CRASH MODIFICATION FACTORS IN PRACTICE

Using CMFs to Quantify Safety in 

the Development and Analysis of 

Alternatives

The Crash Modification Factors (CMFs) in Practice: Using CMFs to Quantify 

Safety in the Development and Analysis of Alternatives guide describes 

and illustrates several opportunities to incorporate the latest methods to 

quantify safety in the development and analysis of design alternatives

using CMFs. The target audience includes planners, engineers, and

program managers responsible for the development, review, and 

evaluation of alternatives. The purpose of this guide is to help raise 

awareness of opportunities to consider and quantify safety in the 

development and analysis of alternatives, with a specific focus 

on the application of CMFs to support this process. The objectives 

are to 1) identify opportunities to consider safety in the various steps 

of the design process, 2) describe various methods available for 

quantifying safety using CMFs, and 3) explain when it would be 

appropriate to employ each method. By providing safety 

awareness, practitioners will be better prepared to assess the 

safety impacts of design alternatives and explicitly consider those 

impacts during the development and analysis of alternatives.

INTRODUCTION

Historically, it has been very challenging to quantify safety explicitly 

along with other factors such as operational and environmental 

impacts during the project development process. Instead, safety has 

been assumed to be inherent in design policies and practices. 

Methods and related tools have been available for several years 

to quantify the operational and environmental impacts of design 

decisions. Recently, similar methods and tools have been developed 

to quantify the safety impacts of these decisions, but these resources 

are relatively new. There is a need to raise awareness of the current 

level of road safety knowledge and the methods available to 

quantify safety in the development and analysis of alternatives. 

Quantifying safety will help decision-makers better understand the 

safety impacts of design alternatives and allow safety impacts to 

be considered in conjunction with other factors. It is important 

for professionals involved in the development and analysis of 

alternatives to understand the importance of quantifying safety 

and using appropriate methods to do so.

Development and analysis of alternatives ensures that multiple 

options are explored to achieve the goals and objectives of 

a project. Alternatives development identifies various options 

for improvement strategies or design elements. Alternatives 

analysis compares the various designs on a number of factors 

including safety, cost, operational performance, and 

environmental and economic impacts. As such, alternatives 

development and analysis provides an added opportunity 

to consider safety early in the project development process. 

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 help raise awareness of 

safety, demonstrate the use 

of CMFs, and introduce other 

methods to quantify safety in 

these five activities.

Federal Highway Administration, Office of Safety, 

1200 New Jersey Avenue SE, Washington, DC 20590
Contact information for 

the FHWA field offices 

is available at: http://

www.fhwa.dot.gov/

about/field.cfm.

CONTENTS

1 Introduction

2 Overview of Safety in 

the Development and 

Analysis of Alternatives

4 Methods for Quantifying 

Safety Impacts in the 

Development and 

Analysis of Alternatives

14 Application of CMF-Related 

Methods in the Development 

and Analysis of Alternatives

17 Case Studies

24 Overcoming Potential 

Challenges

27 References

2

Safety is explicitly considered in the evaluation of alternatives, but has traditionally 

been more of a qualitative and nonmonetary consideration. Recently developed 

methods may allow the project team to quantify the safety performance (i.e., estimate 

crash frequency) for various alternatives. Estimated crashes can then be converted 

to a monetary value by applying average crash costs. In this way, safety can be 

considered in conjunction with other monetary costs during the decision-making 

process.

Read more for an overview of quantifying safety in the development and analysis 

of alternatives using crash modification factors (CMFs) or skip to the section 

that describes available methods for quantifying safety using CMFs. A decisionsupport chart is provided to help identify when CMF-related methods may be 

appropriate in the development and analysis of alternatives. Examples are 

provided to illustrate how these methods can be applied and case studies 

illustrate how these methods have been applied in particular states in the 

development and analysis of alternatives. Finally, actual and potential 

challenges are presented with opportunities to overcome common 

application issues. While several examples are provided to demonstrate 

the basic application of CMF-related methods, the State Highway Safety 

Engineer (or equivalent) or Federal Highway Administration (FHWA) Division 

Office can provide further guidance and assistance with the application of 

these methods and the interpretation of results.

OVERVIEW OF SAFETY IN THE DEVELOPMENT AND ANALYSIS OF ALTERNATIVES

The development and analysis of alternatives is a fundamental part of 

the transportation planning process. The transportation planning process 

begins with the creation of a vision aimed at promoting prosperity, social 

equity, and environmental quality (1). Vision statements express the 

desired direction for a transportation system but generally lack specific 

information. Once a vision has been established, goals and objectives 

are formulated to define the specific purposes of the transportation 

planning process. Goals and objectives, in turn, help to identify aspects 

of the transportation system that are deemed to be of greatest 

importance, which lead to the selection of system performance 

measures (1). System performance measures determine what data 

are to be collected and what analyses are to be performed. The 

development and analysis of alternatives fits into the transportation 

planning process at this point. This process typically consists of 

two steps:

1. Identification of alternatives.

2. Evaluation of alternatives. 

First, alternative improvement strategies or projects are identified 

that address the established goals and objectives. Alternatives 

are then evaluated to determine which plans are “feasible” and 

should be recommended for implementation. A brief summary 

of each step is presented below, noting the steps where 

safety considerations and analysis can be incorporated. By 

incorporating safety analysis in the process, agencies can 

quantify and better understand the anticipated safety 

performance of alternatives. This is particularly useful for risk 

management and defending against potential litigation. For 

example, a project team may consider several alternatives for 

a given project and select the combination that achieves a 

reasonable balance between cost, safety, operations, and 

environmental impacts.
The estimated safety performance, 

along with other factors, can help 

guide decisions in the selection of 

a reasonable alternative. Safety is 

only one factor to consider in the 

project development process and 

other factors such as operational 

efficiency, cost-effectiveness, and 

environmental impacts may take 

priority in certain cases. 

3

Identification of Alternatives

The initial identification of alternatives considers all possible courses of action 

including the “as-is” or “no-build” scenario. The next step is to screen the inclusive list 

of potential alternatives according to suitable criteria. One possible set of criteria 

are appropriateness, adequacy, and implementation feasibility (2).

• Appropriateness – assesses whether the course of action addresses the specific 

goals and objectives set forth in the planning process.

• Adequacy – assesses whether the magnitude of the improvement caused 

by the course of action would be sufficient to meet the performance 

expectations.

• Feasibility – assesses whether the course of action can be implemented, given 

the available resources.

Alternatives that pass the screening process represent “feasible” alternatives. 

Enough alternatives should be generated to identify tradeoffs among 

performance goals (2). However, the number of alternatives generated should 

not be so great that evaluations become unmanageable (2).

Evaluation of Alternatives

The evaluation of alternatives requires the estimation of costs and 

implications of improvement projects on the performance of a roadway 

where safety, operations, and other factors are used as performance 

measures. Once the monetary and nonmonetary impacts have been 

determined, alternatives are evaluated by comparing their respective costs, 

impacts, and cost-effectiveness to identify the alternative that achieves 

the desired balance among these factors. 

