit/cost analysis provides a basis of comparison of the benefits of a project for the dollars invested. However to take monetary constraints into 

consideration, optimization methods must be used.

Optimization Methods

Optimization methods take into account certain constraints when prioritizing 

projects. Linear programming, integer programming, and dynamic programming are optimization methods consistent with an incremental benefits/cost 

analysis, but they also account for budget constraints in the development of the 

project list. (These optimization methods are more likely to be incorporated into 

a software package than directly applied and will not be addressed further in 

this manual.) Multi-objective resource allocation is another optimization method 

which incorporates nonmonetary elements, including decision factors not related 

to safety, into the prioritization process.

Software programs are available to assist in the selection and ranking of countermeasures. SafetyAnalyst includes economic appraisal and priority ranking tools. 

The economic appraisal tool calculates the benefit/cost ratio and other metrics for 

a set of countermeasures. The priority ranking tool provides a priority ranking of 

sites and proposed improvement projects based on the benefit and cost estimates 

determined by the economic appraisal tool. The priority-ranking tool also has the 

ability to determine an optimal set of projects to maximize safety benefits.

The prioritization methods presented in this unit are consistent with those in the 

HSM. The HSM provides additional resources and examples of many of these 

methods.

So far this unit has focused on prioritizing hot spot improvements. The next section will address systemic improvements and balancing between the two types.

4.5 Approaches Addressing Current and Future

Safety Problems

As discussed in Unit 2, transportation safety practitioners are focusing more on 

systemic improvements using countermeasures proven to be successful rather 

than on a particular location with an identified problem or “hot spot.” For 

example, some states have identified systemic problems (e.g., high occurrence of 

run-off-road, median crossover crashes, etc.) through crash data analysis, and are 

implementing cable median barrier and rumble strips on roads even if no safety 

problem has been identified at a particular location. These are proven effective 

countermeasures and it is more efficient to add these road improvements while 

addressing infrastructure functions, such as resurfacing, routine maintenance, 

and construction on a systemic basis. These actions may prevent or minimize the 

severity of future crashes even though a road segment or intersection may not 

have yet had a safety problem resulting in crashes.
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Planning: Project Prioritization

Embedding these improvements into state or local policy leaves a lasting legacy 

for safety. A historical example is pavement marking, which at one point was not 

a standard installation on highway projects. Today, a highway agency would not 

consider opening a new section of highway without striping. In at least one state, 

rumble strips have been given this same status. On any overlay project on a major 

highway, rumble strips are a required addition, regardless of the road’s crash 

history. The addition of rumble strips has simply replaced traditional striping as 

the state standard for pavement marking on its highways. The safety treatment 

has been institutionalized, and the benefit of this policy change will outlast any 

specific safety project or program.

Since systemic improvements are intended to be implemented on several miles of 

roadway or at several locations, they do not necessarily have to be prioritized by 

location per se; however, it may be necessary to determine a point of departure 

for implementing these improvements. An agency might consider incorporating 

improvements into maintenance/design practices (e.g., all rural roads projects 

include the safety edge or shoulder rumble strips/stripes during paving projects), 

or at high risk locations that have:

•	 A high exposure – high ADT, lots of curves;

•	 A high-crash frequency;

•	 A high-crash rate; or

•	 A high-crash density.

When developing their HSIP, an additional issue that states will need to address is 

how to balance systemic improvements versus hot spot improvements.

Striking a Balance

No prescriptive method exists for determining the proportion of HSIP projects 

that should be systemic improvements versus hot spot improvements. While the 

majority of fatal crashes tend to occur in rural areas, urban areas comprise a much 

greater proportion of injury and property damage only (PDO) crashes. Due to 

the inherent differences in the two area types, the focus of the improvements will 

vary. Although improvements in rural areas typically focus more on systemic 

improvements, and urban areas typically focus more on hot spot locations, both 

types of improvements can be used in either area type. However, since rural areas 

are associated with a lower crash density (i.e., crashes spread over many miles of 

roads), systemic improvements are more likely to address sites with potential for 

safety improvement that might not be identified through a crash analysis. The 

appropriate balance between systemic and hot spot improvements should be 

determined by each state. For example, some states set aside a portion of their 

HSIP funds to implement systemic improvements.
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Planning: Project Prioritization

4.6 Summary

States may select a combination of project prioritization strategies and typically 

consult with other agencies (e.g., DOT district or regional offices, FHWA Division 

Safety staff) during this process. A balance is needed in the HSIP among hot spot, 

segment/corridor, and systemic improvements to ensure the best mix of safety 

solutions is identified and implemented to reduce fatalities and serious injuries.

Once the prioritized projects are included in the HSIP, the next step is implementation. Implementation is addressed in the next unit.
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Implementation

5.0 Implementation

The previous three units focused on the planning component of the HSIP – identifying the problems, selecting appropriate countermeasures, and prioritizing 

projects. Now it is time to implement the projects and put the planning efforts 

into action.

The first step towards implementing prioritized projects is to identify funding 

sources. Once funding is identified, projects are included in the transportation 

improvement program and move forward into design and construction.

Unit 5 begins with a discussion on several funding topics, including: HSIP 

funding requirements, other safety funding sources, allocation issues, and a discussion on state solutions to funding challenges. This unit also includes a discussion on programming projects into the transportation improvement program 

and concludes with a discussion on the development of evaluation plans.

5.1 HSIP Funding Requirements

Under 23 U.S.C. 148(a)(3), a variety of highway safety improvement projects are 

eligible for HSIP funding on all public roadways. States should identify projects 

or activities that are most likely to reduce the number of and potential for fatalities 

and serious injuries. In most cases, the Federal share is 90 percent except for certain 

safety improvements listed in 23 U.S.C. 120(c) which are funded at 100 percent.

A highway safety improvement project is defined as a project consistent with the 

SHSP that corrects or improves a hazardous road location or feature or addresses 

a highway safety problem. Projects include, but are not limited to, the following:

•	 An intersection safety improvement;

•	 Pavement and shoulder widening (including addition of a passing lane to 

remedy an unsafe condition);

•	 Installation of rumble strips or other warning devices, if the rumble strips 

or other warning devices do not adversely affect the safety or mobility of 

bicyclists, pedestrians, and persons with disabilities;

•	 Installation of a skid-resistant surface at an intersection or other location with 

a high frequency of crashes;

•	 An improvement for pedestrian or bicyclist safety or for the safety of persons 

with disabilities;

•	 Construction of any project for the elimination of hazards at a railway-highway crossing that is eligible for funding under 23 U.S.C. 130, including the 

separation or protection of grades at railway-highway crossings;

•	 Construction of a railway-highway crossing safety feature, including installation of highway-rail grade crossing protective devices;

•	 The conduct of an effective traffic enforcement activity at a railway-highway 

crossing;
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Implementation

•	 Construction of a traffic calming feature;

•	 Elimination of a roadside obstacle or roadside hazard;

•	 Improvement of highway signage and pavement markings;

•	 Installation of a priority control system for emergency vehicles at signalized 

intersections;

•	 Installation of a traffic control or other warning device at a location with highcrash potential;

•	 Transportation safety planning;

•	 Improvement in the collection and analysis of safety data;

•	 Planning integrated interoperable emergency communications equipment, 

operational activities, or traffic enforcement activities (including law 

enforcement assistance) relating to work zone safety;

•	 Installation of guardrails, barriers (including barriers between construction 

work zones and traffic lanes for the safety of road users and workers), and 

crash attenuators;

•	 The addition or retrofitting of structures or other measures to eliminate or 

reduce crashes involving vehicles and wildlife;

•	 Installation and maintenance of signs (including fluorescent yellow-green 

signs) at pedestrian-bicycle crossings and in school zones;

•	 Construction and operational improvements on high-risk rural roads; and

•	 Conducting road safety audits.

Many Federal funding sources are eligible for HSIP projects and programs. The 

next section details these sources and additional behavior-related Federal funds 

which may be available to benefit HSIP programs and projects, especially through 

SHSP partnerships and initiatives.

5.2 Federal Safety Funding Sources

Funding for safety projects comes from a variety of Federal, state, and local 

sources. This section identifies Federal funding resources to help leverage your 

HSIP projects and programs.
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Implementation

SAFETEA-LU established new programs and set-asides, including the following 

funding sources:

•	 High-Risk Rural Roads Program (HRRRP) – The HRRRP is a set-aside of 

the HSIP and supports road safety program efforts through construction and 

operational improvements on high-risk rural roads. The HSIP, including the 

HRRRP element, must consider all public roads.

•	 23 U.S.C. 130: Railway-Highway Grade Crossing Program (RHGCP) – 

SAFETEA‐LU continued the RHGCP as a set-aside program of the HSIP. It is 

focused on reducing the occurrence of crashes at railway-highway crossings. 

States can use the apportioned funds for related data compilation and analysis 

which will allow informed decisions to prioritize railway-highway crossing 

improvements (e.g., crash data, traffic volume and mix, road inventory, etc.). 

States can use not more than 2 percent of funds apportioned to a state for 

the data compilation and analysis. At least half of the funds are to be used 

for the installation of protective devices at railway-highway crossings, with 

special emphasis given to the legislative requirement that all public crossing 

be provided with standard signing.

•	 Safe Routes to School (SRTS) – The program is designed to make walking 

and bicycling to school safe and more appealing; and to facilitate the planning, development, and implementation of projects which improve safety and 

reduce traffic, fuel consumption, and air pollution in the vicinity of schools. 

Each state is apportioned funds based on its relative share of total enrollment 

in primary and middle schools (kindergarten through eighth grade), but no 

state receives less than $1 million annually.

Other Federal-aid funds are eligible to support and leverage the HSIP. States are 

encouraged to fund improvements to safety features routinely provided as part 

of a broader Federal-aid project from the same source as the broader project, as 

per 23 CFR 924. States should address the full scope of their safety needs and 

opportunities on all roadway categories by using other funding sources such as the 

following:

•	 Interstate Maintenance (IM) – Provides funding for resurfacing, restoration, 

rehabilitation, and reconstruction; reconstruction or new construction of 

bridges, interchanges, and over crossings along existing Interstate routes, 

including the acquisition of right-of-way where necessary; capital costs for 

operational, safety, traffic management, or intelligent transportation systems 

(ITS) improvements (operating costs are not eligible for IM funds); and preventive maintenance.

