CRASH MODIFICATION FACTORS IN PRACTICE

Quantifying Safety in the Roadway 

Safety Management Process

The Quantifying Safety in the Roadway Safety Management Process guide 

describes and illustrates opportunities to incorporate the latest tools 

and techniques to quantify safety in the roadway safety management 

process. The target audience includes safety program managers and 

safety analysts. The purpose of this guide is to help raise awareness of 

opportunities to apply crash modification factors (CMFs) in the roadway 

safety management process. The objectives are to 1) identify 

opportunities to apply CMFs in the various steps of the safety 

management process, 2) describe the process of applying CMFs to 

quantify safety, and 3) explain potential challenges related to the 

application of CMFs and opportunities to overcome those challenges. 

Readers will better understand the purpose of CMFs and how they 

can be applied in the roadway safety management process.

INTRODUCTION

Historically, it has been very challenging to quantify safety explicitly along 

with other factors such as design, operational, and environmental impacts 

during the project development process. Instead, safety has been 

assumed to be inherent in design policies and practices. 

Tools have been available for several years to quantify the operational 

and environmental impacts of design. Recently, similar tools have 

been developed to quantify the safety impacts of design decisions, 

but the tools and resources are relatively new. There is a need to raise 

awareness of the current level of road safety knowledge and the 

tools that are available to quantify safety in the project development 

process. Quantifying safety will help decision-makers to better 

understand the safety impacts of design decisions and allow 

safety impacts to be considered in conjunction with other factors 

in the project development process. It is necessary for 

professionals involved in the project development process to 

understand the importance of quantifying safety and apply 

appropriate methods or seek assistance to do so. 

Crash modification factors (CMFs) are one tool that state and local 

transportation agencies are applying to better understand the 

safety impacts of their decisions. CMFs are a measure of the 

safety effectiveness of a particular treatment or design element. 

When applied correctly, CMFs can be used to estimate the safety 

effectiveness of a given treatment or compare the relative safety 

effectiveness of multiple treatments and determine the potential 

benefit for a benefit-cost analysis. Readers can refer to the 

Introduction to Crash Modification Factors (1) for more 

information on CMFs and how they are applied.

CMFs can be applied in the roadway safety management 

process to help select countermeasures and prioritize projects 

through an economic evaluation (e.g., benefit-cost analysis). 

Read more for an overview of CMFs in the roadway safety 

Crash modification factors 

(CMFs) support a number 

of safety-related activities 

in the project development 

process. The CMFs in 

Practice series includes 

five separate guides that 

identify opportunities to 

consider and quantify safety 

in specific activities, including 

roadway safety management 

processes, road safety audits, 

design decisions and 

exceptions, development and 

analysis of alternatives, and 

value engineering. The purpose 

of the CMFs in Practice series is 

to illustrate the value of CMFs in 

these five activities and 

demonstrate practical 

application of CMFs.

Federal Highway Administration, Office of Safety, 

1200 New Jersey Avenue SE, Washington, DC 20590
CONTENTS

1 Introduction

2 Overview of CMFs in the 

Roadway Safety 

Management Process

4 Application of CMFs in the 

Roadway Safety 

Management Process

7 Case Study

13 Overcoming Potential 

Challenges

16 References

2

management process or skip to the step-by-step process for applying CMFs. 

Examples are provided to illustrate how CMFs can be applied and a case study 

illustrates how CMFs have been applied in the roadway safety management 

process. Finally, potential challenges are presented along with opportunities to 

overcome these common application challenges. 

OVERVIEW OF CMFS IN THE ROADWAY SAFETY MANAGEMENT PROCESS

The roadway safety management process is a six-step process as shown in Figure 

1 and outlined in the Highway Safety Manual (HSM) (2). 

Network

Screening

Safety 

Effectiveness 

Evaluation

Diagnosis

Economic

Appraisal

Countermeasure

Selection

Project

Prioritization

Figure 1. HSM 6-Step Roadway Safety Management Process

The Highway Safety Improvement Program (HSIP) Manual (3) identifies 

this process as planning, implementation, and evaluation, 

where planning covers problem identification, countermeasure 

identification, and project prioritization. In either case, CMFs can 

play a role in the countermeasure selection and project 

prioritization components of the roadway safety management 

process. While not directly applicable to the application

of CMFs, one can develop new CMFs in the safety 

effectiveness evaluation component of the process. A brief 

summary of these three opportunities follows. 

Countermeasure Selection

In this step, potential countermeasures are developed to 

address the contributing factors identified in the safety 

diagnosis. Physical, financial, and political constraints need 

to be taken into consideration during this task as well as the 

potential impacts on safety, mobility, and the environment. 

CMFs can provide valuable information to assist in the 

countermeasure selection process, particularly the 

quantification of safety impacts. 

With respect to countermeasure selection, CMFs can 

play a valuable role by indicating which candidate 

treatments are associated with the greatest expected 
3

reductions in crashes. From the diagnosis step, a list of contributing factors is generated. The first step in 

the countermeasure selection process is to identify a list of potential countermeasures to 

address the specific contributing factors. Contributing factors and related treatments are identified in 

the NCHRP Report 500 Series (4) for several specific topics.

CMFs can help to reduce the list of potential treatments to more manageable levels by grading the treatments 

in terms of expected safety effectiveness. For example, those treatments with CMFs less than 1.0 could be 

carried forward for further evaluation, while treatments with CMFs greater than or equal to 1.0 may be eliminated 

from further consideration as they are likely to result in an increase in crashes. Of course, there may also be 

physical, financial, and political constraints, but CMFs are a useful tool for sifting through the initial list of potential 

treatments. 