Safety is typically considered during the development and analysis 

of alternatives, but has traditionally been assessed based on the 

compliance of the design to applicable design standards. It was 

difficult to quantify the safety impacts of alternatives and include with 

other nonmonetary considerations such as operational, environmental, 

economic, and accessibility impacts. Agency and user costs have 

traditionally been considered as the only monetary costs. Agency 

costs for a given alternative may include construction costs, 

rehabilitation and maintenance costs, and operating costs.

The evaluation phase is the primary opportunity to use CMFs and 

related methods to quantify safety impacts in the analysis of 

alternatives. The application of these methods may allow the 

project team to estimate the safety performance as they identify 

and discuss advantages and disadvantages of each alternative. 

It is possible to convert the estimated safety performance to 

monetary terms and use economic efficiency criteria, such as 

a benefit-cost ratio, to evaluate the alternatives. Otherwise, a 

multi-criteria evaluation is necessary in which monetary and 

nonmonetary criteria are weighted, scaled, and combined to 

derive an objective function (2); the alternative with the highest 

value on the objective function represents the best option.

Design exceptions may arise during the evaluation of 

alternatives. A design exception is “a documented decision 

to design a highway element or a segment of highway to 

design criteria that do not meet minimum values or ranges 

established for that highway or project” (3). Readers can refer 
Note that while there 

are several methods 

available to consider 

and quantify safety in 

the development and 

analysis of alternatives, 

there is a clear order of 

preference based on the 

availability of data and 

reliability of the methods. 

Engineering judgment is 

an essential component 

of each method.

4

to the companion guide, CMFs in Practice: Quantifying Safety in Design Decisions 

and Exceptions (4) for further guidance on the application of CMFs and related 

methods to quantify the safety impacts of design decisions and exceptions.

METHODS FOR QUANTIFYING SAFETY IMPACTS IN THE DEVELOPMENT AND 

ANALYSIS OF ALTERNATIVES

There are several opportunities to identify and address safety impacts in the 

development and analysis of alternatives. This section focuses on the evaluation 

of alternatives and identifies several methods and related tools that can be used 

to compare the safety impacts of alternatives. Safety impacts are quantified by 

estimating the extent to which each alternative or given set of conditions is likely 

to impact the frequency and severity of crashes. The safety impacts can then be 

compared among the alternatives and considered in conjunction with other 

factors such as operational and environmental impacts and overall project cost. 

The safety impacts can be estimated using a number of methods which 

incorporate one or more of the following inputs: crash modification factors, 

safety performance functions, observed crash frequency, predicted crash 

frequency, and expected crash frequency. Engineering judgment is an 

essential component of each method. These terms are defined below, 

followed by a discussion of each method. The methods are presented 

in order of increasing reliability, with a discussion of their strengths and 

limitations. While the most reliable method is preferred, the most appropriate 

method depends on the complexity of the decision at hand and the 

availability of required inputs. Related tools are then identified and can 

be used to help implement the methods. This section concludes with 

guidance on how to select an appropriate method based on the 

decision at hand and availability of required inputs.

Inputs

The required inputs are defined below, followed by a discussion of the 

various methods. More rigorous methods can be employed when 

more inputs are available; the most rigorous method requires all of the 

following inputs. 

Crash Modification Factors

A crash modification factor (CMF) is an index of the expected 

change in safety performance following a modification in traffic 

control strategy or design element. When applied correctly, CMFs 

can be used to estimate the safety effectiveness of a given strategy, 

compare the relative safety effectiveness of multiple strategies, and 

adjust the crash frequency estimated from observed, predicted, or 

expected crashes. Readers can refer to the Introduction to Crash 

Modification Factors for more information on CMFs and how they 

are applied (5).

Safety Performance Functions

A safety performance function (SPF) is an equation used to 

predict the average number of crashes per year at a location 

as a function of traffic volume and, in some cases, roadway 

or intersection characteristics (e.g., number of lanes, traffic 

control, or median type). SPFs are developed for specific 

facility types based on data from a group of similar sites 
5

and the results apply to a set of specified baseline conditions. The results from an SPF can be multiplied by an 

applicable CMF to account for differences between the actual site conditions and the specified baseline conditions. 

If an SPF is developed using data from another jurisdiction or time period, then it may be necessary to adjust 

the SPF through calibration to better reflect local conditions or a different study period. Readers can refer to the

Introduction to Safety Performance Functions (6) for more information on SPFs and how they are applied.

Observed Crashes

Observed crashes are those reported at a site of interest. For example, there were 15 crashes reported over a 

three-year period at an urban, stop-controlled intersection. One might estimate that, on average, there will be five 

crashes per year at this location based on the observed crash history. Using the observed crashes to estimate 

annual average future crashes assumes that the past performance is a good approximation of the future (e.g., 

no changes in traffic volume, site conditions, driver behavior, weather, etc).

Predicted Crashes

Predicted crashes are estimated from an SPF. The predicted number of crashes for a given site is an estimate 

of the average number of crashes per year based on the crash experience at other locations with similar 

characteristics (e.g., area type, geometry, and operations). One might use the predicted crashes to estimate 

the future safety performance of a site when the observed crash history is not a good approximation of future 

conditions (e.g., conditions change over time such as traffic volume, site conditions, driver behavior, weather, etc).

Expected Crashes

Expected crashes are estimated using the Empirical Bayes method, which is a weighted average of the 

observed and predicted crashes for a site of interest. One might use the expected crashes to estimate future safety 

performance when there is value in both the observed and predicted crashes for a site of interest. One benefit 

of using the expected crashes is that it helps to account for the natural variation in crashes (i.e., regressionto-the-mean).

Engineering Judgment

Engineering judgment refers to decisions made based on an evaluation of available pertinent information 

and a sound understanding of established engineering principles and practices. Applying sound engineering 

judgment is necessary when selecting and utilizing all methods for quantifying safety impacts. It is also 

necessary when interpreting the results of a method and considering the safety impacts of various alternatives in 

conjunction with other factors such as operational and environmental impacts as well as overall project cost.

Methods for Quantifying Safety Impacts

Several methods are available for quantifying safety impacts in the development and analysis of alternatives. The 

following is a detailed discussion of each method, required inputs, and associated strengths and limitations. It is 

important to note that the methods are presented in order of increasing reliability and an appropriate method 

should be selected based on the complexity of the decision at hand and the availability of required inputs. 

Further guidance on the selection of an appropriate method is provided after the discussion of methods. 

Relative Comparison of CMFs

This method is used to estimate the relative magnitude and direction of potential safety impacts based on the 

anticipated percent change in crash frequency. It does not provide an estimate of the change in the number of 

crashes (only the percent change). The required inputs for this method include the following:

• Applicable CMFs.

• Engineering judgment. 

When there is a lack of required inputs or expertise to employ more rigorous methods, then it may be necessary 

to simply compare the relative values of applicable CMFs to estimate the safety impacts of a design alternative. 

For example, a CMF may be identified for converting a signalized intersection to a roundabout and used to 
6

estimate the percent change in crashes when the intersection type is a roundabout compared to a 

conventional signal. A numerical example is provided later in this document in the Relative Comparison of 

Design Alternatives using CMFs section.

The advantages of this method include the following:

• It is relatively simple to apply.

• It does not require an estimate of crashes without treatment to which the CMF would be applied. 

The limitations of this method include the following:

• It requires applicable CMFs.

• It does not provide an estimate of the change in the number of crashes (only the percent change).