•	 Surface Transportation Program (STP) – Provides funding for a variety of 

transportation purposes. With some exceptions, these funds can be used on 

all public roads except those functionally classified as local or rural minor 

collectors. Highway safety improvement projects, including projects to 

improve signing and pavement markings, may be funded on any public road.
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Implementation

•	 National Highway System (NHS) – Provides funding for resurfacing, 

restoring, rehabilitating, and reconstructing highways on the NHS.

•	 Congestion Mitigation and Air Quality Improvement Program (CMAQ) – 

Provides funding for projects and programs in air quality nonattainment and 

maintenance areas for ozone, carbon monoxide (CO), and particulate matter 

(PM10, PM2.5) which reduce transportation-related emissions.

•	 State Planning and Research (SPR) – The state DOTs must provide data 

that supports the FHWA’s responsibilities to the Congress and to the public, 

including information required for preparing proposed legislation and reports 

to the Congress; and evaluating the extent, performance, condition, and use 

of the Nation’s transportation systems. States have used SPR funds for data 

improvements.

•	 Equity Bonus – Ensures each state receives a specific share of the aggregate 

funding for major highway programs, with every state guaranteed at least 

a specified percentage of that state’s share of contributions to the Highway 

Account of the Highway Trust Fund. The Federal share for the funds programmatically distributed to other programs has the same Federal share as 

those programs.

In addition to the major highway program funding sources, other Federal 

safety resources may assist with HSIP implementation. These grant programs 

are administered by NHTSA and FMCSA and can be used to assist with law 

enforcement efforts and improve traffic record data collection and data systems. 

They include:

•	 23 U.S.C. 154 and 164 Transfer Funds – States in which Federal-aid highway 

funds are transferred based on noncompliance with 23 U.S.C. 154 Open 

Container Requirements or 23 U.S.C. 164 Minimum Penalties for Repeat 

Offenders for Driving While Intoxicated or Under the Influence can use the 

transfer funds on approved projects for alcohol-impaired driving countermeasures or direct the funds to state/local law enforcement to increase 

impaired driving enforcement. States also may elect to use the funds for 

hazard elimination activities eligible under 23 U.S.C. 152.

•	 23 U.S.C. 402: State and Community Highway Safety Grants – Supports a 

full range of highway safety behavioral programs, including alcohol countermeasures, occupant protection, police traffic services (e.g., enforcement), 

emergency medical services, traffic records, motorcycle safety pedestrian and 

bicycle safety, nonconstruction aspects of road safety, and speed enforcement 

and management programs. A minimum of 40 percent of a state’s Section 402 

funds must be expended by local governments, or be used for the benefit 

of local governments. To receive Federal highway safety grant funds, State 

Highway Safety Offices must submit an annual Highway Safety Plan (HSP) to 

the NHTSA.
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Implementation

•	 23 U.S.C. 405: Occupant Protection Incentive Grants – Provides incentive 

grants to encourage states to adopt and implement effective programs to reduce 

highway deaths and injuries resulting from individuals riding unrestrained or 

improperly restrained in motor vehicles.

•	 23 U.S.C. 406: Safety Belt Performance Grants – Encourages states to enact 

and enforce primary safety belt laws. A state may use these grant funds for 

any behavioral or infrastructure safety purpose under Title 23, for any project 

which corrects or improves a hazardous road location or feature, or proactively addresses highway safety problems. However, at least $1 million of each 

state’s allocation must be obligated to behavioral highway safety activities.

•	 23 U.S.C. 408: State Traffic Safety Information System Improvement Grants – 

Encourages states to adopt and implement effective programs to improve the 

timeliness, accuracy, completeness, uniformity, integration, and accessibility 

of state data needed to identify priorities for national, state, and local highway 

and traffic safety programs; to evaluate the effectiveness of efforts to make 

such improvements; to link the state’s data systems, including traffic records, 

with other data systems within the state; and to improve the compatibility of 

the state’s data system with national data systems and data systems of other 

states.

•	 23 U.S.C. 410: Alcohol-Impaired Driving Countermeasures Incentive 

Grants – Provides an incentive to states to implement effective programs to 

reduce traffic safety problems resulting from impaired driving.

•	 SAFETEA-LU Section 2010: Motorcyclist Safety Grants – Provides grants to 

states which adopt and implement effective programs to reduce the number 

of crashes involving motorcyclists. Funds can be used only for motorcycle 

training and motorist awareness programs.

•	 CFR Title 49 Part 350 Commercial Motor Carrier Safety Assistance Program 

(MCSAP) – Provides financial assistance to states to reduce the number and 

severity of crashes and hazardous materials incidents involving commercial 

motor vehicles (CMV). The goal of MCSAP is to reduce CMV-involved 

crashes, fatalities, and injuries through consistent, uniform, and effective CMV 

safety programs.

Many sources of funding are available to resourceful transportation safety professionals. Sometimes understanding the regulations associated with the funding 

can be challenging. The following section addresses the most common funding 

allocation issues and provides examples of what states have done to meet those 

challenges.
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Implementation

5.3 Funding Allocation Issues

The impact of HSIP funding allocations on state programs is not always as clearcut as it may appear from reading the legislation. While the issues are complicated 

and can provide challenges, they can often be overcome through collaboration 

and innovative solutions.

As an example, a flexible funding provision in SAFETEA‐LU allows states to use 

a portion HSIP funds for noninfrastructure projects if the state has adopted a 

strategic highway safety plan and certified all safety infrastructure and railwayhighway crossing needs have been met. The HSIP flexible funding provision 

allows states to transfer up to 10 percent of the HSIP funds to noninfrastructure 

projects identified in the SHSP, including projects to promote public awareness 

and educate the public concerning highway safety matters and projects to enforce 

highway safety laws.

A study focusing on HSIP implementation following SAFETEA‐LU found many 

states could not meet the certification requirement because of ongoing infrastructure needs and concerns about potential legal liability a state could incur 

by certifying all its infrastructure safety needs have been met; however, states 

working closely with their FHWA Division Offices have been able to certify the 

needs have been met and successfully flexed some of their HSIP funds.

State Allocation Issues

A primary allocation issue involves “best use of funds” versus “eligibility.” To 

qualify as an eligible highway safety improvement project under Section 148, a 

project must be described in the state strategic highway safety plan and correct 

or improve a hazardous road location or feature, or address a highway safety 

problem.

Safety engineers and their managers should employ a proactive approach in allocating HSIP funding for projects. The following tactics will help move projects 

forward, while optimizing the use of safety funds:

•	 Use a data-driven process to identify projects for which HSIP funds are 

allocated.

•	 Collaborate with stakeholders, decision-makers, and within the agency to help 

generate internal and external support.

•	 Provide clear and continuous communication to educate decision-makers and 

the public about the importance of safety and the successes achieved.
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Implementation

Making use of these practices also will help avoid potential allocation issues such 

as the following:

•	 HSIP funds are not spent on safety or not spent at all due to management 

decision-making processes.

•	 Management believes all infrastructure projects improve safety, resulting in 

safety funds being used for purposes other than addressing the specific safety 

problems identified through data analysis. Examples include using the safety 

funds to pay for safety elements (e.g., guardrail, lighting, etc.) on projects not 

identified as part of the HSIP.

•	 HSIP funds are used to make up the difference between obligation authority 

and obligation limitation.

State Solutions

Some agency decision-makers have considerable discretion on proportional allocation and eligibility. When a single activity accomplishes multiple purposes (e.g., 

pavement preservation and improved safety), these agencies attribute the cost 

associated with each improvement to the appropriate program. Lack of flexibility 

encourages delivery of only single-purpose projects. The ability to distribute the 

cost of a single project to multiple funding programs is an important asset when 

allocations are not restricted legislatively by eligible expenditures and amounts.

Safety engineers who are successful in making the case to “put the money on 

the road” use the following strategies to expedite the implementation of safety 

projects:

•	 Program safety projects by line items in the STIP, also referred to as “lump sum 

programming,” which allows for flexibility in moving projects forward.

•	 Bundle multiple projects to save on time and resources when letting projects 

for bid.

•	 Mainstream safety elements (e.g., guardrail, rumble strips, edgeline on horizontal curves, etc.) into the overall construction program; hence, the projects 

are separated from the HSIP, which frees up resources.

•	 Expedite a safety project by qualifying for a categorical exclusion (CE), which 

eliminates the need for an environmental assessment or environmental impact 

statement under the National Environmental Policy Act (NEPA). Projects may 

be eligible for a CE if they do not pose a significant impact on the human environment. Examples of such projects are included in 23 CFR 771.

•	 Streamline contract negotiations by utilizing indefinite delivery/indefinite 

quantity (IDIQ) or task order contracts. These contracts are awarded to a 

selected company or companies for a base period of time and provide minimum and maximum limits for services in dollar values.
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Implementation

•	 Use force account construction for small projects. If agencies can document 

a finding of cost-effectiveness, they can use their own workers for the project 

and forego the procurement process.

•	 Integrate safety improvements into resurfacing and restoration projects, 

which may be an effective and efficient method for simultaneously pursuing 

infrastructure and safety goals.

Once funding sources have been identified, the next step in implementing prioritized safety projects is to include them in the statewide transportation 

improvement program.

5.4 Programming Projects

The statewide transportation improvement program (STIP) is the financial programming document for the state. It represents a commitment of the projects 

and programs that will be implemented throughout the state using Federal-aid 

transportation and transit funding.

For most categories of transportation projects, FHWA/FTA funds cannot be used 

unless the project is included in a fiscally constrained STIP. Safety projects funded 

under 23 U.S.C. 104(b)(5) must be included in the STIP.

•	 The STIP must identify reasonably available or committed revenue to match 

the estimated costs of the strategies included in the STIP.