The CMF alone is not always enough information to immediately include or discount a treatment from further 

consideration. CMFs are developed using various study designs, sample sizes, and study periods. As such, there 

is a wide range in the quality and reliability of CMFs. The standard error of a CMF should be considered as it 

indicates the potential variability in the estimate. The standard error can be used to define a confidence interval 

which indicates the range of values that contain the true treatment effect with a given level of confidence. A CMF 

confidence interval which includes 1.0 suggests that a treatment is not highly effective and may be completely 

ineffective. Consequently, it would be reasonable to give less consideration to treatments for which the 

associated CMF has a confidence interval that includes 1.0. Furthermore, it may be prudent in some situations 

to give greater consideration to treatments with smaller confidence intervals because of the greater level of 

certainty in the results. 

Economic Appraisal

The economic appraisal step of the highway safety management process seeks to compare the benefits of 

safety improvements to the costs of implementing those improvements. There are two main types of economic 

appraisals: benefit-cost analysis and cost-effectiveness analysis. In benefit-cost analyses, the safety benefits of 

potential treatments are translated into monetary values and then compared to treatment costs. In contrast, 

a cost-effectiveness analysis does not convert safety benefits into monetary terms. Instead, the cumulative 

treatment costs are divided by the estimated number of reduced crashes to approximate the cost per crash 

reduced. CMFs may be utilized in either type of analysis to estimate the reduction in crashes. 

With respect to the economic appraisal, the main function of CMFs is to help estimate the benefits of proposed 

treatments as part of benefit-cost or cost-effectiveness analyses. Depending on which type of economic appraisal 

is conducted, benefits may be quantified in different forms. In a benefit-cost analysis, benefits are measured 

in terms of monetary values. Specifically, estimated crash reductions are converted to monetary values using 

average crash costs. In a cost-effectiveness analysis, benefits are quantified simply as the estimated reduction 

in crashes. In either case, CMFs are used to estimate the change in crash frequency associated with proposed 

treatments. 

Safety Effectiveness Evaluation

The safety effectiveness evaluation step of the roadway safety management process assesses how an 

implemented safety treatment or set of safety treatments affected the frequency and severity of crashes. During 

this step, evaluations of individual treatments or combinations of treatments can be carried out based on various 

performance measures. It is often possible to develop CMFs in this step of the process. If the goal is to develop 

CMFs, there are numerous study designs that can be utilized which have varying levels of complexity and quality. 

More information about the various approaches to develop CMFs can be found in A Guide to Developing Quality 

Crash Modification Factors (5) and Recommended Protocols for Developing Crash Modification Factors (6). 

This step is intended to provide quantitative indicators of effectiveness in order to guide future highway safety 

decision-making and policy development. 
4

APPLICATION OF CMFS IN THE ROADWAY SAFETY MANAGEMENT PROCESS

This section presents the step-by-step process for applying CMFs in the roadway 

safety management process. Specifically, it covers the two related areas discussed 

in the overview, countermeasure selection and economic appraisal.

Countermeasure Selection

CMFs can be used to help reduce the list of potential treatments in the 

countermeasure selection process. The following steps can be applied to the 

entire list of countermeasures, but it may be more useful to complete the 

following steps for each specific contributing factor or groups of target crashes 

identified in the diagnosis phase of the roadway safety management process.

Step 1: Identify Applicable CMFs and Standard Errors for the List of Potential 

Countermeasures

CMFs are first identified for each potential countermeasure. As discussed in 

the Introduction to Crash Modification Factors (1), the CMF selection process 

involves several considerations including the availability of related CMFs, the 

applicability of available CMFs, and the quality of applicable CMFs. The CMF 

Clearinghouse (7) contains more than 3,000 CMFs for various design and 

operational features and also provides detailed information for each CMF 

to help users identify applicable scenarios and the related quality of the 

CMF. The most applicable CMF should be listed for each countermeasure 

along with the standard error (if available) and applicable crash types 

and severities.

Step 2: Apply Screening Techniques and Engineering Judgment to 

Reduce the List

There are several potential screens to reduce the list of 

countermeasures. In addition to physical, financial, and political 

constraints, the following CMF screens may be applied:

1. Absolute value of the CMF: Countermeasures are eliminated if the 

associated CMF is greater than a given threshold. For example, 

those treatments with a CMF greater than or equal to 1.0 may be 

eliminated as they are likely to be counterproductive.

2. Relative value of the CMF: Countermeasures are eliminated based 

on the relative values of the associated CMFs. For example, those 

treatments with the greatest CMFs (i.e., least effective treatments) 

are eliminated. Note that countermeasures should only be 

compared if the respective CMFs apply to the same crash 

conditions (i.e., crash type and severity). For example, it would 

be appropriate to compare multiple countermeasures if the 

associated CMFs are related to angle crashes of all severities. 

If the applicable CMFs are related to different crash types and 

severities, it is not appropriate to make direct comparisons 

without further analysis (e.g., benefit-cost analysis).

3. Confidence interval: Countermeasures are eliminated based 

on the absolute or relative confidence in the associated 

CMF. For example, treatments could be eliminated if the 

confidence interval for the associated CMF includes 1.0 

as this indicates that the treatment could be ineffective or 

produce a negative effect. The confidence interval is 

computed as follows:
Note that the 

confidence 

interval can only 

be computed for 

those CMFs with a 

standard error.

Observed crashes are 

based on reported crashes 

for the site of interest. 

Predicted crashes are based 

on estimates from a safety 

performance function. 

Expected crashes are based 

on the Empirical Bayes method, 

which combines the observed 

and predicted crashes.