• It is difficult to compare multiple alternatives when the applicable CMFs are for different crash types or severities.

Observed Crash Frequency with CMF Adjustment

This method is used to estimate the crash frequency for design alternatives. The results can be used to compare 

the safety performance of design alternatives or included in a benefit-cost analysis to quantify the benefits. The 

required inputs for this method include the following:

• Observed crashes.

• Applicable CMF(s).

• Engineering judgment. 

When there is a lack of required inputs or expertise to employ more rigorous methods, then it may be 

necessary to estimate the safety impacts of a design alternative based on observed crashes and CMFs. The 

observed crashes (e.g., five-year average) for the location of interest are used to estimate the average crash 

frequency for existing conditions. Appropriate CMFs are then applied to estimate the crash frequency under 

different design alternatives. Compared to the previous method, the observed crash history is the only additional 

piece of information required. A numerical example is provided later in this document in the Estimating the Safety 

Impacts of Alternative Designs Using Observed Crashes and CMFs section, comparing the safety effectiveness of 

a traffic signal and roundabout as alternatives to an existing two-way stop-controlled intersection. 

The advantages of this method include the following:

• It is relatively simple to apply.

• It provides an estimate of the change in crash frequency (not just the percent change).

• It can be applied when an SPF is not available for the facility type of interest.

The limitations of this method include the following:

• Applicable crash history and CMF(s) are required.

• It does not properly account for changes in traffic volume.

• It is susceptible to regression-to-the-mean bias (i.e., random variation in crashes over time).

Predicted Crash Frequency

This method is used to estimate the crash frequency for design alternatives. The results can be used to compare 

the safety performance of design alternatives or to quantify the benefits in a benefit-cost analysis. The required 

inputs for this method include the following:

• Applicable SPF.

• Engineering judgment. 

This method applies to situations where the observed crash history is not available (e.g., new construction) or 

applicable (e.g., proposed conditions differ drastically from the existing conditions). The predicted crash 

frequency is computed from an applicable SPF. 

The advantages of this method include the following:

• It provides an estimate of the change in crash frequency (not just the percent change).

• It can account for changes in traffic volume over time.

• It can be applied when observed crash history is not available or not applicable for the location of interest.
7

• It includes data from similar sites to reduce the reliance on crash data for any 

one site.

The limitations of this method include the following:

• An applicable SPF is required that includes the variables of interest. For example, 

the SPF would need to include a variable for median type if this was a design 

feature of interest. It may also be necessary to adjust the SPF through calibration 

to better reflect local conditions or a different study period.

• It is susceptible to regression-to-the-mean bias (i.e., random variation in crashes 

over time).

Predicted Crash Frequency with CMF Adjustment

This method is used to estimate the crash frequency for design alternatives. The 

results can be used to compare the safety performance of design alternatives 

or to quantify the benefits in a benefit-cost analysis. The required inputs for this 

method include the following:

• Applicable SPF.

• Applicable CMF(s).

• Engineering judgment. 

This method applies to situations where observed crash history is not 

available (e.g., new construction) or applicable (e.g., proposed conditions 

differ drastically from the existing conditions) and where the SPF does not 

include one or more variables of interest. In these cases, an applicable 

SPF is used to estimate the predicted crashes for a set of baseline 

conditions and applicable CMFs are applied to estimate the predicted 

crashes for other conditions of interest. For example, an applicable SPF 

may be available for the facility type of interest, but not include a 

variable for median type. The SPF would be used to estimate the 

predicted crashes for baseline conditions and CMFs would be applied 

to estimate the impacts of different median types.

The advantages of this method include the following:

• It provides an estimate of the change in crash frequency (not just the 

percent change).

• It can account for changes in traffic volume over time.

• It can be applied when observed crash history is not available or 

not applicable for the location of interest.

• It includes data from similar sites to reduce the reliance on crash 

data for any one site.

• It does not require an SPF that includes all variables of interest.

The limitations of this method include the following:

• An applicable SPF is required for the facility type of interest. It may 

also be necessary to adjust the SPF through calibration to better 

reflect local conditions or a different study period.

• Applicable CMFs are required to account for the additional 

variables of interest.

• It is susceptible to regression-to-the-mean bias (i.e., random 

variation in crashes over time).

Expected Crash Frequency

This method is used to estimate the crash frequency for design 

alternatives. The results can be used to compare the safety 

performance of design alternatives or to quantify the benefits 
8

in a benefit-cost analysis. The required inputs for this method include the following:

• Observed crashes from an applicable crash history.

• Predicted crashes from an applicable SPF.

• Engineering judgment.

This method applies to situations where the observed and predicted crashes can 

be estimated and where the SPF includes the variables of interest. In these cases, 

the predicted crash frequency is computed from the applicable SPF for the 

conditions of interest. The expected crash frequency is computed using the 

Empirical Bayes approach, which is a weighted average of the observed and 

predicted crashes; this improves the accuracy and reliability of the estimate. The 

weight is based on the statistical reliability of the SPF. 

The advantages of this method include the following:

• It provides an estimate of the change in crash frequency (not just the percent 

change).

• It can account for changes in traffic volume over time.

• It includes data from the site of interest as well as data from similar sites to 

reduce the reliance on crash data for any one location.

• It can account for regression-to-the-mean bias (i.e., random variation in 

crashes over time) by considering the long-term average crash frequency 

rather than short-term observed crash frequency.

The limitations of this method include the following:

• An applicable SPF is required that includes the variables of interest. For 

example, the SPF would need to include a variable for median type if this 

was a design feature of interest. It may also be necessary to adjust the 

SPF through calibration to better reflect local conditions or a different 

study period.

• An appropriate level of expertise is required to apply the Empirical Bayes 

method.

Expected Crash Frequency with CMF Adjustment

This method is used to estimate the crash frequency for design 

alternatives. The results can be used to compare the safety 

performance of design alternatives or to quantify the benefits in a 

benefit-cost analysis. The required inputs for this method include the 

following:

• Observed crashes from an applicable crash history.

• Predicted crashes from an applicable SPF.

• Applicable CMF(s).

• Engineering judgment. 

This method applies to situations where the observed and 

predicted crashes can be estimated and where the SPF does 

not include one or more variables of interest. In these cases, the 

predicted crash frequency is computed from the applicable SPF 

for baseline conditions and multiplied by applicable CMFs to 

estimate crashes for the conditions of interest. The expected 

crash frequency is computed using the Empirical Bayes 

approach, which is a weighted average of the observed and 

predicted crashes; this improves the accuracy and reliability of 

the estimate. The weight is based on the statistical reliability of 

the SPF. 
Note t

9

The advantages of this method include the following:

• It provides an estimate of the change in crash frequency (not just the percent 

change).

• It can account for changes in traffic volume over time.

• It includes data from the site of interest as well as data from similar sites to reduce 

the reliance on crash data for any one location.

• It does not require an SPF that includes all variables of interest. 

• It can account for regression-to-the-mean bias (i.e., random variation in crashes 

over time) by considering the long-term average crash frequency rather than 

short-term observed crash frequency.

The limitations of this method include the following:

• An applicable SPF is required for the facility type of interest. It may also be 

necessary to adjust the SPF through calibration to better reflect local 

conditions or a different study period.

• Applicable CMFs are required to account for the additional variables of interest.