•	 The STIP identifies implementation timing for specific projects and must cover 

a period of at least four years.

•	 The STIP must be fiscally constrained; however, a financial plan is optional.

•	 The FHWA/FTA must approve the STIP before STIP projects can proceed to 

implementation.

In urbanized areas with populations over 50,000, MPOs develop a transportation 

improvement program (TIP) which is the programming document for the metropolitan planning area. The TIP identifies the projects and funding to be 

implemented to reach the vision for the metropolitan area’s transportation system 

and services. The TIP represents a commitment of the projects and programs that 

will be implemented in the metropolitan planning area using local, state, and 

Federal-aid funds. TIPs are incorporated directly, without change, into the STIP.

Amendments to the STIP are common given the frequent changes in engineering 

practices, environmental issues, contracting issues, project readiness, and other 

factors that can require adjustments to project schedules and budgets.

Improvements listed in the STIP may be by location or improvement type. For 

example, several low-cost safety enhancements could be grouped together and 

listed as various safety improvements with an estimated cost and funding source 

identified.
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Implementation

Once projects have been programmed, they can move forward into design and 

construction. However, since the HSIP is a data driven process, it is important to 

first develop an evaluation plan.

5.5 Evaluation Plan Development

Well-designed evaluations reduce agency reliance on professional judgment by 

providing quantitative information on the impacts of highway safety improvements. Evaluation plans should always be considered prior to implementing any 

project or program.

The level of detail will depend upon the scope and complexity of the project or 

program. Following are typical steps in developing the evaluation plan:

•	 Write a statement defining the purpose(s) of the evaluation;

•	 Define the target population (e.g., facility, crash types, etc.);

•	 Clearly state goals, objectives, and performance measures;

•	 Define data needs based upon performance measures;

•	 Determine budget, staff, materials and other resource needs;

•	 Determine what method(s) will be used for collecting the information;

•	 Identify an evaluation timeline and milestones; and

•	 Identify the type of evaluation(s) and analyses to be used (e.g., design and 

combination of quantitative and qualitative analyses).

Rather than being considered an integral part of the HSIP process, evaluations are 

often an after thought. As a result, the opportunity to collect critical baseline data 

may be lost thereby compromising the effectiveness of the evaluation. Agencies 

should consider establishing evaluation guidelines to reinforce their commitment to 

evaluation, provide consistency, and improve the quality of evaluations.

5.6 Summary

Understanding HSIP funding requirements and sources, as well as potential 

allocation issues and solutions will assist in a smooth transition into the HSIP 

implementation process. While incorporating safety into programs and projects 

may be challenging, states are proving it is possible to implement countermeasures that demonstrate safety benefits even with limited resources. Development 

of an evaluation plan, prior to implementing the project, will help agencies 

identify the appropriate data to collect and use in the next phase of the HSIP 

process – evaluation. The evaluation component of the HSIP process is critical as 

it documents the effectiveness of projects and programs and provides feedback to 

improve future project and program planning and implementation.

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Evaluation

6.0 Evaluation

The ultimate measure of success for the HSIP is a reduction in motor vehicle 

related crashes and the resulting fatalities and serious injuries. SAFETEA‐LU 

established the HSIP as a core program and nearly doubled the funds for infrastructure safety. With the increased funding also came a required focus on results, 

which further heightens the importance of the state’s procedures for evaluating 

individual projects and programs, as well as the overall HSIP program.

The goal of evaluation in the HSIP process is for agencies to estimate the effectiveness of highway safety improvements. The evaluation process reveals if the 

overall program has been successful in reaching performance goals established 

in the planning process, including its effectiveness in reducing the number of 

crashes, fatalities, and serious injuries or the potential for crashes. Evaluation 

results should flow back into the various HSIP components to improve future 

planning and implementation, ensure resources are used effectively, and increase 

the effectiveness of future safety improvements.

Unit 6 discusses project and program evaluations. It addresses CMFs, evaluation 

studies, program evaluation methods, and using evaluation feedback to impact 

future safety planning and decision-making. The unit does not detail statistical 

and economic assessment methodologies to determine the effectiveness of HSIP 

projects or programs in achieving their goals; these methodologies are addressed 

in the HSM.

6.1 Project Evaluation

Evaluation is critical to determine if a specific project or group of projects is 

achieving the desired results and to ensure the investments have been worthwhile. The evaluation will provide a quantitative estimate of the effects on safety 

of a specific countermeasure, project, or group of projects. The evaluation results 

can provide valuable information for future planning. For example, the evaluation of a particular countermeasure can be used to determine if it should be used 

at more sites.

The evaluation may include determining the effectiveness of:

•	 A single project at a specific location or site;

•	 A group of similar projects; or

•	 A group of projects to quantify a CMF for a particular countermeasure.

The evaluation must be stated in terms related to the desired results. If the 

goal is to reduce the hazard to pedestrians at an intersection, at least one of the 

performance measures must gauge the affect on pedestrian-related crashes. 
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Evaluation

Agencies should identify actionable and measurable performance goals (e.g., 

reduce the number of fatalities and serious injuries) for the evaluation.

A basic task of project evaluation is to measure conditions, including the performance measures, both before and after a change is made. The effectiveness of 

the change is determined by comparing change in the value of the performance 

measure (e.g., frequency or rate of crashes) with the change which would have been 

expected if the site had not been treated. This approach is appropriate whether one 

is evaluating the application of strategies at a site or subjects (e.g., drivers). The 

challenge is estimating the change in the performance measure without a treatment. It is especially difficult because all other things do not remain equal as 

noted earlier. Since crash rates can vary significantly from year to year, crash 

estimates are susceptible to regression to the mean (RTM).

Developing Crash Modification Factors

In addition to project specific evaluations (single or multiple sites), agencies can 

use the results of evaluation studies to develop state-specific CMFs. By developing their own CMFs, states will have a more accurate indication of the countermeasure effects. Using a CMF developed by another agency does not necessarily 

account for actual driver, roadway, traffic, climate, or other characteristics in a 

state and may over or underestimate the effectiveness of a countermeasure. In 

addition, the methodology used by another agency to develop a CMF may be 

uncertain. Developing state-specific CMFs not only allows a state to evaluate the 

effectiveness of their efforts, it also verifies their efforts are working to improve 

safety.

As previously discussed in Unit 3, a CMF is the ratio of the expected number 

of crashes with a countermeasure to the expected number of crashes without a 

countermeasure.

Where:

CMF = CMF for treatment “t” implemented under conditions “a”;

Et = the expected crash frequency with the implemented treatment; and

Ea = the expected crash frequency under identical conditions but with no 

treatment.

When developing CMFs, it is not recommended to use data from only one site 

because it may overestimate the effectiveness of a change. It is best to use data 

from a minimum of 10 to 20 sites, as it is less biased and will produce a more 

reliable result.

Some states already develop their own CMFs based on past HSIP projects. Other 

states refine CMFs (or crash reduction factors) to account for local road conditions, 

crash severity, injury severity, collision manner, and weather condition. Lastly, 
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Evaluation

other agencies use before/after EB analysis to revise CMFs, and use these factors 

to analyze and prioritize new programs and projects.

This section demonstrates the various evaluation methods that can be used to 

determine the effectiveness of a single project at a specific site or a group of similar 

projects, and also provides information related to calculating CMFs.

Evaluation Methods

The three basic types of evaluations used to measure a safety improvement are:

1. Observational before/after studies;

2. Observational cross-sectional studies; and

3. Experimental before/after studies.

Observational studies are more common in road safety evaluation because they 

consider safety improvements implemented to improve the road system, not 

improvements implemented solely to evaluate their effectiveness. Conversely, 

experimental studies evaluate safety improvements implemented for the purpose 

of measuring their effectiveness.

The remainder of the project evaluation section will outline these three evaluation 

methods.

Observational Before/After Studies

Observational before/after studies are the most common approach used in safety 

effectiveness evaluation. An observational before/after study requires crash data 

and volume data from both before and after a safety improvement. These studies 

can be conducted for any site where improvements have been made; however, 

if a site was selected for an improvement because of an unusually high-crash 

frequency, evaluating this site may introduce the RTM bias.

Simple Before/After Evaluation

An observational before/after study conducted without consideration to nontreatment sites is referred to as a simple before/after evaluation. Figure 6.1 

demonstrates a simple before/after evaluation.

In this figure and the series of figures that follows, the y‐axis represents the value 

of the performance measure (e.g., number of crashes, number of fatalities, etc.), 

and the x‐axis represents the time increment of the performance measure data 

(e.g., monthly, annually, etc.). The period between before and after measurements 

is shown by the vertical line, which can range from instantaneous (e.g., where the 

change may be a law coming into effect), to more than a year (e.g., where a period 

is required for construction and adjustment of traffic).
6-4 Highway Safety Improvement Program Manual

Evaluation

In a simple before/after evaluation, the average value of the performance measure for all treatment sites remains unchanged in the after period, as shown by 

the dashed line. The assumption is the expected value would remain the same 

as in the before period. This simplifying assumption weakens the ability to 

conclusively say the difference measured in the after period was due solely to 

the applied treatment. This approach is not recommended, and has sometimes 

been referred to as a naïve method.

Figure 6.1 Simple Before/After Evaluation

As shown in Figure 6.1, a CMF can be developed using a simple before after 

study by taking the ratio of the observed value of the performance measure in 

the after period with the treatment to the estimated value of the performance 

measure in the after period without the treatment. However, this is not a preferred method for developing CMFs.

Observational before/after evaluations can incorporate nontreatment sites by 

using the EB method or by using a comparison group. These methods are preferred over a simple before/after evaluation.

Observational Before/After Evaluation Using Empirical Bayes Method

Incorporating the Empirical Bayes (EB) method into a before/after study compensates for the RTM bias. The EB method can be used to calculate a site’s 

expected crash frequency “E.” The EB analysis requires AADT and crash data 

Before Period without Treatment

Performance Measure

Bwithout

Observed 

Value Before 

Period without 

Treatment

After Period with Treatment

Awithout

Awith

CMF =

Awith

Awithout

Time

Observed 

Value After Period 

with Treatment

Estimated 

Value After Period 

without Treatment
Highway Safety Improvement Program Manual 6-5

Evaluation

for the treatment site for both before and after the treatment was implemented. 