The annual crashes should be 

estimated for each year over the 

service life and also correspond 

with the specific crash type and 

severity for which the CMF is 

applicable. If the CMF applies to 

total crashes, then Step 2 should 

estimate the total annual crashes 

without treatment. If the CMF applies 

to a specific crash type or severity, the 

annual crashes should be computed 

for that crash type or severity.

5

Confidence Interval = CMF ± [Cumulative Probability*Standard Error]

The following table gives the cumulative probability for common confidence intervals.

Confidence Interval Cumulative Probability

99% 2.576

95% 1.980

90% 1.645

This process is highly dependent on engineering judgment, but supported by 

CMFs. While it may be desirable to reduce the list of potential countermeasures, 

it is important not to eliminate treatments prematurely. The economic 

appraisal can be used to further compare the potential effectiveness of 

countermeasures, incorporating the relative costs. 

Economic Appraisal

Economic appraisal is a more formal application of CMFs in the roadway 

safety management process. Again, the economic appraisal may be based 

on a benefit-cost or cost-effectiveness analysis. The following steps outline 

the two approaches and the process would be repeated for each potential 

countermeasure.

Step 1: Estimate Cost of Treatment

The treatment cost includes the installation and annual maintenance 

costs over the life of the project (e.g., repainting, replacing parts, 

and repairing hits). The expected service life should also be identified. 

Step 2: Estimate Annual Crashes WITHOUT Treatment

The annual crashes without treatment have to be estimated before 

applying CMFs. The HSM presents several methods for estimating 

the future safety performance of a roadway or intersection (2). The 

most simplistic method to estimate crashes without treatment is to 

compute the long-term average (i.e., 5+ years) based on observed

crash frequency before treatment. In this method, it is assumed 

that the observed crash history before treatment will represent the 

future safety performance in the absence of any changes. Safety 

performance functions (SPFs) are another method to estimate 

crashes without treatment. SPFs provide an estimate of the 

predicted annual crashes for the site of interest based on the 

crash history of other similar sites. The Empirical Bayes method, 

described in the HSM, is a rigorous method for estimating the 

expected crashes without treatment as it combines the observed 

crash history from the site of interest with predicted crashes from 

a SPF. Drawbacks and opportunities to overcome potential 

challenges related to these methods are discussed in 

Estimating Annual Crashes without Treatment in the 

Overcoming Potential Challenges section.

Step 3: Estimate Annual Crashes WITH Treatment

The CMF is multiplied by the estimated annual crashes 

without treatment from Step 2 to estimate the annual crashes

with treatment for each year of the service life.
6

Step 4: Estimate Annual Reduction in Crashes

The estimated annual reduction in crashes is computed as the estimated annual crashes without treatment 

minus the estimated annual crashes with treatment for each year of the service life. 

At this point, there is enough information to conduct a cost-effectiveness analysis. The cost-effectiveness is simply 

the treatment cost divided by the estimated reduction in crashes. The result is a cost per crash reduced. For a 

benefit-cost analysis, it is necessary to complete one more step (Step 5).

Step 5: Convert Estimated Annual Crash Reduction to Monetary Benefit

The estimated annual crash reduction is converted to a monetary benefit by multiplying the estimated annual 

crash reduction by the appropriate average crash cost for each year of the service life. Many agencies have 

developed or adopted their own crash costs, but national estimates are also available such as those provided 

by FHWA. The following table shows the comprehensive crash costs, in 2001 dollars, by severity level from the HSM 

(2), which are based on the costs from the FHWA report, Crash Cost Estimates by Maximum Police-Reported Injury 

Severity within Selected Crash Geometries (8). These costs should be adjusted by the gross domestic product 

(GDP) to better reflect the actual costs associated with the analysis period. The FHWA crash cost report also 

provides crash costs disaggregated by crash type, severity, and posted speed (8).

Crash Severity Estimated Cost

Fatal (K) $4,008,900

Disabling Injury (A) $216,000

Evident Injury (B) $79,000

Possible Injury (C) $44,900

Property Damage Only (PDO) $7,400

It is necessary to adjust the annual monetary benefits to a present dollar value. This can be accomplished by 

multiplying the computed monetary benefit in a given year by its present value factor. The present value factor is 

computed from the following equation.

Present Value Factor = ------------------------------------------------------------- 1

(1 + Discount Rate)Year of Service Life

It should be noted that the discount rate is dependent on the service life and may change over time. Discount 

rates typically range between three and seven percent. The current discount rate can be obtained from the 

Office of Management and Budget (http://www.whitehouse.gov/omb/circulars_a094/a94_appx-c) or agencies 

may have a standard discount rate.

At this point, the estimated annual benefit (i.e., cost savings) can be summed and divided by the treatment cost 

to estimate the benefit-cost ratio.

Example: As part of the network screening process, a mid-block pedestrian crossing was selected for further 

investigation. The crossing is located on an urban, four-lane, divided arterial with a posted speed of 45 mi/h. 

Based on a site diagnosis, it was determined that a marked crosswalk alone was inappropriate given the posted

speed and number of lanes. Several potential countermeasures were identified during the countermeasure 

selection process, including a pedestrian hybrid beacon. The following example presents a benefit-cost analysis 

for a pedestrian hybrid beacon that is being considered in the economic appraisal. A CMF for fatal and injury (FI) 

crashes was obtained from the CMF Clearinghouse based on a study by Fitzpatrick and Park (9). The CMF was 

developed from intersections in Arizona with a suburban or urban area type and it is assumed that the CMF is 

applicable to the location of interest. The treatment cost was estimated from another study, assuming a $100,000 

installation cost, 10-year service life, and negligible annual maintenance costs (10). A five percent discount rate is also 

assumed for the computations. The mean comprehensive crash cost for FI crashes is assumed to be $158,177 (8).
7

The following table presents the estimated crashes for each year of the service life. These values were 

estimated using the procedures outlined in the HSM. The CMF is applied to each of the estimated annual crashes 

without treatment to estimate the annual crashes with treatment. The annual crash reduction is estimated as the 

difference between the estimated annual crashes without and with treatment, and the mean comprehensive 

crash cost ($158,177) is applied to the reduction to estimate the annual monetary benefit. Present value factors 

are then computed and applied to estimate the annual benefit in terms of present dollars. 