• An appropriate level of expertise is required to apply the Empirical Bayes 

method.

The following table provides a summary of the previous methods along 

with the required inputs. Note that engineering judgment is an essential 

component of all methods.

Methods for Quantifying 

Safety Impacts

Required Inputs

Applicable

CMF

Applicable 

Crash History

(Observed Crashes)

Applicable SPF

(Predicted Crashes)

Engineering 

Judgment

Relative Comparison 

of CMFs • •

Observed Crash Frequency 

with CMF Adjustment • • •

Predicted Crash Frequency • • Predicted Crash Frequency 

with CMF Adjustment • • •

Expected Crash Frequency • • • Expected Crash Frequency 

with CMF Adjustment • • • •

Related Tools for Implementing Methods

Several tools have been developed to help implement the methods 

presented above. This guide provides a brief introduction to various 

tools that are available for quantifying safety impacts in the 

development and analysis of alternatives. Readers can refer to 

the specific references for more information on each tool. 

Highway Safety Manual

The Highway Safety Manual (HSM) provides a new generation 

of safety analysis methods and represents the current stateof-the-art in highway safety analysis (7). The knowledge and 

methods included in the HSM may allow users to explicitly 

consider and quantify safety in the project development 

process. The HSM includes four parts as follows:
Contact information for the 

FHWA field offices is available 

at: http://www.fhwa.dot.gov/

about/field.cfm.

10

• Part A – Introduction, Human Factors, and Fundamentals: Part A describes the 

purpose and scope of the HSM and includes the fundamentals and background 

information needed to apply the methods and tools provided in Parts B, C, and D 

of the HSM.

• Part B – Roadway Safety Management Process: Part B presents information related 

to each of the six steps in the safety management process. These steps include 

network screening, diagnosis, countermeasure selection, economic appraisal, 

project prioritization, and effectiveness evaluation.

• Part C – Predictive Method: Part C provides a predictive method for estimating 

expected crash frequency of a network, facility, or individual site. This includes 

the use of SPFs to estimate the predicted crash frequency. Predictive methods 

are currently provided for roadway segments and intersections for the following 

facility types: 1) rural two-lane, two-way roads, 2) rural multilane highways, and 

3) urban and suburban arterials. The predictive method for freeways and 

ramps has been developed and will be incorporated in the next edition of 

the HSM.

• Part D – Crash Modification Factors: Part D provides a catalog of CMFs for 

a variety of design and operational strategies. The material is organized by 

site type and includes CMFs for strategies related to roadway segments, 

intersections, interchanges, special facilities, and road networks.

With respect to the development and analysis of alternatives, Part B is used to 

help guide the diagnosis of safety issues and the countermeasure selection 

process. While safety is currently incorporated in the development and 

analysis of alternatives, a formal safety diagnosis helps to develop more 

targeted strategies to address specific safety issues. Part C and Part D are 

likely the most applicable as SPFs and CMFs are used to quantify and 

compare the safety impacts of various alternatives. Part C is used to 

estimate the safety performance of alternatives in terms of crash frequency 

and severity. Readers can refer to the Introduction to Safety Performance 

Functions (6) for more information on SPFs and how they are applied. 

For more information on the use of predictive methods to evaluate 

alternatives, refer to Integrating the HSM into the Highway Project 

Development Process (8). If the application of this approach is beyond 

the expertise of the project team, then they could seek assistance from 

the State Highway Safety Engineer (or equivalent) or the FHWA Division 

Office. 

Crash Modification Factors Clearinghouse

The CMF Clearinghouse (9) is a web-based database of CMFs with 

supporting documentation to help users identify the most appropriate 

countermeasure for their safety needs. Four of the seven methods 

presented in the previous section rely on CMFs and the CMF 

Clearinghouse is a good source for this information. Users can 

search the site for applicable CMFs or submit CMFs to be included 

in the clearinghouse. The CMF Clearinghouse includes all CMFs 

from the HSM and many others. While the CMF Clearinghouse 

provides a wealth of information related to CMFs, sound 

engineering judgment is paramount to selecting an appropriate 

value, particularly when there are multiple CMFs for a given 

treatment. Readers can refer to the Introduction to Crash 

Modification Factors (5) for further guidance on selecting an 

appropriate CMF. Challenges and opportunities related to the 

applicability of CMFs are also discussed later in this document 

in the section titled: Overcoming Potential Challenges.
11

Interactive Highway Safety Design Model 

The Interactive Highway Safety Design Model (IHSDM) is a decision-support tool 

that provides a suite of analysis modules for evaluating the safety and operational 

impacts of geometric design decisions (10). The predictive methods from Part 

C of the HSM are included in this free software to help users estimate the safety 

performance of an existing or proposed facility. Predictive methods are available 

for rural two-lane highways, rural multilane highways, urban/suburban arterials, 

and mainline freeway segments. A calibration tool is also available to assist users 

in implementing the calibration procedures described in Part C of the HSM. 

Other modules allow users to check existing or proposed highway designs against 

relevant design policy values, assess design consistency, conduct detailed 

intersection design reviews, analyze traffic operations, and simulate driver and 

vehicle factors for two-lane roads.

Interchange Safety Analysis Tool Enhanced

The Interchange Safety Analysis Tool Enhanced (ISATe) is a decision-support 

tool that provides the ability to estimate the safety impacts of design 

decisions related to interchanges (11). The tool was developed as part of 

a larger research effort under the National Cooperative Highway Research 

Program (NCHRP) Project 17-45, Enhanced Safety Prediction Methodology 

and Analysis Tool for Freeways and Interchanges, to develop predictive 

methods for freeways and interchanges to be included in future editions of 

the HSM. The ISATe tool can help users implement the predictive methods 

for freeway segments, ramps, and ramp terminal intersections. 

Selecting an Appropriate Method

It is important to select an appropriate method to assess the safety 

impacts during the development and analysis of alternatives. The 

selection of an appropriate method is based on the complexity of the 

decision at hand and the availability of required inputs. It does not 

depend on the specific phase of the project development process. For 

example, the preferred method is to estimate crashes based on the 

Expected Crash Frequency with CMF Adjustment; however, this 

method requires an applicable crash history and would not apply 

to new construction projects. As another example, the Relative 

Comparison of CMFs may not be appropriate when there are 

substantial differences in the fundamental characteristics of the 

alternatives (e.g., different area type, number of lanes, and/or traffic 

volume). In such cases, it is necessary to conduct a more detailed 

analysis, preferably using expected crashes with or without CMF 

adjustment. The following table is provided to help users select an 

appropriate method for quantifying safety impacts.
12

Sample 

Scenario 1

Compare the safety impacts 

of alternatives with differences

in design elements 

(e.g., shoulder width)

Sample 

Scenario 2

Question 1

Is an applicable crash history 

available to estimate the observed 

crashes for future conditions 

without treatment?

Is an applicable SPF available 

to estimate predicted crashes 

for baseline conditions?

Is an applicable CMF available to 

estimate the safety impact of the 

differences in the design elements 

(e.g., different shoulder widths)?

Go to Expected Crash Frequency 

with CMF Adjustment 

Question 2

Is an applicable crash history 

available to estimate the observed 

crashes for future conditions 

without treatment?