The SPF, discussed in Unit 2, is incorporated into the EB analysis to determine the 

average crash frequency at similar sites. The sites expected crash frequency can 

be calculated is as follows:

Where: 

μ = SP = The average number of crashes/(mile-year) on similar entities (determined from SPF);

Y = Number of years in evaluation period; and

 = Overdispersion parameter estimated per unit length for segments (calculated in the development of the SPF).

The EB method pulls the crash count towards the mean, accounting for RTM bias. 

Figure 6.2 illustrates how the observed crash frequency and the predicted crash 

frequency are combined to calculate a corrected value, which is the expected crash 

frequency using EB. The expected crash frequency will lie somewhere between 

the observed crash frequency and the predicted crash frequency from the SPF.

The reliability of the data affects the “weight.” The more reliable the data is, the 

more weight will go to the data; conversely, the less reliable the data is, the more 

the weight will go to the average.

The standard deviation of the estimated expected crash frequency can be calculated as follows:

Count of crashes on this entity
6-6 Highway Safety Improvement Program Manual

Evaluation

Figure 6.2 Empirical Bayes Method

The following is an example application of the EB method to estimate the expected 

crash frequency (Hauer, 2001):

Given a 1.1-mile road segment with annual crash counts of 12, 7, and 8 over a 

three-year time period and an ADT of 4,000 vehicles per day (for all three years). 

The safety performance function for similar roads is 0.0224 x ADT0.564 crashes per 

mile-year with an overdispersion parameter  = 3.25 per mile. The expected safety 

of the road is estimated as follows:

AADT

Crash Frequency

Predicted Crash Frequency from SPF

SPF

Observed Crash Frequency

Expected Crash Frequency Using EB
Highway Safety Improvement Program Manual 6-7

Evaluation

1. Calculate the predicted crash frequency for entities of this kind using the SPF:

μ = 0.0224x40000.564 crashes/(mile-year) = 2.41 crashes/(mile-year).

On the 1.1-mile segment in three years we can expect:

2.41 crashes/(mile-year) x (3 years) x (1.1 mile) = 7.95 crashes.

2. Calculate the Weight:

A “weight” is needed for joining crash counts to average count from Step 1.

3. Estimate the expected crash frequency:

E = 0.375 x 2.41 + (1-0.375) x (12 + 7 + 8) = 17.78 crashes in three years.

With a standard deviation:

crashes in three years

The expected number of crashes is 17.78 ± 3.35 crashes in three years or 5.39 ± 

1.01 crashes/(mile-year).

Figure 6.3 illustrates an observational before/after evaluation using the EB method. 

In the before period, the SPF is used to calculate the predicted value without the 

treatment, and then the observed value and the predicted value from the SPF are 

used to calculate an expected value. In the after period, the predicted value with 

the treatment is calculated using the SPF. The expected value in the after period 

without the treatment is then calculated by taking the ratio of the predicted values 

from the SPFs of the after “with” treatment to the before “without” treatment, and 

then multiplying this ratio by the expected value in the before period without the 

treatment. The expected value for the after period without the treatment can then 

be used to calculate a CMF by dividing the observed value in the after period with 

the treatment by this value.

17.78

2.41 3.25

3.35

of on
6-8 Highway Safety Improvement Program Manual

Evaluation

Figure 6.3 Before/After Evaluation Using the EB Method

Before Period without Treatment

Performance Measure

Observed Value 

for Before Period 

without Treatment

After Period with Treatment

SPa

CMF =

A

Ea

Expected Value 

for After Period 

without Treatment

Ea

 = Eb x (Spa/Spb)

Predicted Value 

for After Period 

with Treatment

Time

Observed Value

for After Period with

Treatment

A

Ea

Expected Value 

for Before Period 

without Treatment

Eb

SPb

B

Predicted Value 

for Before Period 

without Treatment

The EB method can be used by agencies to evaluate countermeasures and to calculate CMFs for specific sites as demonstrated in the following example.

Using the same 1.1-mile road segment from the previous example, a countermeasure was implemented to improve safety on the roadway. For the three years 

following the implementation of the countermeasure, the observed crash experience was 4, 7, and 5 crashes per year with an ADT of 4,200 for each year. The 

CMF for this project is calculated as follows:

1. In the previous example, we already calculated the predicted crash frequency 

using the SPF and the expected crash frequency using EB, so the first step is to 

calculate the predicted crash frequency in the after period using the SPF (for 

simplicity purposes, the same SPF is used without adjustments):

μ = 0.0224x42000.564 crashes/(mile-year) = 2.47 crashes/(mile-year).

On the 1.1-mile segment we can expect:

2.47 crashes/(mile-year) x (3 years) x (1.1 mile) = 8.17 crashes.

4. Next we calculate the expected crash frequency in the after period:

SPb

SPa 8.17 17.78

7.95

17.65
Highway Safety Improvement Program Manual 6-9

Evaluation

5. Finally we calculate the CMF:

Observational Before/After Evaluation Using a Comparison Group

Observational before/after studies can incorporate nontreatment sites into the 

evaluation by using a comparison group (or control sites). A comparison group 

typically consists of nontreated sites comparable in traffic volume, geometrics, 

and other site characteristics to the treated sites which do not have the improvement being evaluated. Crash and traffic volume data must be collected for the 

same time period for both the treated sites and the comparison group.

A valid comparison group is essential for conducting an observational before/after 

study using a comparison group. There should be consistency in the rate of 

change in crashes from year to year between the treatment sites and the comparison group, which is generally determined using a statistical test (refer to the HSM 

for detailed information on statistical tests).

The comparison group is used to estimate what would have happened if no 

treatment had been implemented. Figure 6.4 demonstrates the use of a comparison group.

Figure 6.4 Before/After Evaluation Using a Comparison Group

Before Period without Treatment

Performance Measure

Average Observed 

Value Before Period 

without Treatment

After Period with Treatment

Time

Project Sites

Control Sites

CMF =

Awith

Awithout

Awith

Awithout

Average Value for

Control Sites After Period 

without Treatment

Average Observed Value 

After Period with Treatment

17.65

0.91
6-10 Highway Safety Improvement Program Manual

Evaluation

Similar to the previous figures, the period between before and after measurements 

is shown by the vertical line. With a comparison group, similar measurements are 

taken for both the comparison group and the sites being treated in both the before 

and after periods.

The values for the performance measure at the control sites are used to predict what 

would have happened if no change had occurred at a treatment sites. Figure 6.4 

demonstrates how a change at the comparison sites could be estimated by using 

averages for the before and after period. It also shows individual site values may 

be used to perform a regression or trend analysis. Several statistical techniques 

are available to do this, some more “sophisticated” than others (the statistical 

techniques are described in the HSM). The choice of which technique to use is 

dependent upon the resources and time available to complete the evaluation, as 

well as the nature and significance of the treatment.

Figure 6.4 illustrates how a comparison group evaluation can be used to develop 

a CMF. The CMF is developed by dividing the average observed value of the 

performance measure for the project sites in the after period by the average 

observed value for the control sites in the after period.

In some cases, adequate comparison sites will not exist. An example would be what 

occurs as a result of a change in a state or Federal law intended to impact driving 

behavior (e.g., the national maximum speed limit, or lowering of the blood alcohol 

concentration (BAC) limit which defines DUI). In such cases, all sites or subjects 

which can be considered similar come under the category of “treated.” While not 

covered in this Manual, statistical procedures are available for conducting trend 

analyses which may be applied to this situation.

Observational Cross-Sectional Studies

In some cases, evaluations have been performed only after the fact, and data were 

not available for the performance measure during the before period. This might 

be necessary when:

•	 Treatment installation dates are not available;

•	 No crash and traffic volume data are available for the period prior to treatment; or

•	 The evaluation needs to explicitly account for effects of roadway geometrics or 

other related features by creating a CMF function, rather than a single value 

for a CMF.

In these cases, a cross-sectional study is often used. As demonstrated in Figure 6.5, 

the studies only measure the “after” period. Control sites or subjects are chosen 

to compare with the treated site(s). The assumption is the average value of the 

performance measure for all similar sites would be the same, so any difference 

among the averages would be due to the application of the strategy(ies) at the sites, 

or to the subjects. This approach is commonly referred to as a “with and without 

study.”
Highway Safety Improvement Program Manual 6-11

Evaluation

Figure 6.5 Cross-Sectional Evaluation

Before Period without Treatment

Performance Measure

After Period with Treatment

Time

CMF =

Awith

Awithout

Awith

Awithout

Figure 6.5 illustrates how a CMF is developed using an observational crosssectional study. The CMF is the ratio of the estimated value of the performance 

measure for the treatment sites to the estimated value of the performance measure 

for the control sites.

Limitations exist when using a cross-sectional study. This approach limits the 

ability to be confident in the conclusions since trends over time are not taken into 

account. This method does not account for RTM, which threatens the validity of 

the results, especially if the treated sites were selected because they were identified 

as high-hazard locations. In addition, it is usually quite difficult to find control 

sites or subjects about which, or whom, it can be said there is true similarity, for 

the purposes of the evaluation.

Even in a well-designed evaluation, care should be taken to differentiate between 

the documented change and assumptions regarding the causes of the change. The 

stronger the evaluation, the more confident the evaluator can be that the strategies 

employed to improve safety brought about the change. However, limits to the 

confidence one can have exist, both of the type which can be measured statistically 

and due to the inability to account for the myriad of factors which may be present.

Estimated Value for Treatment Sites

After Period with Treatment

Estimated Value for Control Sites 

After Period without Treatment
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Evaluation

Experimental Before/After Studies

Experimental studies are those in which comparable sites with respect to traffic 

volumes and geometric features are randomly assigned to a treatment group or 

nontreatment group. In these studies, crash and traffic volume data is obtained 

for time periods before and after the treatment for the sites in the treatment group. 