The present monetary benefit is estimated to be $236,427 while the monetary cost is estimated to be $100,000. 

Thus, the BCR is 2.36 indicating a favorable result of the proposed treatment.

Year

Estimated 

FI Crashes 

Without 

Treatment

CMF

Estimated 

FI Crashes 

With 

Treatment

Estimated 

Reduction 

in FI 

Crashes

Estimated 

Monetary 

Benefit

Present 

Value 

Factor

Estimated 

Present 

Benefit

1 0.96 0.849 0.82 0.14 $22,929 0.95 $21,837

2 1.00 0.849 0.85 0.15 $23,885 0.91 $21,664

3 1.05 0.849 0.89 0.16 $25,079 0.86 $21,664

4 1.12 0.849 0.95 0.17 $26,751 0.82 $22,008

5 1.20 0.849 1.02 0.18 $28,662 0.78 $22,457

6 1.30 0.849 1.10 0.20 $31,050 0.75 $23,170

7 1.41 0.849 1.20 0.21 $33,677 0.71 $23,934

8 1.55 0.849 1.32 0.23 $37,021 0.68 $25,057

9 1.72 0.849 1.46 0.26 $41,082 0.64 $26,482

10 1.92 0.849 1.63 0.29 $45,859 0.61 $28,153

Total 13.21 11.23 2.00 $315,995 $236,427

CASE STUDY

CMFs can be applied in the roadway safety management process to help select countermeasures and prioritize 

projects through an economic evaluation (e.g., benefit-cost analysis). The following case study illustrates how 

CMFs have been applied in the roadway safety management process. It also identifies lessons learned, including 

noteworthy practices and challenges encountered by agencies with respect to the application of CMFs in the 

roadway safety management process.

Program Description

In 2007, the Virginia Department of Transportation (VDOT) started a new program, Strategically Targeted 

Affordable Roadway Solutions (STARS), aimed at critical safety and congestion hot spots throughout the State. 

The primary goals of the STARS program are to identify roadway improvements on the interstate and primary 

systems that:

• Are relatively low-cost.

• Address existing mobility and safety problem areas.

• Require minimal preliminary engineering and right-of-way.

• Can be implemented quickly (24 months or less).

The STARS program allows VDOT to better incorporate operations and safety into the long-term planning process 

and involves the following four steps.

1. Study area selection.

2. Detailed safety and operational analysis.

3. Prioritization of recommendations.

4. Programming and implementation. 
8

In this process, the study team identifies potential safety and operational issues in Step 2 along with a list of 

potential countermeasures. CMFs are then applied in Step 3 to help justify and prioritize the suggestions. 

Specifically, CMFs are used to estimate the safety impacts associated with each countermeasure. 

Project Description

The project highlighted for this case study is a hot spot analysis conducted in Wise County, Virginia in 2009. The 

study area, developed by the Southwest Regional Operations (SWRO) Study Team, encompasses the intersection 

of Orby Cantrell Highway (Route 23) and Wise Norton Road (Route 757), shown below in Figure 2.

Figure 2. Study location.

This location was prioritized by the SWRO study team based on a review of the crash history and peak hour 

operations. The study location is a signalized intersection controlled by an actuated traffic signal and both 

intersecting roads are maintained by VDOT. Right-turn-on-red operations are allowed from all approaches and 

all left-turn movements at the intersection operate under fully-protected phasing. There are no crosswalks or 

sidewalks at or near the intersection and each approach is characterized by the following variables.

Feature Route 23

(northbound/southbound)

Route 757

(westbound)

Route 23B

(eastbound)

Functional Classification Principal Arterial Minor Arterial Minor Arterial

Annual Average Daily Traffic 

(vehicles per day) 23,000 (year 2007) 5,600 (year 2007) 5,600 (year 2007)

Area Type Urban Urban Urban

Number of Lanes 4 4 2

Median Type Grass Undivided Undivided

Approach Grade Downgrade on Both Moderate Downgrade Upgrade

Posted Speed (mph) 55 25 25

The study team reviewed several pieces of information, including peak hour turning movement volumes, 

operational performance measures, and three years of police crash reports (2005-2007). The study team then 

conducted a field review to identify potential safety and operational issues and developed a list of possible 

measures to mitigate the identified issues. These measures were further analyzed to determine the timeframe for 

implementation (near-term, intermediate, or long-term), cost, and estimated benefit.
Note the steps followed in the 

case study are similar, but not 

identical, to those presented in 

the Application of CMFs in the 

Roadway Safety Management 

Process. Notably, the VDOT 

application form compares the 

annualized construction costs 

with the annual safety benefit. In 

the previous section, the total 

construction cost is compared to 

the present value of the safety 

benefit over the life of the project. 

Either method will produce similar 

results, but it is important to compare 

costs and benefits that are based 

on the same timeframe (e.g., present 

value, annual value, or future value).

9

Practical Application of CMFs

The study team identified the following potential safety issues at the study location.

1. Inconsistent and unmaintained signs.

2. Faded and missing pavement markings.

3. Sight distance obstructions (vegetation).

4. Limited guidance (ground-mounted street signs and lack of reflectors 

on guardrail)

5. Limited intersection lighting (30 percent of crashes occurred at night).

6. Short cycle length (queue does not clear).

7. Alignment issue (southbound receiving lanes don’t align with 

approach lanes).