Is an applicable SPF available to 

estimate predicted crashes for the 

conditions of interest (e.g., does 

the SPF include a variable for 

shoulder width)?

Go to Expected Crash 

Frequency below

Question 3

Is an applicable SPF available to 

estimate predicted crashes for 

baseline conditions?

Is an applicable CMF available to 

estimate the safety impact of the 

differences in the characteristics 

of the facility type of interest (e.g., 

is a CMF available for converting 

a four-lane road to a three-lane 

road with two-way left-turn lanes)?

Go to Predicted Crash 

Frequency with 

CMF Adjustment 

Expected Crash Frequency 

with CMF Adjustment

Process Compute the predicted 

crashes for baseline conditions and 

multiply by the applicable CMFs to 

estimate the predicted crashes for the 

conditions of interest. The expected 

crash frequency is then estimated 

using the Empirical Bayes approach.

Applicability1 Simple and 

Complex Scenarios

Expected Crash 

Frequency

Process Compute the predicted 

crashes for the conditions of 

interest. The expected crash 

frequency is then estimated using 

the Empirical Bayes approach.

Applicability1 Simple and 

Complex Scenarios

Predicted Crash Frequency 

with CMF Adjustment

Process Compute the predicted 

crashes for baseline conditions and 

multiply the predicted crashes by 

the applicable CMFs to estimate the 

predicted crashes for the conditions 

of interest.

Applicability1 Simple and 

Complex Scenarios

If NO, go to 

Question 3 YES

If NO, go to 

Question 5 YES

If NO, go to 

Question 2 YES

If NO, go to 

Question 3 YES

If NO, go to 

Question 5 YES

If NO, go to 

Question 3 YES If NO, go to 

Question 4 YES

Notes: 1. Simple scenarios include those with minor differences in the overall characteristics of the alternatives (e.g., same area 

type, number of lanes, and traffic volume). Complex scenarios include those with substantial differences in the overall 

characteristics of the alternatives (e.g., different area type, number of lanes, and/or traffic volume).
13

Compare the safety impacts of 

alternatives with different overall 

characteristics (e.g., existing four-lane 

undivided segment and proposed 

three-lane segment with two through 

lanes and a two-way left-turn lane)

Sample 

Scenario 3

Compare the safety impacts of 

alternatives with different safety 

treatments (e.g., shoulder widening 

and shoulder rumble strips)

Question 4

Is an applicable SPF available to 

estimate the predicted crashes for 

the conditions of interest (e.g., does 

the SPF include a variable for number 

of lanes and median type)?

Go to Predicted 

Crash Frequency 

Question 5

Is an applicable crash history 

available to estimate the observed 

crashes for baseline conditions 

(without either treatment)?

Are applicable CMFs available to 

estimate the safety impacts of the 

conditions of interest 

(e.g., shoulder widening 

and shoulder rumble strips)?

Go to Observed Crash 

Frequency with CMF Adjustment

Question 6

Are applicable CMFs available to 

estimate the safety impacts of 

the conditions of interest 

(e.g., shoulder widening and 

shoulder rumble strips)?

Go to Relative Comparison 

of CMFs

Predicted Crash 

Frequency

Process Compute the predicted 

crashes for the conditions of interest.

Applicability1 Simple and 

Complex Scenarios

Observed Crash Frequency 

with CMF Adjustment

Process Compute the observed 

crashes for baseline conditions 

and multiply the observed crashes 

by the applicable CMF to estimate 

crashes for the two conditions.

Applicability1 Simple Scenarios

Relative Comparison 

of CMFs

Process Compare the CMFs to 

estimate the relative impacts of the 

two conditions.

Applicability1 Simple Scenarios

If NO, go to 

Question 5 YES

If NO, go to 

Question 6 YES

If NO, then it is 

not possible 

to quantify the 

safety impacts 

based on 

these methods

YES

If NO, then it is 

not possible 

to quantify the 

safety impacts 

based on 

these methods

YES
14

APPLICATION OF CMF-RELATED METHODS IN THE DEVELOPMENT AND ANALYSIS OF ALTERNATIVES

There are several opportunities to quantify safety in the development and analysis of alternatives. The 

identification of potential safety issues and development of targeted mitigation measures can be accomplished 

in the identification phase. The actual analysis to quantify and compare safety impacts would occur in the 

evaluation phase. 

This section focuses on the evaluation phase and the application of CMFs to quantify the safety impacts of 

alternatives. Four of the six methods for quantifying safety impacts involve the use of CMFs. As such, the 

remainder of this guide focuses on only those methods that apply CMFs in the development and analysis of 

alternatives as noted below. Examples are provided, followed by a case study and a discussion of opportunities 

to overcome potential challenges.

Specific applications of CMF-related methods are presented below to demonstrate the use of CMFs to quantify 

the safety impacts of alternatives. The first demonstrates the Relative Comparison of Design Alternatives using 

CMFs, which uses CMFs alone to compare the anticipated percent change in crashes for various alternatives. 

The second application, Estimating the Safety Impacts of Design Decisions using Observed Crashes and CMFs, is 

slightly more advanced as CMFs are used within a benefit-cost analysis. The second application demonstrates 

the use of observed crash history to estimate future crashes for baseline conditions and the application of CMFs 

to estimate the change in crashes for design alternatives. The estimated change in crashes is then converted 

to a monetary value based on average crash costs and compared to the project cost to estimate the benefitcost ratio of the alternative. The results can be used to compare the safety performance of alternatives in terms 

of estimated crashes or determine whether or not an enhanced design feature or specific mitigation measure 

is cost-effective. The case studies provide additional examples, including the Expected Crash Frequency with 

CMF Adjustment method. The Predicted Crash Frequency with CMF Adjustment method is a component of the 

Expected Crash Frequency with CMF Adjustment method.

Relative Comparison of Design Alternatives using CMFs 

The following steps can be used to compare the relative safety impacts of various alternatives in the evaluation 

phase when the Relative Comparison of CMFs is identified as an appropriate method.

Step 1: Identify Applicable CMFs for Conditions of Interest

CMFs are first identified for the various conditions of interest. As discussed in the Introduction to Crash 

Modification Factors (5), 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 

(9) 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.

Step 2: Combine CMFs to Estimate Overall Impact of Alternatives

One or more features may vary among alternatives. If there is only one feature of interest that varies among 

alternatives (e.g., presence or absence of rumble strips), then it is not necessary to combine multiple CMFs and 

the user can proceed with Step 3. If there are multiple features that vary among alternatives (e.g., lane and 

shoulder width), then it may be necessary to combine multiple CMFs to represent the overall safety impact of 

each alternative before proceeding to Step 3. As discussed in the Introduction to Crash Modification Factors 

(5), the current practice assumes that CMFs are multiplicative when the CMFs apply to the same crash type 

and severity. It is not appropriate to multiply CMFs that do not apply to the same crash type and severity. More 

information regarding the application of multiple CMFs is available in recent articles (12, 13).