Optionally, data also may be collected from sites in the nontreatment group during 

the same time period. One example of an experimental study is evaluation of the 

safety effectiveness of a new signing treatment.

The RTM bias is reduced in an experimental study compared to an observational 

study because of the random assignment of sites to the treatment or nontreatment groups. However, experimental studies are rarely used in highway safety 

due to the reluctance to randomly assign locations for improvements. This 

reluctance is largely due to budget and potential liability issues; however, a negative connotation may also be associated with denying improvements to certain 

populations or locations.

Data Needs for the Evaluation Methods

The necessary data will vary based on the evaluation method chosen. Table 6.1 

summarizes the minimum data requirements for each study type.

Table 6.1 Safety Evaluation Method Data Requirements

Safety Evaluation Method

Data Needs and Inputs

EB 

Before/After

Before/After with

Comparison Group

Cross-Sectional 

Study

Experimental 

Before/After

10 to 20 treatment sites    

10 to 20 comparable 

nontreatment sites  

3 to 5 years of crash and volume 

data from before treatment   

3 to 5 years of crash and volume 

data from after treatment    

SPF for treatment site types  

SPF for nontreatment site types 

Source: Highway Safety Manual, First Edition, Draft 3.1, April 2009.

Although a step-by-step process has not been provided for each of these methods, 

the HSM provides details on how to conduct each of these evaluations, and 

includes examples. Additional references on the techniques to use for highway 

safety evaluation and the EB method are included in the Resources section at the 

end of this document.

Agencies can use the safety effectiveness evaluations presented in this section to 

evaluate an individual project, group of projects, or a particular countermeasure. 

Cumulatively, the results of these evaluations feed into the assessment of the 

overall program.
Highway Safety Improvement Program Manual 6-13

Evaluation

6.2 Program Evaluation

Agencies conduct program-level evaluations to assess the HSIP’s contribution 

in reaching established performance goals. Section 1.7 addressed setting performance goals and more specific performance measures to determine the effectiveness of countermeasures and how changes in the system will affect performance. 

Now that the program has been implemented, it is time to analyze the data to 

determine the overall effectiveness of the HSIP and individual HSIP subprograms.

Assessing Overall HSIP Success

Agencies can utilize several different methods for assessing the overall success of 

their HSIP. States should perform evaluations that are most meaningful to them. 

Several common methods for measuring overall program success include, but 

are not limited to, process output and outcome performance measures, general 

statistics, trend analysis, benefit/cost analysis and safety culture. Each of these 

methods are described in more detail below.

Process Output and Outcome Performance Measures

One basic program evaluation method uses a compilation of output and outcome 

performance measures as a means to measure HSIP progress.

•	 Process performance measures identify the progress in utilizing resources, 

such as the total number of projects, total funding, and related output measures (e.g., the number of traffic signals installed or the number of intersections 

with improved pavement markings, etc.).

•	 Outcome performance measures are focused on the results of the program. 

General statistics (e.g., the number of crashes and crash rates), trend analysis, 

and benefit/cost analysis measure outcomes of performance.

General Statistics

Agencies typically calculate crashes and crash rates (crashes per million vehiclemiles traveled) which are summarized by fatal crashes, injury crashes, property 

damage only crashes and total crashes. As an example, Figure 6.6 summarizes the 

annual fatal crashes by facility type. This summary is useful for determining if the 

program has been successful in reducing fatalities on particular roadway types.
6-14 Highway Safety Improvement Program Manual

Evaluation

Figure 6.6 General Statistics

Rural Rural Rural Rural Rural Rural Urban Urban Urban Urban Urban Urban

Interstate Other Minor 

Arterial

Major

Collector

Minor

Collector

Local 

Road

Interstate Frwy/

Xprwy

Other Minor 

Arterial

Collector Local 

Road

 2004 26 27 34 114 27 126 34 11 46 75 41 77

 2005 24 25 39 111 37 112 26 7 71 68 45 53

 2006 22 37 35 106 41 127 37 11 60 70 35 66

 2007 18 24 41 114 27 181 44 10 58 80 40 65

 2008 26 33 32 96 18 186 52 9 49 44 15 74

0

50

100

150

200

Number of Fatal Crashes Fatal Crashes by Facility Type and Year

Trend Analysis

Another method for measuring overall program success is to identify the crash 

trends for each of the agency’s focus areas. In this case, the established performance goal(s) are compared to the actual number of crashes for the past five-year 

period (although longer is preferred to better identify the trend). As an example, 

if one of the goals is to reduce the fatality rate by 50 percent by 2010, the trend rate 

can be determined by plotting the annual fatality rates as shown in Figure 6.7. The 

slope of the trend line identifies the average annual change in fatality rates.
Highway Safety Improvement Program Manual 6-15

Evaluation

Figure 6.7 Trend Analysis

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

0

0.5

1.0

1.5

2.0

2.5

Fatality Rate

Year

Performance Trend

Fatality Rate/100 

Million VMT Annual Fatality Rates

Trend lines help identify if the actual number of crashes each year is better or worse 

than would be expected if the trend stayed the same from year to year. In Figure 6.7, 

the end year data point is below the trend line, meaning the trend in fatality rates 

is better than would be expected had all other things been equal. Studying crash 

trends provides an indication of overall safety performance. However, since 

it is possible various programs or actions were causing this decline, additional 

evaluation of individual programs within the HSIP are beneficial for identifying 

which aspects of the program had the most impact on reducing fatalities.

Benefit/Cost Analysis

Conducting a benefit/cost analysis of all HSIP-related projects provides another 

indicator of overall HSIP success. To conduct a benefit/cost analysis for the overall 

HSIP program, add the present value of the benefits for all HSIP projects together 

to get an overall benefit and add the present value of all of the project costs to 

get an overall cost. The benefit/cost ratio is calculated by dividing the present 

value of the overall program benefits by the present value of the overall program 

costs (Section 4.2 of this manual discusses benefit/cost analysis in detail). If the 

benefit/cost ratio is greater than one, the benefits of the program have outweighed 

the costs, and it provides some indication the program has shown success in 

improving safety. Typically, program benefit/cost analysis is conducted using 

three years data for both before and after implementation of improvements.
6-16 Highway Safety Improvement Program Manual

Evaluation

Safety Culture

Qualitative measures also may demonstrate the effectiveness and success of the 

HSIP. For example, successful implementation of HSIP-related programs, strategies, and/or treatments may lead to policy or design standard changes. These 

policy and design standard changes result in safety treatments being applied 

across all projects and not just safety-specific projects. This reflects not only a 

policy-level change, but a shift in the safety culture of the agency.

Evaluating Specific Program Effectiveness

States are expected to focus their HSIP resources on their areas of greatest need 

and those with the potential for the highest rate of return on the investment of 

HSIP funds. As the HSIP has evolved, one noteworthy change has been the shift 

in focus towards evaluation of individual HSIP programs. While it is beneficial 

to determine the overall effectiveness of a state’s HSIP in terms of achieving 

statewide performance goals; it is just as important to determine the success of 

specific HSIP-funded programs.

A highway safety program is a group of projects, not necessarily similar in type 

or location, implemented to achieve a common highway safety goal. Examples 

of highway safety programs include an established program administered by a 

Federal agency (e.g., Highway-Rail Grade Crossing Program), a systemic program to address a specific crash type (e.g., lane departures, “drift-off-the-roadway” crashes), and a speed management program combining engineering, 

enforcement, emergency response, and public education strategies designed to 

address a Strategic Highway Safety Plan (SHSP) emphasis area of speed-related 

crashes on selected rural road corridors.

Identifying programs that have the least amount of impact on the performance 

goals can result in subtle changes, such as new or additional treatments to move 

the program toward its intended purpose. Alternatively, implementation of 

successful programs and treatments implemented as part of the HSIP should 

continue.

Measures of program effectiveness include observed changes in the number, rate, 

and severity of traffic crashes resulting from the implementation of the program. 

Program effectiveness is also examined with respect to the benefits derived from 

the program given the cost of implementing the program.

The following examples of program evaluations provide an overview of how an 

agency might conduct an evaluation of each type of highway safety programs. 

Other examples of program evaluation criteria might better demonstrate the success of HSIP-related program.
Highway Safety Improvement Program Manual 6-17

Evaluation

SHSP Emphasis Areas

Similar to determining overall HSIP effectiveness, overall SHSP success can be 

seen in the crash trends for each of the emphasis area performance measures (i.e., 

fatalities and serious injuries, all crashes). Figure 6.8 illustrates a summary of 

statewide fatalities by SHSP emphasis area.

Figure 6.8 SHSP Emphasis Area

0

20

40

60

80

Fatalities Statewide Fatalities by SHSP Emphasis Area

100

120

140

2004 2005 2006 2007 2008

Safety Restraints

Impaired Driving

Aggressive Driving

Drowsy Driving

Younger Drivers

Commercial Vehicles

Pedestrians

Work Zones

Motorcycles

Emphasis Area

HSIP Subprograms

The evaluation process also must assess if the HSIP contributed to reaching the 

specific performance goals aligned with the state’s SHSP. Programs administered under the HSIP often target subsets of the SHSP emphasis areas or specific 

strategies (e.g., cable median barrier program or speed management program). 

States should evaluate the overall effectiveness of these programs.

As an example, if a state has been implementing a median guard cable program 

for the past several years, trends in cross median crashes should be evaluated. An 

effective approach is to compare the cross median fatalities to the miles of guard 

cable installed, as shown in Figure 6.9. This figure demonstrates a decrease in 

cross-median fatalities as the miles of median guard cable installation increased.
6-18 Highway Safety Improvement Program Manual

Evaluation

Figure 6.9 HSIP Subprogram

2000 2001 2002 2003 2004 2005 2006 2007 2008

0

Cross-Median Fatalities

Year

Guard Cable Installation (miles)

Median Guard Cable Program

Guard Cable

Installation (Miles)

5

10

15

20

25

30

35

40

45

50

0

100

200

300

400

500

600

700

Cross-Median 

Fatalities

Source: Chandler (2007).