8. Narrow and inconsistent shoulder width.

9. Multiple access points in close proximity to the intersection

The study team also developed several potential countermeasures to address 

the identified issues. Near-term measures are typically implemented by VDOT 

personnel within 12 months and include basic signing and pavement 

marking improvements, vegetation control, and minor signal timing 

improvements. Long-term measures are considered for inclusion in the 

long-range planning process. Intermediate measures are further analyzed 

to determine the benefit-cost ratio and potential for implementation. The 

economic evaluation is used to support the application for funding through 

the HSIP. 

The following intermediate measures were identified to address potential 

safety issues at the study location.

1. Convert constant-flash ‘signal ahead’ warning sign to 

signal-actuated warning. 

2. Install intersection lighting. 

3. Restripe southbound approach to improve alignment 

and conspicuity.

VDOT has developed an application form with an associated list 

of prescribed CMFs to be used when applying for funding for 

highway safety projects (see Sample Materials for a link to the 

application form and a sample of VDOT’s CMFs). This standardized 

form and application process help to enhance consistency across 

the nine districts in Virginia when applying for safety funding. 

The VDOT application form is a spreadsheet that incorporates 

many of the necessary computations to estimate the benefit-cost 

ratio. The sample calculations below are based on the benefit-cost 

analysis for the three intermediate measures above and the 

following steps outline the process for computing the benefit-cost 

ratio.

Step 1 – Estimate Cost of Treatment

The total and annualized construction costs are shown in 

Table 1 along with the expected service life for each treatment. 

For the economic evaluation, the annual operating costs, 

maintenance costs, and salvage values were assumed to be 

negligible. A discount rate of five percent was assumed to 

compute the annualized cost.
The Empirical Bayes method is an 

alternative for computing the 

expected crashes. The Empirical 

Bayes method helps to account for 

the natural fluctuation in crashes by 

combining the observed crash history 

with the predicted crashes obtained 

from a safety performance function.

10

Table 1. Estimated Construction Costs

Countermeasure Service Life

(years) Total Cost Annual Cost

Convert to Signal-Actuated Warning 10 $9,737 $1,261

Install Lighting 20 $34,002 $2,728

Restripe Southbound Approach 7 $42,838 $7,403

Step 2 – Identify CMFs

CMFs were obtained from the VDOT prescribed list of CMFs (refer to the Sample 

Materials), which is based on various studies and references. The applicable 

CMFs are shown in Table 2. Note that the CMFs are given by crash severity. In this 

case, the CMFs are the same across severity level for each treatment; however, 

the CMF may change by severity for other treatments.

Table 2. Applicable CMFs

Countermeasure CMFs by Severity Applicability Fatal Injury PDO

Convert to Signal-Actuated Warning 0.75 0.75 0.75 Right Angle, Rear End, Run-Off-Road

Install Lighting 0.75 0.75 0.75 Nighttime Crashes

Restripe Southbound Approach 0.80 0.80 0.80 All Crashes on Treated Approach

Step 3 – Estimate Annual Crashes WITHOUT Treatment

The target crashes without treatment were estimated from historical crash 

data. Specifically, the average annual crashes were computed by severity 

based on three years of observed crash data. The total target crashes by 

severity are shown in Table 3 for the three-year crash history at the study 

location. 

Table 3. Total Target Crashes by Severity (3-year history)

Crash Severity Right Angle, Rear End, 

Run-Off-Road

Nighttime 

Crashes

All Crashes on SouthBound Approach

Fatal (K) 0 0 0

Incapacitating Injury (A) 2 0 0

Non-Incapacitating Injury (B) 1 0 1

Possible Injury (C) 6 1 3

Property Damage Only (O) 14 9 10

The estimated annual target crashes by severity are shown in Table 

4 for each of the three treatments. Again, the estimated annual 

crashes were computed as the three-year average.
11

Table 4. Estimated Annual Target Crashes without Treatment

Crash Severity Right angle, Rear end, 

Run-off-road

Nighttime 

crashes

All crashes on southbound approach

Fatal (K) 0.00 0.00 0.00

Incapacitating Injury (A) 0.67 0.00 0.00

Non-Incapacitating Injury (B) 0.33 0.00 0.33

Possible Injury (C) 2.00 0.33 1.00

Property Damage Only (O) 4.67 3.00 3.33

Step 4 – Estimate Annual Reduction in Crashes

To estimate the change in target crashes, it is first necessary to estimate the 

annual crashes with treatment. To estimate the annual crashes with treatment, 

the annual crashes without treatment (Table 4) is multiplied by the applicable 

CMF (Table 2). The difference between the estimated crashes with and 

without treatment is then computed to estimate the change in target crashes. 

The computations are shown in Table 5 for the first treatment and the results 

for all three treatments are summarized in Table 6.