Step 3: Compare CMFs to Quantify Relative Impacts of Alternatives

Once CMFs are identified for the various alternatives and combined as necessary, they can be compared to 

estimate the relative safety impacts. CMFs indicate the expected change in crashes relative to a certain baseline 

condition. For example, a CMF may indicate the expected change in crashes if a roundabout is constructed 

in place of a signalized intersection. In this way, CMFs are used to estimate the benefit of one condition over 

another. The estimated percent change in crashes is equal to 100*(1-CMF). For example, a CMF equal to 0.95 

indicates an expected five percent reduction in crashes.
15

Example: The following example presents a scenario where a project team is developing and evaluating 

alternatives for enhancing the safety and operations of an existing two-way stop-controlled intersection. Two 

alternatives were developed by the study team including a traffic signal and a roundabout. [Note that a traffic 

signal is warranted based on an engineering study.] As part of the evaluation phase, the study team would like 

to estimate the potential safety impacts of the two alternatives. The safety impacts can then be considered in 

conjunction with other factors such as cost and operational impacts. The following table summarizes the 

conditions for the existing intersection and two alternatives identified for the evaluation phase. The intersecting 

roadways are rural, two-lane roads with one approach lane per approach and posted speeds of 45 mi/h.

Scenario Approaches Traffic Control

Existing Design 4 Two-way stop-control

Alternative 1 4 Traffic signal

Alternative 2 4 Single-lane roundabout

It was determined that a relative comparison of CMFs would be an appropriate method for quantifying the 

safety impacts of the alternatives because the required inputs and expertise to apply more rigorous methods 

were not available to the study team. Applicable CMFs were identified from the HSM (7). The following table 

presents the CMFs for each opportunity along with the baseline condition and applicability. [Note that all CMFs 

apply to total crashes at rural, four-legged intersections.]

Alternative CMF Applicable 

Facility Type

Applicable

Crash Type

Applicable

Crash Severity

Convert two-way stop-control 

to traffic signal 0.56 Rural 4-leggedintersection All All

Convert two-way stop-control to 

single-lane roundabout 0.29 Rural 4-leggedintersection All All

Alternative 1 includes changes to only one feature (i.e., traffic control) compared to the existing design. As 

such, it is not necessary to combine CMFs (Step 2). Based on the CMF for installing a traffic signal, Alternative 1 is 

expected to reduce total crashes by 44 percent (100*(1-0.56)) compared to the existing design.

Alternative 2 also includes changes to only one feature (i.e., traffic control) compared to the existing design. 

As such, it is not necessary to combine CMFs (Step 2). Based on the CMF for installing a single-lane roundabout, 

Alternative 2 is expected to reduce total crashes by 71 percent (100*(1-0.29)) compared to the existing design.

Based on the relative comparison of CMFs, it appears that either alternative would enhance safety compared 

to the existing design, but Alternative 2 (single-lane roundabout) is anticipated to have larger safety benefits 

than Alternative 1 (traffic signal). The potential safety impacts can now be considered in conjunction with other 

factors such as cost and operational impacts. 

Estimating the Safety Impacts of Alternative Designs Using Observed Crashes and CMFs 

The previous example is a relatively simple application of CMFs and is useful for estimating the relative safety 

effects of various alternatives or safety strategies. It does not, however, estimate the change in the number of 

crashes or consider the relative cost of the alternatives. If the number of crashes without treatment is estimated, 

then the CMFs can be applied to estimate the change in the number of crashes. The change in crashes can 

then be converted to a monetary value, based on average crash costs, to estimate the value of the benefit 

(or disbenefit). Finally, these costs can be compared to the construction costs to estimate a benefit-cost ratio. 

The following example illustrates this process. Further details on the step-by-step process can be found in the 

companion guide, CMFs in Practice: Quantifying Safety in the Roadway Safety Management Process (14).
Note that several 

methods are available 

for estimating crashes 

without treatment. The 

estimated crash 

frequency without 

treatment should 

correspond with the 

specific crash type and 

severity for which the CMF 

is applicable. If the CMF 

applies to total crashes, then 

one should estimate the 

total annual crashes without 

treatment. If the CMF applies 

to a specific crash type or 

severity, then the annual 

crashes without treatment 

should be computed for that 

crash type or severity. 

16

Example: Continuing with the previous example, suppose now that the project team 

would like to determine if either of the alternatives are cost-effective (i.e., benefit-cost 

ratio greater than 1.0) and, if so, which is more cost-effective. This analysis requires 

an estimate of the benefit and cost of each alternative in terms of a dollar value. 

The following table provides a summary of the construction costs, annual operating 

and maintenance costs, and expected service life for the two alternatives. [Note 

that these costs would be based on average construction costs provided by the 

State or local agency.]

Alternative Construction 

Cost

Annual Operating 

and Maintenance 

Cost

Service Life

Traffic signal $300,000 $10,000 10

Single-lane roundabout $900,000 Negligible 20

The five-year average crash frequency for the existing two-way stop-controlled 

intersection is 10.4 crashes per year. This is used as the estimate of crashes 

without treatment (i.e., no-build scenario). [Note that more rigorous methods 

should be used to estimate crashes without treatment when the required 

inputs are available.] 

The CMFs are applied individually to estimate the crashes for each 

alternative as follows:

Estimated crashes with treatment = CMF * Estimated crashes without 

treatment

Alternative #1: Install traffic signal

Estimated crashes = 0.56 * 10.4 crashes per year = 5.8 crashes/year

Alternative #2: Install single-lane modern roundabout

Estimated crashes = 0.29 * 10.4 crashes per year = 3.0 crashes/year

The estimated change in crashes per year is calculated as the 

estimated crashes with treatment minus the estimated crashes without 

treatment. For the traffic signal, the estimated change in crashes is 4.6 

crashes per year (10.4 crashes per year minus 5.8 crashes per year). 

For the roundabout, the estimated change in crashes is 7.4 crashes 

per year (10.4 crashes per year minus 3.0 crashes per year). 

The dollar value of the annual safety benefit is then computed by 

multiplying the change in crashes per year by the average cost of 

a crash. Many agencies have developed or adopted their own 

crash costs, but national estimates are also available such as those 

provided by FHWA (15). The HSM (7) also provides comprehensive 

crash costs by severity level, which are based on the data from 

the FHWA report, Crash Cost Estimates by Maximum PoliceReported Injury Severity within Selected Crash Geometries (15). 

In this case, total crashes were analyzed so the average cost 

of all crashes is used. The average cost of a crash, including 

all types and severities, is $32,236 (15). [Note that crash costs 

vary by type and severity and different costs would apply if 

the analysis was based on specific crash types or severities. If 

possible, the analyst should use local crash costs by severity 
17

level.] For the traffic signal, the annual benefit is $148,286 (4.6 crashes per year times $32,236 per crash). For the 

roundabout, the annual benefit is $238,546 (7.4 crashes per year times $32,236 per crash).

The present value is computed for each treatment using the following equation. This scenario assumes an 

inflation rate of three percent, and a service life of 10 years for the traffic signal and 20 years for the roundabout. 

In the following equation, (A) is the annual benefit or disbenefit, (i) is the inflation rate, and (n) is the service life.