Systemic Treatments

With the increasing move toward systemic application of countermeasures, program evaluations are effective in determining what may be the best and most 

efficient use of resources to impact statewide fatalities and injuries. For example, 

if a state agency implemented a “Chevron Warning Sign Program” using HSIP 

funds to target horizontal curve crashes on a systemic basis, the agency could 

evaluate the effectiveness of the program based on the reduction in the targeted 

crash type as shown in Figure 6.10. The agency would report on the effectiveness 

of the HSIP-funded “Chevron Warning Sign Program” based on the reduction in 

horizontal curve crashes, and encourage other “off-system” partners to consider 

this treatment for similar crashes in their jurisdiction.
Highway Safety Improvement Program Manual 6-19

Evaluation

Figure 6.10 Systemic Treatment

0

Fatal Crashes

Year

Off-Roadway Fatal Crashes

40

60

80

100

120

Number of 

Off-Roadway 

Fatal Crashes

20

Program Evaluation Challenges

The most common program evaluation challenges are related to data issues and 

available resources for conducting evaluations. Numerous reports indicate states 

are making progress in resolving data issues. Resolving resource issues associated 

with performing evaluations can include training, hiring additional staff, obtaining 

outside assistance, or identifying additional funding to support the oversight and 

conduct of the state’s evaluation efforts. Resolving data and resource issues will 

improve future HSIP planning and decision-making.

To identify some of these challenges, it is beneficial to periodically take a step 

back and conduct an assessment of the HSIP. An assessment allows states to 

review their HSIP, or elements of the program, to identify noteworthy practices 

and/or opportunities for improvement. The FHWA Office of Safety provides an 

HSIP Assessment Toolbox containing tools and resources to aid state DOTs in 

evaluating their HSIP program and processes. The toolbox provides information 

on several options available to conduct program assessments. The state can 

choose a self assessment, program review or peer exchange. States interested in 

obtaining more information about the HSIP Assessment Toolbox should contact 

their FHWA Division Office.

It is important to conduct evaluations to determine the overall effectiveness of the 

HSIP and of individual HSIP programs. However, evaluations can only provide 

benefit if they are used. The next section discusses the importance of using 

evaluation results to impact future actions.

2004 2005 2006 2007 2008
6-20 Highway Safety Improvement Program Manual

Evaluation

6.3 Feedback to Future Planning

Evaluation is a critical element in efforts to improve highway safety. Program 

and project evaluations help agencies determine which countermeasures are 

most effective in saving lives and reducing injuries. Agencies also may identify 

which countermeasures are not as effective as originally expected and decide not 

to use them in the future. The results of all evaluations should be captured in a 

knowledge base to improve future estimates of effectiveness and for consideration in future decision-making and planning.

As mentioned previously, states are conducting more rigorous statistical evaluations and refining CMFs based on crash data from past HSIP projects, using 

before/after EB analysis to revise CMFs, and using these findings to analyze and 

prioritize new programs and projects. At least one state has implemented a program which moves data from completed projects into a historical file that recalculates the CMFs.

Documentation is critical for the evaluation process. States should document key 

findings and issues occurring throughout the implementation process. Identifying potential issues and solutions before they occur can ease the implementation of similar programs and projects in the future.

To aid future planning, a state’s project analysis should:

•	 Summarize assessment data reported during the course of the project;

•	 Analyze both output and outcome performance measures (qualitative and 

quantitative);

•	 Evaluate the degree to which goals and objectives were achieved (using performance measures);

•	 Estimate costs (especially in relation to pre-implementation estimates);

•	 Document anecdotal material which may provide insight for improving future 

projects and implementation efforts; and

•	 Conduct and document debriefing session(s) with persons involved in the 

project, including anecdotal evidence of effectiveness, and recommended 

revisions.

Results of a well designed analysis can be fed back into making better estimates of 

effectiveness for use in planning future strategies.

Project results should be reported back to those who authorized them, and any 

stakeholders, as well as others in management involved in determining future 

projects. Decisions must be made on how to continue or expand the effort, if at 

all. If a program is to be continued or expanded, as in the case of a pilot study, the 

results of its assessment may suggest modifications. In some cases, a decision may 

be needed to remove what has been placed in the highway environment as part 

of the program, due to a negative impact. Even a “permanent” installation (e.g., 

rumble strips) requires a decision regarding investment for future maintenance, if 

its effectiveness is to continue.
Highway Safety Improvement Program Manual 6-21

Evaluation

Evaluation results also can provide justification for changing design standards 

and department policies. For example, countermeasures proven to be effective at 

improving safety based on the evaluation could be incorporated into new roadway design standards and included on all resurfacing projects.

One successful program evaluation strategy states employ is to monitoring 

performance in achieving fatality-reduction goals for specific SHSP emphasis 

areas and reporting those results periodically to state transportation leaders. By 

doing so, the evaluation process can lead to outcomes, such as further studies; 

the implementation of projects; refinement of planning, design, operational or 

maintenance standards; new practices and policies; and new regulations.

6.4 Summary

The HSIP development process is continuously evolving. States work to 

improve data deficiencies through their Traffic Records Coordinating Committee 

(TRCC), which in turn results in more accurate analysis for future programs. 

States make use of countermeasures proven effective based on project and program evaluations, and incorporate lessons learned into future HSIP and SHSP 

planning efforts. In combination, all these collaborative efforts result in moving 

the nation toward our goal of fewer motor vehicle-related fatal and serious injury 

crashes.

Appendices

A-1

Multydiscipline Case Study

Highway Safety Improvement Program Manual

A. Multidisciplinary Case Study

Multidisciplinary approaches can be used to improve safety along designated 

corridors which many states are implementing. In one state, the program began in 1992. 

Since that time, 32 projects have been launched and 7completed. Corridor selection 

criteria include: statistical evidence (established by the state DOT) that a section 

or set of roadways is experiencing a significant crash problem, local-level support, 

and low-cost, near-term solutions.

The goal of the corridor safety program is to reduce fatal and disabling collisions 

on roadways through partnerships with community groups, businesses, engineering, enforcement, education, and emergency services organizations. The 

safety corridor programs are implemented at the community level.

The state’s most noteworthy corridor program encompassed seven miles of 

roadway located within one city’s boundaries. The program’s steering committee 

was comprised of local government agencies, law enforcement officials, emergency 

response personnel, school districts, and other interested parties.

Law Enforcement

Project funding provided increased traffic patrols focused on 

crosswalk safety, driving under the influence (DUI) of alcohol or 

drugs, and red light running. The police department reported 

4,147 contacts, 2,539 citations, 149 suspended or miscellaneous 

criminal violations; 44 DUI arrests, 35 warrant arrests, and 1,667 

verbal warnings. (Note: warnings plus infractions is slightly 

higher than total contacts because some drivers were cited for 

multiple violations).

Traffic Engineering

The engineering team completed several low-cost, near-term improvements to the 

corridor, including installation of signs to mark the corridor, improved timing, 

and upgrades to traffic signals and crosswalks, installation of pedestrian warning 

lights, and bus stop upgrades.

Public Education

During the project, steering committee members educated the public by hosting a 

traffic safety fair, making pedestrian safety presentations to area elementary and 

middle school students, utilizing transit advertising, and distributing pedestrian 

safety information brochures in English, Spanish, and Russian to residents and 

businesses.
A-2 Highway Safety Improvement Program Manual

Multydiscipline Case Study

Results

Results of the two-year effort showed a 

19 percent drop in fatal/disabling and injury 

collisions and a 14 percent decrease in total 

collisions. Rear end collisions, which were 

the leading type of collision in the corridor, 

decreased 10 percent, while drivers failing 

to yield decreased 44 percent.

The 14 percent reduction in total 

collisions on this corridor is nearly 

three times higher than we find on a 

typical safety corridor project.

DOT Program Manager
Highway Safety Improvement Program Manual

Resources

B-1

B. Resources

Constant evaluation of policies, procedures, engineering judgment, and conventional wisdom lead to new methods for improving road safety. Transportation 

safety professionals stay knowledgeable in road safety through research, continuing education, and peer networking. The resources below provide additional 

tools and references for the concepts presented in the unit under which they are 

listed.

B.1 Unit 1

Browse US Code by Title (select Titles 23. Highways). http://www.gpoaccess.

gov/uscode/browse.html.

Code of Federal Regulations, Title 23, Part 924. http://edocket.access.gpo.

gov/2008/pdf/E8-30168.pdf.

Federal Highway Administration (April 5, 2006). 5 Percent Report Guidance: 

http://safety.fhwa.dot.gov/safetealu/guides/guide040506.cfm.

Federal Highway Administration (May 15, 2009). Highway Safety Improvement 

Program Reporting Guidance. http://safety.fhwa.dot.gov/safetealu/guides/

docs/guide051509.pdf.

Federal Highway Administration (2008). Interactive Highway Safety Design Model 

(IHSDM). http://www.tfhrc.gov/safety/ihsdm/ihsdm.html.

Federal Highway Administration Office of Safety web site: http://safety.fhwa.

dot.gov.

Federal Highway Administration (May 5, 2006). Railway Highway Grade Crossing 

Program Reporting Guidance: http://safety.fhwa.dot.gov/safetealu/guides/

guide050506.

Highway Safety Manual web site: http://www.highwaysafetymanual.org/.

SafetyAnalyst web site: http://www.safetyanalyst.org/.

Texas Transportation Institute (2007). Urban Mobility Report, College Station, 

Texas.

Transportation Safety Planning Working Group (September 2008). Transportation 

Planner’s Safety Desk Reference, Companion to NCHRP Report 500. FHWAHEP-07-005.
Highway Safety Improvement Program Manual

Resources

B-2

B.2 Unit 2

American Association of State Highway and Transportation Officials (2004). 

AASHTO Green Book – A Policy on Geometric Design of Highways and Streets, 5th

Edition. https://bookstore.transportation.org/Item_details.aspx?id=109%20.