Table 5. Computations for Estimated Change in Crashes for Treatment 1

(Convert to Signal-Actuated Warning)

Crash Severity

Estimated Annual 

Crashes Without 

Treatment

Applicable CMF

Estimated 

Annual Crashes 

With Treatment

Estimated 

Change in 

Crashes

Fatal (K) 0.00 0.75 0.00 0.00

Incapacitating Injury (A) 0.67 0.75 0.50 0.17

Non-Incapacitating Injury (B) 0.33 0.75 0.25 0.08

Possible Injury (C) 2.00 0.75 1.50 0.50

Property Damage Only (O) 4.67 0.75 3.50 1.17

Table 6. Estimated Change in Target Crashes by Severity by Treatment

Crash Severity Convert to SignalActuated Warning

Install 

Lighting Restripe SB Approach

Fatal (K) 0.00 0.00 0.00

Incapacitating Injury (A) 0.17 0.00 0.00

Non-Incapacitating Injury (B) 0.08 0.00 0.07

Possible Injury (C) 0.50 0.08 0.20

Property Damage Only (O) 1.17 0.75 0.67

Step 5 – Convert Estimated Annual Crash Reduction to Monetary 

Benefit

Crash costs were obtained from the National Safety Council, 

which provides updated average comprehensive costs for 

motor vehicle crashes. The value of estimated annual safety 

benefit (i.e., crash cost savings) is computed by multiplying 

the change in target crashes (Table 6) by the applicable 

crash cost. The computations are shown in Table 7 for the first 

treatment and the results for all three treatments are 

summarized in Table 8.
12

Table 7. Computations for Value of Safety Benefit for Treatment 1 (Convert to Signal-Actuated Warning)

Crash Severity Estimated Change in Crashes Crash Cost1 Value of Safety Benefit

Fatal (K) 0.00 $3,760,000 $0

Incapacitating Injury (A) 0.17 $188,000 $31,960

Non-Incapacitating Injury (B) 0.08 $48,200 $3,856

Possible Injury (C) 0.50 $22,900 $11,450

Property Damage Only (O) 1.17 $6,500 $7,605

1.“Estimating the Costs of Unintentional Injuries, 2005” from the National Safety Council website www.nsc.org.

Table 8. Annual Value of Safety Benefit by Treatment

Crash Severity Convert to SignalActuated Warning

Install 

Lighting Restripe SB Approach

Fatal (K) $0 $0 $0

Incapacitating Injury (A) $31,960 $0 $0

Non-Incapacitating Injury (B) $3,856 $0 $3,374

Possible Injury (C) $11,450 $1,832 $4,580

Property Damage Only (O) $7,605 $4,875 $4,355

Total $54,871 $6,707 $12,309

Step 6 – Compute Benefit-Cost Ratio

The benefit-cost ratio is computed as the average annual benefit divided by the annual cost. The results of the 

analysis are presented in Table 9.

Table 9. Benefit-Cost Ratios

Countermeasure Annual Benefit Annual Cost B/C Ratio

Convert to signal-actuated warning $54,871 $1,261 43.5

Install lighting $6,707 $2,728 2.5

Restripe southbound approach $12,309 $7,403 1.7

It is worth noting that the benefit-cost ratio in the VDOT application is only used to assess the eligibility of a 

proposed improvement for HSIP funding. Improvements expected to provide crash reductions resulting in a 

benefit-cost ratio greater than one (1.0) are eligible for HSIP funding. However, a high benefit-cost ratio does not 

guarantee funding. Other factors such as the validity of treatment, project cost, and timeframe to complete the 

project are also considered to prioritize the eligible improvements. In general, projects that are low-cost, relatively 

quick to install, and target high-crash locations will receive more favorable consideration.

Sample Materials

Details regarding the VDOT Highway Safety Project application and general HSIP process, including the 

prescribed list of CMFs, are documented in the VDOT Highway Safety Improvement Program Manual. The 

VDOT Highway Safety Improvement Program Manual and Highway Safety Project application form can be 

downloaded at: http://www.virginiadot.org/business/ted_app_pro.asp.

Note that the computations in the above case study are based on the FY 2009-2010 HSIP application form. The 

current application form from the above link may contain some modifications, including updated crash costs. 

The following table is a sample of the prescribed reduction factors issued by VDOT. The table identifies 

the improvement type, expected service life of treatment, reduction factor, and target crashes. Note that the 

reduction factor may be different for different crash severities. Also, these reduction factors indicate the expected 

percent reduction in crashes, which could be converted to a CMF (e.g., expected 30 percent reduction in all 

crashes with the installation of a school zone warning sign is equivalent to a CMF of 0.7). 
13

Improvement Type Service Life

CRF Target Crashes

Fatal Injury PDO

Traffic Sign Improvement

Warning Sign

 Curve Warning 10 0.30 0.30 0.30 X X X X

 School zone 10 0.15 0.15 0.15 X

Regulatory Signs

 Stop Sign (Two-way) 10 0.30 0.30 0.30 X X X X

 Yield 10 0.25 0.25 0.25 X X

 All-way Stop 10 0.50 0.50 0.50 X X X X

Night

Wet Pavement

Overturn

Run Off Road

Pedestrian

Fixed Object

Right Turn

Left Turn

Right Angle

Side Swipe

Head On

Rear End

All

For more information about the case study, contact Robin Grier, (Virginia Department of Transportation (VDOT), 

Assistant Division Administrator for Statewide and Regional Planning, 804-786-2964, Robin.Grier@VDOT.Virginia.

gov), or Chad Tucker, (VDOT, Short Range Planning Manager, 804-786-2974, Chad.Tucker@VDOT.Virginia.gov).

Summary of Key Findings

There are several potential benefits associated with the application of CMFs in the safety management process. 

Specifically, CMFs provide a means to quantify the safety impacts of decisions and help to raise awareness of 

safety. The application of CMFs also helps to prioritize potential treatments and provides decision-makers with the 

information needed to identify cost-effective strategies. VDOT indicated that the STARS program has helped to 

raise awareness of safety issues at both the State and local level, which has led to more safety-focused projects.

The goal of the STARS program is to identify where safety and congestion issues overlap on the State’s roadways. 

As demonstrated in the case study, CMFs are used in the benefit-cost analysis to quantify the safety impact 

of the suggested countermeasures. The results of the benefit-cost analysis are beneficial in the prioritization of 

recommendations as well as the programming and implementation stage. VDOT indicated that STARS-based 

projects have addressed more crashes and typically involve lower impact treatments (less utility and right of 

way) that can be implemented more quickly than proposals submitted prior to the STARS program.