Present Value = A * ----------------------

(1 + i)n - 1

i * (1 + i)n

The present value of the safety benefits of installing a traffic signal is computed as follows:

Present Value of Traffic Signal = $148,286 * ---------------------------------------- = $1,264,910 (1 + 0.03)10 - 1

0.03 * (1 + 0.03)10

The present value of the safety benefits of constructing a roundabout is computed as follows:

Present Value of Roundabout = $238,546 * ---------------------------------------- = $3,548,962 (1 + 0.03)20 - 1

0.03 * (1 + 0.03)20

The benefit-cost ratio is computed as the present value of the benefits divided by the present value of the total 

project costs. The total project costs include the construction cost plus the present value of annual operating 

and maintenance costs. Using the equation above, the present value of the annual operating and maintenance 

cost of the traffic signal is $85,302. For the traffic signal, the benefit-cost ratio is 3.3 ($1,264,910 / $385,302). For the 

roundabout, the benefit-cost ratio is 3.9 ($3,548,962 / $900,000). From this analysis, it is shown that both treatments 

are economically justified (benefit-cost ratio greater than 1.0) and the roundabout is more cost-effective (i.e., 

greater improvement per dollar spent) than the traffic signal. Note that this example focused on total crashes 

and the results may be different if the analysis focused on fatal and injury crashes.

CASE STUDIES

CMFs can be applied in the development and analysis of alternatives to estimate the safety performance when 

the advantages and disadvantages of each alternative are considered. The following case studies illustrate how 

CMFs have been applied by the Colorado Department of Transportation (CDOT) and the Arizona Department of 

Transportation (ADOT) in the development and analysis of alternatives.

Case Study #1: Evaluating Alternatives using Observed Crash Frequency with CMF Adjustment

The following case study illustrates how the Observed Crash Frequency with CMF Adjustment method has been 

used to assess the safety impact of alternatives. Information for the case study was provided by CDOT.

Project Description

Castle Rock, Colorado lies south of Denver along the Interstate 25 corridor. To accommodate growing 

development in the area, CDOT considered a new interchange on I-25. In addition to the “no build” scenario, they 

considered two alternatives for the new interchange design (see Figure 1). Alternative 1 would extend one road, 

Castlegate Drive, to create the new interchange. Alternative 2 would extend another road, Atrium Drive, to create 

the new interchange.
18

Alternative 1 (Castlegate Dr extended to I-25) Alternative 2 (Atrium Dr extended to I-25)

Figure 1. Study Area for Alternatives 1 and 2 (16)

As part of the environmental assessment of the project in 2009, CDOT conducted a safety analysis to evaluate 

the effect on crashes for the proximate roadway segments and intersections, including ramp junctions. The full 

safety analysis developed estimates of crash predictions for each segment and junction based on either SPFs 

(for segments) or comparisons to similar intersections in the area (for intersections). At the time of the analysis, 

CDOT did not have available SPFs for intersections. 

Practical Application of CMFs

This case study focuses on two alternative designs for the junction of the I-25 southbound ramp with Castlegate 

Drive and Atrium Drive. The following explains the process used to generate the safety predictions for the two 

alternatives.

Step 1 – Identify Alternatives

The two alternatives are presented in Table 1. In Alternative 1, the southbound ramp from I-25 would intersect with 

Castlegate Drive at a one-way stop-controlled intersection. In Alternative 2, due to the angle of the approaches, 

the southbound ramp from I-25 would intersect Atrium Drive at a roundabout. 

Table 1. List of Alternatives

Alternative Location Intersection Type

1 Castlegate Drive One-way stop-control

2 Atrium Drive Roundabout

Step 2 – Estimate Traffic Volumes

CDOT estimated total intersection volume for the build-out year of 2030 based on trip generation and distribution 

models. For both alternatives, the projected volume is 25,000 – 30,000 vehicles per day.

Step 3 – Estimate Base Annual Crash Frequency

CDOT estimated the base annual crash frequency at the ramp junction intersection for both alternatives. As 

noted above, intersection SPFs were not available at the time of the analysis. Instead, the crash frequency without 

treatment was estimated from the observed crash histories of nearby intersections that were similar in terms of 

roadway type and traffic volume. The base annual crash frequency was estimated to be 1.0 to 2.0 crashes per 

year. A range was used to indicate the potential variability in the results. 
19

Step 4 – Apply CMF

The intersections used to estimate the base crash frequency were all stop-controlled 

intersections. As such, the results from Step 3 provided an estimate of the annual 

crash frequency for Alternative 1 (stop-controlled intersection), but not for 

Alternative 2 (roundabout). To estimate the annual crashes for Alternative 2 

(roundabout), CDOT applied a CMF of 0.5 to adjust the base crash frequency 

from Step 3. The CMF applies to total intersection crashes. Table 2 presents a 

summary of the two alternatives and the estimated annual crash frequency for 

the build-out year 2030. In this case, Alternative 2 (roundabout junction) appears 

to be more favorable than Alternative 1 (stop-controlled junction) with respect to 

safety for the I-25 southbound ramp junction.

Table 2. Estimated Annual Crash Frequency

Alternative Intersection Type

Estimated Crashes

per Year

(Base Estimate)

CMF

Total Crashes

per Year

(Adjusted Estimate)

1 One-way stop-control 1.0 – 2.0 N/A 1.0 – 2.0

2 Roundabout 1.0 – 2.0 0.5 0.5 – 1.0

Source: Gan, A., Shen, J., and Rodriguez, A., “Update of Florida Crash Reduction Factors and Countermeasures to Improve the 

Development of District Safety Improvement Projects.” Florida Department of Transportation, (2005).

For more information about the case study, please contact Colorado 

Department of Transportation, Safety and Traffic Engineering Branch, 

303-757-9662. 

Summary of Key Findings

This case study presented an example of how CMFs can be applied to 

estimate the safety impacts of various alternatives. The safety analysis 

presented in this case study was just one piece of the overall safety 

analysis conducted for the proposed interchange alternatives. In 

addition to the safety analysis of the alternative junction types, CDOT 

developed crash estimates for each segment and intersection 

within the study area. The result was an estimate of annual crashes 

for the entire study area for Alternatives 1 and 2. The estimated safety 

performance of each alternative can then be considered with the 

operational performance, project costs, environmental impacts, and 

other factors to identify a balanced design and the most desirable 

alternative.

Case Study #2: Evaluating Alternatives using Predicted Crash 

Frequency with CMF Adjustment

The following case study illustrates how the Expected Crash 

Frequency with CMF Adjustment method has been used to quantify 

the safety impacts during the development and analysis of 

alternatives. Information for the case study was provided by ADOT.

ADOT is performing predictive analyses following the procedures 

in the AASHTO Highway Safety Manual (7) at the scoping and 

alternative selection stage of demonstration projects. They are 

working to develop a framework for integrating substantive 

safety considerations into the ADOT project planning and 

development process.
20

Project Description

ADOT identified potential safety improvements on a 24.6 mile section of Arizona State Route 264 (SR 264) and 

evaluated the potential safety impacts during the analysis phase of the development and analysis of the 

alternatives. SR 264 is a rural, two-lane road in northeastern Arizona and functionally classified as a minor arterial. 

Figure 2 identifies the general location and limits of the study section. 

Figure 2. SR 264 Section of Interest (17)

The existing roadway is characterized by a narrow cross-section with 12-ft lanes, 1-ft or less paved shoulders, and 

intermittent turn lanes and passing lanes. The traffic volume for 2010 ranged from 4,100 to 6,400 within the study 

section. Proposed improvements included widening the shoulder, adding centerline and shoulder rumble strips, 

adding delineators and recessed pavement markers, flattening side slopes, installing guardrail, and extending 

drainage structures. It was determined that all improvements would be implemented, but the optimal shoulder 

width was in question. As such, ADOT considered two alternatives with different shoulder widths.