Council, F.M., et al. (2007). Model Minimum Inventory of Roadway ElementsMMIRE. Federal Highway Administration. McLean, Virginia: FHWA, Report 

FHWA/HRT 07/046. http://www.tfhrc.gov/safety/pubs/07046/index.htm. 

Crash Outcome Data Evaluation System (CODES) web site: http://www.nhtsa.

dot.gov/people/ncsa/codes/.

FARS web site http://www-fars.nhtsa.gov/Main/index.aspx.

Harper, Ogle, J. (2007). NCHRP Synthesis 367: Technologies for Improving Safety 

Data. Transportation Research Board. Washington, D.C. http://onlinepubs.

trb.org/onlinepubs/nchrp/nchrp_syn_367.pdf.

MCMIS web site: http://mcmiscatalog.fmcsa.dot.gov/.

MMUCC website: www.mmucc.us/.

National Highway Traffic Safety Administration. Catalog of State Crash Forms

http://www.nhtsa-tsis.net/crashforms.

National Highway Traffic Safety Administration. State Assessments. http://www.

nhtsa.dot.gov/People/perform/pages/Programs/State_Assessments.htm.

National Highway Traffic Safety Administration (2006). State Traffic Safety 

Information System Improvement Grants. Federal Register Volume 71, No. 22. 

http://www.nhtsa.dot.gov/nhtsa/whatsup/tea21/GrantMan/HTML/408_

FRGuidance_2-2-06.pdf.

National Highway Traffic Safety Administration. Traffic Records Improvement 

Program Reporting System (TRIPRS). http://www.nhtsa-tsis.net/TRIPRS/.

National Model for the Statewide Application of Data Collection and 

Management Technology to Improve Highway Safety web site: http://www.

tracsinfo.us/.

NEMSIS web site: http://www.nemsis.org/.

Smith, R., et al. (2000). Implementation of GIS-Based Highway Safety Analyses: 

Bridging the Gap. FHWA-RD-01-039. Federal Highway Administration. 

McLean, Virginia. http://www.tfhrc.gov/safety/pubs/1039.pdf.

STSI web site: http://www-nrd.nhtsa.dot.gov/departments/nrd30/ncsa/STSI/USA%20WEB%20REPORT.HTM.

Suhrbier, J., et al. (2006). Research Results Digest 306: Identification of LiabilityRelated Impediments to Sharing Section 409 Safety Data among Transportation 

Agencies and Synthesis of Best Practices. Transportation Research Board. http://

onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rrd_306.pdf.
Highway Safety Improvement Program Manual

Resources

B-3

B.3 Unit 3

American Association of State Highway and Transportation Officials (2002). 

Roadside Design Guide, 3rd Edition.

American Traffic Safety Services Association (2006). Low-Cost Local Road Safety 

Solutions. http://www.t2.unh.edu/pubs/lowcostlocalroads.pdf.

Bahar, G., et al. (September 2008). Desktop Reference for Crash Reduction Factors. 

Federal Highway Administration, FHWA-SA-08-011. http://safety.fhwa.dot.

gov/tools/crf/desk_ref_sept2008/desk_ref_sept2008.pdf.

Crash Modification Factors Clearinghouse website: http://www.

cmfclearinghouse.org/.

Federal Highway Administration (2008). Fact Sheets on Highway Provisions: 

Highway Safety Improvement Program (HSIP). http://www.fhwa.dot.

gov/safetealu/factsheets/hsip.htm.

Federal Highway Administration (2007). Fact Sheets for Highway Provisions in the 

SAFETEA-LU. http://www.fhwa.dot.gov/safetealu/factsheets/factsheetssafetea-lu.pdf.

Federal Highway Administration (2008). Fact Sheet on High-Risk Rural Roads, 

http://safety.fhwa.dot.gov/index.cfm.

Federal Highway Administration (2003). Manual on Uniform Traffic Control 

Devices (MUTCD), Washington, D.C. http://mutcd.fhwa.dot.gov/pdfs/2003r

1r2/mutcd2003r1r2complet.pdf.

Federal Highway Administration (2006). Road Safety Audit Guidelines. FHWASA-06-06. http://safety.fhwa.dot.gov/index.cfm.

Federal Highway Administration (2008). Technical Memorandum on Consideration 

and Implementation of Proven Safety Countermeasures. http://safety.fhwa.dot.

gov/index.cfm.

Harkey, D.L., et al. (2004). The Pedestrian Safety Guide and Countermeasure Selection 

System. Federal Highway Administration, FHWA-SA-04-003. http://www.

walkinginfo.org/pedsafe/pedsafe_downloads.cfm.

Hughes, W., et al. (2006). Innovative Intersection Safety Improvement Strategies 

and Management Practices: A Domestic Scan. Federal Highway Administration, 

FHWA-SA-06-016.

Larsen, D.M., Ranck, F.N., and McFadden, J. (October 2006). Low-Cost, 

High-Return. Public Roads. Volume 70, No. 2. http://www.tfhrc.

gov/pubrds/06sep/04.htm.
Highway Safety Improvement Program Manual

Resources

B-4

McGee, H., et al. (2006). Low-Cost Treatments for Horizontal Curve Safety. Federal 

Highway Administration, FHWA-SA-07-002. http://safety.fhwa.dot.

gov/roadway_dept/horicurves/fhwasa07002/.

Nabors, D., et al. (2007). Pedestrian Road Safety Audit Guidelines and Prompt Lists. 

Federal Highway Administration, FHWA-SA-07-007. http://drusilla.hsrc.unc.

edu/cms/downloads/PedRSA.reduced.pdf.

National Highway Traffic Safety Administration. Countermeasures That Work: A 

Highway Safety Countermeasure Guide for State Highway Safety Offices, Fourth 

Edition, DOT HS 811 081. http://www.nhtsa.gov/staticfiles/DOT/NHTSA/

Traffic%20Injury%20Control/Articles/Associated%20Files/811081.pdf.

National Intersection Safety Workshop (2001). Milwaukee, Wisconsin. http://

safety.fhwa.dot.gov/index.cfm.

Ogden, B., et al. (2007). Railroad-Highway Grade Crossing Handbook, Second 

Edition. Federal Highway Administration, FHWA-TS-07-010. http://safety.

fhwa.dot.gov/index.cfm.

PEDSAFE web site: http://www.walkinginfo.org/pedsafe/index.cfm.

Robinson, B., et al. (2000). Roundabouts: An Informational Guide. Federal 

Highway Administration, FHWA-RD-00-067. http://www.tfhrc.

gov/safety/00-0671.pdf.

Transportation Research Board. (2008). NCHRP 17-33: Effectiveness of Behavioral 

Highway Safety Countermeasures. http://www.trb.org/TRBNet/ProjectDisplay.

asp?ProjectID=459.

Transportation Research Board. (2008). NCHRP 622: Effectiveness of 

Behavioral Highway Safety Countermeasures. http://onlinepubs.trb.

org/onlinepubs/nchrp/nchrp_rpt_622.pdf.

Transportation Research Board. (2003 - 2009). NCHRP 500: Implementation 

Guides, Volumes 1-23. http://safety.transportation.org/guides.aspx.

Wilson, E. (2003). NCHRP Synthesis 321: Roadway Safety Tools for Local Agencies. 

Transportation Research Board, Washington, D.C. http://onlinepubs.trb.

org/Onlinepubs/nchrp/nchrp_syn_321.pdf.

B.4 Unit 4

Council, F.M., et al. (October 2005). Crash Cost Estimates by Maximum 

Police-Reported Injury Severity Within Selected Crash Geometries. Federal 

Highway Administration, FHWA-HRT-05-051. http://www.tfhrc.

gov/safety/pubs/05051/05051.pdf.

NSC web site: http://www.nsc.org/news_resources/injury_and_death_statistics

/Pages/EstimatingtheCostsofUnintentionalInjuries.aspx.
Highway Safety Improvement Program Manual

Resources

B-5

B.5 Unit 5

Federal Highway Administration. A Guide to Federal-Aid Programs and Projects. 

http://www.fhwa.dot.gov/Federalaid/projects.cfm.

Federal Highway Administration. Fact Sheets on the Highway Provisions. http://

www.fhwa.dot.gov/safetealu/factsheets.htm.

Governors Highway Safety Association. State Highway Safety Grant Programs. 

http://www.ghsa.org/html/stateinfo/grants/.

Mahoney, K., et al. (December 2006). Good Practices: Incorporating Safety into 

Resurfacing and Restoration Projects. Federal Highway Administration, FHWASA-07-001. http://safety.fhwa.dot.gov/index.cfm.

U.S. Department of Transportation. Federal Funding Sources for Traffic Safety Data 

Activities. Traffic Records Coordinating Committee. http://www.dottrcc.

gov/pages/funding.htm.

B.6 Unit 6

Hauer, E (1997). Observational Before/After Studies in Road Safety, Pergamon Press.

Cook, T.D. and Campbell, D.T. (1979). Quasi-Experimentation, Rand McNally 

College Publishing Company.

Council, F.M., et al. (February 1980). Accident Research Manual. Washington, 

D.C.: Federal Highway Administration, Report FHWA/RD-80/016. http://

www.hsrc.unc.edu/research_library/PDFs/Accident80.ocr.pdf.

Federal Highway Administration (November 1981). Highway Safety Evaluation, 

FHWA-TS-81-219. http://www.fhwa.dot.gov/tfhrc/safety/pubs/81219/

intro.htm.

Hauer et al. (2001). Estimating Safety by the Empirical Bayes Method: A Tutorial.

http://ca.geocities.com/hauer@rogers.com/Pubs/TRBpaper.pdf.

National Highway Traffic Safety Administration (December 2008). The Art of 

Appropriate Evaluation, DOT HS 811 047. http://www.nhtsa.dot.gov/people/

injury/research/ArtofAppEvWeb/index.html.