Using CMFs as part of the benefit-cost analysis is not only beneficial to prioritizing the suggested 

countermeasures for a particular site, but also helps in the management of a safety program. The STARS 

program actively utilizes HSIP funds for many of the hot spot locations throughout the State. The CMFs used in the 

benefit-cost analysis are instrumental in the application process for HSIP funding.

OVERCOMING POTENTIAL CHALLENGES

Potential challenges may arise when applying CMFs in the roadway safety management process. Many are 

directly related to limitations in the progress of CMF research, while others apply to the lack of understanding of 

CMFs. Despite decades of advancement in CMF research, there are still knowledge gaps that present obstacles 

for practitioners seeking to apply CMFs in the roadway safety management process. The Introduction to Crash 

Modification Factors (1) provides general guidance related to the application of CMFs. The following are general 

challenges associated with the application of CMFs and opportunities to overcome challenges. The discussion 

includes specific concerns and lessons learned based on actual experiences with the application of CMFs in 

roadway safety management efforts.
The VDOT HSIP funding 

application spreadsheet 

accounts for multiple 

treatments by multiplying 

the CMFs for the respective 

treatments. This is the method 

recommended in the HSM (2). 

However, users should recognize 

the treatments may target 

different crashes and the 

associated CMFs may apply to 

different crash types. If this is the 

case, then the CMFs should not 

be multiplied together to estimate 

the combined effect. Instead, the 

CMFs should be applied separately 

to the respective target crashes to 

estimate the expected impact of 

each treatment individually. At that 

point, the results can be aggregated 

to estimate the combined effect of 

the treatment.

14

Availability of CMFs

A notable potential challenge is the availability of CMFs for specific 

countermeasures. The CMF Clearinghouse (7) contains over 3,000 CMFs for a wide 

range of safety countermeasures under a variety of conditions. However, CMFs are 

still lacking for a large number of treatments, especially combination treatments 

and those that are innovative and experimental in nature. Furthermore, CMFs may not 

be available for certain crash types and severities.

The CMF Clearinghouse (7) provides a “Most Wanted List” for CMFs. Users can 

access the website and add to the list by submitting ideas for future CMF 

research or current needs. While the research would need to be completed, this 

link provides users with the opportunity to share their CMF needs.

Applicability of CMFs

CMFs are developed based on a sample of sites with specific conditions. While 

a CMF may be available for a given treatment, it may not be appropriate 

for the scenario under consideration. For example, there may be significant 

differences between the characteristics of a proposed treatment site and the 

sites used to develop the CMF (e.g., different area type, number of lanes, or 

traffic volume). The CMF Clearinghouse (7) and HSM (2) provide information 

to help users identify the applicability of CMFs.

A related challenge may be that multiple CMFs exist for the same 

treatment and conditions. This is particularly challenging when multiple 

studies have estimated CMFs for the same countermeasure and 

combination of crash type and severity level, but yielded dissimilar results. 

If the CMFs also apply to the same roadway characteristics, then the 

selection can become even more difficult. A star quality rating—which 

appraises the overall perceived reliability of a CMF using a range of 

one to five stars—is provided by the CMF Clearinghouse and may be 

helpful in these circumstances to identify the most suitable CMF. 

However, the ratings of the different CMFs may be similar as well. If the 

various CMFs have a fairly small range of values, then this situation 

may not be of great concern. Yet, it is possible for the CMFs to vary 

significantly and even have contradictory expected outcomes (i.e., 

some CMFs greater than 1.0 and others less than 1.0). In such cases, 

this potential situation would be highly challenging to overcome. 

Additional guidance on how to select the most applicable CMF is 

posted on the CMF Clearinghouse (7) under FAQs.

Estimating the Effects of Multiple Treatments

The current practice for many agencies is to assume that CMFs 

are multiplicative; this is the current method presented in the 

HSM (2) and posted on the CMF Clearinghouse (7). There are 

relatively few studies that estimate CMFs for combinations of 

countermeasures. It is far more common for studies to estimate 

CMFs for individual treatments. Consequently, it is difficult to 

accurately estimate the effects of combinations of treatments. 

In brief, the recommended approach (and many of the 

alternatives) is problematic in the sense that applying the 

combined CMF may overestimate or underestimate the 

true crash effects, particularly if the treatments target similar 

crash types. More information regarding the application of 

multiple CMFs is available in recent articles (11, 12).
VDOT has 

participated in 

various training 

sessions related to 

CMFs and the 

application of the 

methods in the HSM.

The VDOT STARS 

program is based on a 

formal and repeatable 

process. In particular, the 

State has developed an 

HSIP manual that identifies 

the process for evaluating 

safety issues and applying 

for funding, including a 

prescribed list of CMFs. The 

standardized process helps 

to enhance consistency 

across the nine districts in 

Virginia when applying for 

safety funding. Specifically, 

it discourages districts from 

selecting and applying CMFs 

that may show a more 

favorable result. It does not, 

however, prevent districts from 

identifying more applicable 

CMFs, but they need to receive 

approval from the central office 

before using a different CMF in 

the funding application.

15

Insufficient Expertise

A specific challenge could be that there is insufficient expertise within an 

agency to apply CMFs. While CMFs are not a new tool, they have only 

recently gained popularity among safety professionals. There are a number 

of opportunities to apply CMFs in aspects of transportation engineering 

(e.g., roadway safety management process), but it may be necessary 

to solicit input or assistance from those who are more familiar with the 

selection and application of CMFs. If an agency does not have the needed 

expertise related to CMFs, then they can solicit outside expertise from the 

State Safety Engineer, FHWA Division Office, or consultants for further guidance 

and assistance with the selection and/or application of CMFs and 

interpretation of results. The National Highway Institute also offers several 

courses related to the quantification of safety using CMFs, including the 

Application of CMFs (#380093) and Science of CMFs (#380094).

Inconsistency across Decentralized States

Where multiple districts/divisions/regions exist within a State, there is the 

potential for inconsistency with respect to the selection and application of 

CMFs. This can result from a number of factors, including available resources 

and range in expertise. There is need to encourage the consistent selection 

and application of CMFs in the roadway safety management process 

within a State, particularly if the districts/divisions/regions are competing for 

the same pool of funding. 

Estimating Annual Crashes without Treatment

To quantify the expected safety performance for a given alternative, it 

is necessary to estimate the annual crashes without treatment. The 

applicable CMFs are then applied to the annual crashes without

treatment to estimate the annual crashes with treatment. The annual 

crashes without treatment can be estimated using several methods, 

with each bringing certain strengths and weaknesses. The most basic 

approach is to use the observed crash history of the site of interest 

(i.e., short-term or long-term average) to estimate annual crashes 

without treatment. This method is relatively simple but is highly 

susceptible to regression-to-the-mean bias (i.e., random fluctuation 

in crashes over time) and could overestimate or underestimate 

the annual crashes without treatment. Another option to 

estimate annual crashes without treatment is to employ SPFs, 

which provide the predicted number of crashes. SPFs help to 

account for the random nature of crashes at a single site by 

incorporating data from other similar sites. The drawback to 

using SPFs is that, unless they are developed using local data, 

they may not accurately reflect local conditions and again 

could overestimate or underestimate the annual crashes 

without treatment. The HSM (2) presents the Empirical Bayes 

method as yet another option, which combines both the observed

crash history of a site and the predicted crashes from the SPF to 

compute the expected crashes. 

The prior discussion assumes that the crash history is available 

and applicable for a given site. In some cases, the crash 

history may not be available (e.g., new construction); 

in others, the crash history may not be applicable 

(e.g., significant changes in the alignment). For both 

scenarios, it may be necessary to rely on SPF predictions, but 
For More Information: 

For more information about CMFs 

or the CMFs in Practice series, 

contact Karen Scurry, FHWA Office 

of Safety, karen.scurry@dot.gov, 

609-637-4207.

Visit us on the web at: 

http://safety.fhwa.dot.gov/

tools/crf/resources/cmfs/

it is suggested that the SPFs be calibrated to local conditions before applying them, 

whenever possible. The Introduction to Safety Performance Functions (13) provides 

general guidance related to the selection, calibration, and application of SPFs.

REFERENCES

1. Introduction to Crash Modification Factors. Federal Highway Administration. 

Available online at: http://safety.fhwa.dot.gov/tools/crf/resources/cmfs/. 

2. American Association of State Highway and Transportation Officials 

(AASHTO). Highway Safety Manual, 1st Edition, Washington, DC, 2010.

3. Highway Safety Improvement Program (HSIP) Manual. Publication 

FHWA-SA-09-029, Federal Highway Administration, Washington, DC, 2010.

4. National Cooperative Highway research Program (NCHRP). NCHRP Report 

500 Series: Guidance for Implementation of the AASHTO Strategic Highway 

Safety Plan, Volumes 1-20. Transportation Research Board, Washington, DC, 

2004. Available online at: http://safety.transportation.org/guides.aspx. 

5. Gross, F., Persaud, B., and C. Lyon. A Guide to Developing Quality Crash 

Modification Factors. Publication FHWA-SA-10-032, Federal Highway 

Administration, Washington, D.C., 2010. Available online at: 

http://safety.fhwa.dot.gov/tools/crf/resources/fhwasa10032/. 

6. Carter, D., R. Srinivasan, F. Gross, and F. Council. Recommended Protocols 

for Developing Crash Modification Factors. National Cooperative 

Highway Research Program, Transportation Research Board, 

February, 2012.

7. Crash Modification Factors (CMF) Clearinghouse. Federal Highway 

Administration. Available online at: www.cmfclearinghouse.org. 

8. Council, F., Zaloshnja, E., Miller, T., and Persaud, B. Crash Cost 

Estimates by Maximum Police-Reported Injury Severity within 

Selected Crash Geometries. Publication FHWA-HRT-05-051, Federal 

Highway Administration, McLean, VA, 2005. Available online at: http://

www.fhwa.dot.gov/publications/research/safety/05051/.

9. Fitzpatrick, K. and Park, E.S. Safety Effectiveness of the HAWK 

Pedestrian Crossing Treatment. FHWA-HRT-10-042, Federal Highway 

Administration, Washington, DC, 2010. Available online at: 

http://www.fhwa.dot.gov/publications/research/safety/10042/.

10. Page, J. “HAWKs may soon protect S.L. pedestrians.” Deseret News, 

November 5, 2008. Accessed October 27, 2011, from http://

www.deseretnews.com/article/705260644/HAWKs-may-soonprotect-SL-pedestrians.html.

11. Gross, F. and Yunk, K. “Crash Modification Factors: An Overview 

of Its Applications.” Public Roads. Federal Highway 

Administration, Washington, D.C., 2011.

12. Gross, F., Hamidi, A., and Yunk, K. Investigation of Existing and 

Alternative Methods for Combining Multiple CMFs. Federal 

Highway Administration, Washington, D.C., 2011.

13. Introduction to Safety Performance Functions. Federal 

Highway Administration. Available online at: http://safety.

fhwa.dot.gov/tools/crf/resources/cmfs/.

FHWA-SA-13-010