Powers, M., et al. (2004). Before/After Crash Analysis: A Primer for Using the 

Empirical Bayes Method. Montana Department of Transportation. http://www.

mdt.mt.gov/research/docs/research_proj/crash_analysis/tutorial.pdf.

Thomas D. Cook and Donald T. Campbell (1979). Quasi-Experimentation, Rand 

McNally College Publishing Company.

Highway Safety Improvement Program Manual

The Haddon Matrix

C-1

C. The Haddon Matrix

The Haddon Matrix is commonly used to approach safety analysis at a site in 

a systematic fashion. Developed in 1980 by William Haddon, the Matrix is a 

two-dimensional model which applies basic principles of public health to motor 

vehicle-related injuries. The first dimension is the phase of injury divided into precrash, crash, and post-crash. The second dimension is the four factors of injury: 

human, vehicle/equipment, physical environment, and socioeconomic.

The Haddon Matrix is completed through the evaluation of sites and/or crash 

details associated with a site or sites. When completed, it provides insight into 

the range of possible safety issues and concerns as well as possible solutions. This 

model is an extremely effective tool for not only identifying where and when to 

implement traffic safety countermeasures, but also planning crash-related data 

collection, and identifying organizations and agencies for collaboration efforts.

The value of the Haddon Matrix is each cell represents a different area in which 

interventions can be identified and implemented for transportation system safety 

improvement. The Haddon Matrix is completed upon examination of crashes for 

a set of locations or single location under study, and is used to inform the road 

safety analyst.

For example, the Haddon Matrix below might be constructed from a set of 

crashes in an urban area. The top-left cell (pre-crash human) identifies potential 

modifications to driver behavior that may reduce the likelihood or the severity 

of a collision. As shown in the example table, it is poor vision or reaction time, 

alcohol consumption, speeding, and risk taking. The matrix in its entirety provides a range of potential issues that can be addressed through a variety of 

countermeasures, including education, enforcement, engineering, and emergency 

response solutions (the 4Es of Safety).

Table C.1 Haddon Matrix

Human

Vehicle/

Equipment Physical Environment Socioeconomic

Pre-Crash Poor vision or reaction 

time, alcohol, speeding, 

risk taking

Failed brakes, missing 

lights, lack of warning 

systems

Narrow shoulders, 

ill-timed signals

Cultural norms permitting speeding, red light 

running, DUI

Crash Failure to use occupant 

restraints

Malfunctioning safety 

belts, poorly engineered 

air bags

Poorly designed guardrailsLack of vehicle design 

regulations 

Post-Crash High susceptibility, 

alcohol

Poorly designed fuel 

tanks

Poor emergency communication systemsLack of support for EMS 

and trauma systems

Highway Safety Improvement Program Manual

Glossary

D-1

D. Glossary

3R is a common term which refers to resurfacing, restoration, and rehabilitation 

projects.

4Es of Safety refers to the four major categories for addressing road safety; 

Engineering, Enforcement, Education, and Emergency Medical Services, which 

have typically been used either as measures to correct existing road safety issues 

or as crash prevention strategies.

Analysis period refers to a defined period of time for analysis. Crash experience 

can vary at a location from year to year; therefore, it is important to use more than 

one year of data for the analysis; generally a minimum of three years is used.

Benefit/cost analysis is a quantitative measure commonly used in prioritizing 

projects and countermeasures which compares all of the benefits associated with 

a countermeasure (e.g., crash reduction, etc.), expressed in monetary terms, to the 

cost of implementing the countermeasure.

Crash Modification Factors (CMF) is a multiplicative factor used to compute the 

expected number of crashes after implementing a given countermeasure at a specific site.

Coefficient of variation is a normalized measure of dispersion of a probability 

distribution. It is the ratio of the standard deviation to the mean value.

Cost-effectiveness is the amount of money invested divided by the benefit in 

crash reduction.

Crash Reduction Factors (CRF) is the percentage crash reduction that might be 

expected after implementing a given countermeasure

Data accessibility is a measure of how easy is it to retrieve and manipulate data in 

a system, in particular by those entities that are not the data system owner.

Data accuracy is a measure of how reliable the data are, and if the data correctly 

represent an occurrence.

Data completeness is a measure of missing information, including missing 

variables on the individual crash forms or underreporting of crashes.

Data integration is a measure of how well various systems are connected or 

linked.

Data timeliness is a measure of how quickly an event is available within a data 

system.

Data uniformity is a measure of how consistent information is coded in the data 

system, and/or how well it meets accepted data standards.
Highway Safety Improvement Program Manual

Glossary

D-2

General Estimates System (GES) is a database of a national representative sample of police reported motor vehicle crashes of all types. GES is directed by the 

National Center for Statistics and Analysis, which is a component of Research and 

Development in NHTSA.

Highway Performance Monitoring System (HPMS) is a national-level highway 

information system that includes data on the extent, condition, performance, use, 

and operating characteristics of the Nation’s highways.

Interactive Highway Safety Design Model (IHSDM) is a software analysis 

package that assists engineers with evaluating safety for two-lane rural highway 

design alternatives.

“KABCO” Injury Scale is frequently used by law enforcement for classifying 

injuries and also can be used for establishing crash costs. (K – Fatal; A – 

Incapacitating injury; B – Nonincapacitating injury; C – Possible injury; and O – 

No injury.)

Overdispersion is a systematic variation in the number of accidents, whenever 

the variance exceeds the mean. The amount of overdispersion of a data set is 

described in terms of the overdispersion parameter.

Net Present Value (NPV) is a method which expresses the difference between the 

discounted costs and discounted benefits of a safety improvement project. The 

costs and benefits are “discounted” meaning they have been converted to a present 

value using a discount rate. NPV also is referred to as net present worth (NPW).

Nominal safety refers to whether or not a design or design element meets minimum design criteria based on national or state standards and guidance documents 

such as the AASHTO Green Book and the MUTCD. Nominal safety does not 

characterize the actual or expected safety of a roadway.

Quantitative analysis typically involves the identification and comparison of cost, 

effectiveness, and resilience (how long it is effective) for each countermeasure or 

program based on the latest research.

Regression to the Mean (RTM) describes a situation in which crash rates are 

artificially high during the before period and would have been reduced even 

without an improvement to the site. Variations at a site are usually due to the 

normal randomness of crash occurrence. Because of random variation, the extreme 

cases chosen in one period are very likely to experience lower crash frequencies in 

the next period – the highest get lower and the lowest get higher.

SafetyAnalyst is a set of software tools which utilizes SPFs for evaluating roadway locations and contains over 100 SPFs for various roadway segment types. 

SafetyAnalyst includes modules for identifying locations for potential safety 

improvement, diagnosis and countermeasure selection, economic appraisal and 

priority ranking, and evaluation of implemented improvements.
Highway Safety Improvement Program Manual

Glossary

D-3

Safety Performance Functions (SPF) are the change in the expected number of 

crashes as average daily traffic (ADT) or some other exposure measure increases, 

while all other factors affecting crash occurrence are held constant.

Statewide Transportation Improvement Program (STIP) is the financial programming document for the state representing a commitment of the projects 

and programs that will be implemented throughout the state using Federal-aid 

transportation and transit funding.

Substantive safety refers to the actual or expected safety on a roadway.

Transportation Improvement Program (TIP) is the programming document for 

metropolitan planning areas (urbanized areas with populations over 50,000) that 

identifies the projects and funding to be implemented to reach the vision for the 

metropolitan areas’ transportation system and services.

Highway Safety Improvement Program Manual E-1

Reference

E. References

American Automobile Association (March 2008). Crashes versus Congestion: 

What’s the Cost to Society? Washington, D.C. http://www.aaanewsroom.net 

/Assets/Files/20083591910.CrashesVsCongestionFullReport2.28.08.pdf.

American Association of State Highway and Transportation Officials (2003). 

AASHTO Red Book: A Manual on User Benefit Analysis for Highways. Second 

Edition.

Blincoe, et al. (2002). Economic Impact of Motor Vehicle Crashes, 2000. National 

Highway Transportation Safety Administration, DOT HS 809 446.

Bonneson, J., et al. (2005). Interim Roadway Safety Design Workbook. Texas 

Transportation Institute. Project Status Report 0-4703-1.

CDC, National Center for Injury Prevention and Control, Office of Statistics 

and Programming. Web-based Injury Statistics Query and Reporting System 

(WISQARS). http://www.cdc.gov/ncipc/wisqars/.

Chandler, B. (2007). Eliminating Cross-Median Fatalities: Statewide Installation 

of Median Cable Barrier in Missouri. TR News, No. 248, pages 29-31, 

Transportation Research Board, Washington, D.C.

Federal Highway Administration (January 7, 2005). Memorandum to Division 

Administrators, ACTION: Safety in Project Development. HSA-10, Washington, 

D.C.

Harkey, D.L., et al. (2008). NCHRP 617: Accident Modification Factors for 

Traffic Engineering and ITS Improvements. Transportation Research Board. 

Washington, D.C. http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_

rpt_617.pdf.

Hauer, E., et al. (2001). Estimating Safety by the Empirical Bayes Method: A 

Tutorial. http://pubsindex.trb.org/document/view/default.asp?lbid=726704.

Hauer, E., et al. (1997). Observational Before/After Studies in Road Safety, Pergamon 

Press, the United Kingdom.

National Cooperative Highway Research Program (April 2009). NCHRP Project 

17‐38: Highway Safety Manual – 1st Edition. Transportation Research Board. 

Draft 3.1.

NSW Roads and Traffic Authority. (1996). Road Whys speeding module presenter’s booklet Regret is such a short distance.

Office of the Secretary of Transportation (March 18, 2009). Memorandum to 

Secretarial Officers and Modal Administrators, Treatment of the Economic Value 

of a Statistical Life in Departmental Analyses – 2009 Annual Revision, Washington, 

D.C. http://regs.dot.gov/docs/VSL%20Guidance%202008%202009rev.pdf.


Federal Highway Administration

Office of Safety

1200 New Jersey Avenue SE

Washington, DC 20590

http://safety.fhwa.dot.gov/hsip

Publication # FHWA-SA-09-029