ADOT considered a 20-year scenario (2016-2036) and the study section was divided into homogenous 

segments for analysis. A homogeneous segment has similar roadway, roadside, and operational characteristics.

For example, a new segment would be created where there was a change in traffic volume. The segmentation 

resulted in 242 homogenous segments. Each of the segments was analyzed separately and the results 

were combined to estimate the safety performance of the entire study section under the various conditions. 

For this case study, the calculations are shown for the first tangent segment and the results are summarized 

for the study section as a whole. The 2016 baseline conditions and proposed alternatives for Segment 1 

are summarized in Table 3 as per the conditions considered in the HSM Part C Predictive Methods for Rural 

Two-Lane Two-Way Roads (7). Notable differences among the scenarios of interest include the following:

• Shoulder width: The 2016 baseline condition would include 1-ft paved shoulders while the two alternatives 

would include 5-ft and 8-ft paved shoulders, respectively.

• Presence of centerline rumble strips: The 2016 baseline condition would not include centerline rumble stripes 

while the two alternatives would both include centerline rumble stripes.

• Roadside hazard rating: The 2016 baseline condition would have a roadside hazard rating of 6, which is 

characterized by a clear zone width less than or equal to 5 feet, non-recoverable sideslope (1V:2H), and 

exposure to rigid roadside obstacles (offset 0 to 6.5 feet) without guardrail. The two alternatives would both 

include roadside improvements to upgrade the roadside hazard rating to 2, which is characterized by a clear 

zone width between 20 and 25 feet and recoverable sideslope (1V:4H).
IHSDM is a suite of software 

analysis tools for evaluating 

the safety and operational 

effects of geometric design 

elements. IHSDM includes six 

modules, including a Crash 

Prediction Module (CPM) that 

is a faithful implementation 

of the HSM Part C Predictive 

Methods for Rural Two-Lane 

Two-Way Roads. The CPM 

estimates crash frequency and 

severity given a highway’s 

geometric design and traffic 

characteristics.

21

Table 3. Summary of Existing and Alternative Conditions for Segment 1 (Tangent)

Roadway Characteristics 2016 Baseline Alternative 1 Alternative 2

Traffic volume 4,350 4,350 4,350

Length (mi) 0.16 0.16 0.16

Lane width (ft) 12 12 12

Shoulder width (ft) 1 5 8

Shoulder type Paved Paved Paved

Horizontal curve No No No

Grade (%) 0 0 0

Driveway density (driveways/mi) 0 0 0

Centerline rumble strips (yes/no) No Yes Yes

Passing lanes (1 lane / 2 lanes / no) No No No

Two-way left-turn lane (yes/no) No No No

Roadside hazard rating (1-7 scale) 6 2 2

Segment lighting (yes/no) No No No

Auto speed enforcement (yes/no) No No No

Practical Application of Expected Crash Frequency with CMF Adjustment

For this analysis, ADOT utilized the HSM Part C Predictive Methods for 

Rural Two-Lane Two-Way Roads. ADOT employed the Interactive Highway 

Safety Design Model (IHSDM) to carry-out the computations for the 

various scenarios (10). 

Using the predictive method, a user specifies an SPF for baseline 

conditions and applies CMFs to adjust the baseline prediction to reflect 

other conditions of interest. In this case, the SPF for baseline conditions 

is given by Equation {1} and the baseline conditions are summarized 

above in Table 3 (7).

NSPF = AADT * L * 365 * 10-6 * e-0.312 {1}

Where:

NSPF = Predicted total crash frequency for baseline conditions.

AADT = Annual average daily traffic volume (vehicles per day). 

L = Segment length (mi).

Applying Equation {1} to the existing conditions with an AADT of 

4,350 vehicles per day and a segment length of 0.16 miles, the 

predicted total crash frequency for the baseline conditions is 

computed as follows:

NSPF = 4,350 * 0.16 * 365 * 10-6 * e-0.312

NSPF = 0.19 crashes per year

CMFs were then identified to reflect the conditions of interest. 

The HSM Part C Predictive Method for Rural Two-Lane 

Two-Way Roads provides specific CMFs for use with the SPF from 

Equation {1}. The CMFs are provided in Table 4 (7).
Note that CMFs should only 

be multiplied if they apply 

to the same crash type and 

severity. In this case, all CMFs 

apply to total crashes.

22

Table 4. Summary of CMFs for Conditions of Interest for Segment 1

Roadway Characteristics 2016 Baseline Alternative 1 Alternative 2

Lane width 1.00 1.00 1.00

Shoulder width 1.23 1.04 0.93

Shoulder type 1.00 1.00 1.00

Horizontal curves 1.00 1.00 1.00

Grades 1.00 1.00 1.00

Driveway density 1.00 1.00 1.00

Centerline rumble strips 1.00 0.94 0.94

Passing lanes 1.00 1.00 1.00

Two-way left-turn lane 1.00 1.00 1.00

Roadside design 1.22 0.94 0.94

Lighting 1.00 1.00 1.00

Automated speed enforcement 1.00 1.00 1.00

* Note that Part C of the HSM does not include a CMF for shoulder rumble strips. Instead, an appropriate CMF would be identified and 

applied to the final estimate to reflect the expected safety impacts of the shoulder rumble strips.

The CMFs were then combined to estimate the overall safety impact 

of the conditions of interest. As recommended in the HSM (7), the 

CMFs were multiplied using Equation {2} to estimate the cumulative 

effect of the combined treatments for each scenario.

CMFCombined = CMF1 * CMF2 * ... * CMFn {2}

Where:

CMFi = Crash modification factor for individual roadway characteristic (i).

n = Number of individual roadway characteristics.

The calculations for the combined CMFs are shown below. Note that 

several of the CMFs are 1.00 and are summarized by 1.00 raised to a 

power in the calculations. The combined CMFs for the 2016 

baseline conditions, Alternative 1, and Alternative 2 are 1.50, 0.92, and 

0.82 respectively.

CMFCombined (2016 Baseline) = 1.23*1.22 *1.0010 = 1.50

CMFCombined (Alternative 1) = 1.04*0.94*0.94*1.009 = 0.92

CMFCombined (Alternative 2) = 0.93*0.94*0.94*1.009 = 0.82

The predicted crash frequency for the baseline conditions is 

adjusted with the combined CMFs, using Equation {3} to estimate 

the predicted crashes for the conditions of interest.

NPredicted = NSPF * CMFCombined {3}

Where: NPredicted = Predicted total crash frequency for 

conditions of interest.

Computations for the three scenarios of interest are shown 

below and summarized in Table 5. Note that the baseline 

predicted crashes are identical for the three scenarios.
Note that a calibration 

factor can also be 

applied to account for 

jurisdictional/regional 

variations such as driver 

population, weather, and 

crash reporting. At the time 

of this case study, ADOT 

had not developed a local 

calibration factor. As a result, 

a local calibration factor of 

1.0 was assumed. 

It is preferred to use calibrated 

SPFs for computing predicted 

crashes to compare alternatives 

or to use in an economic 

analysis. Non-calibrated SPFs may 

overestimate or underestimate 

the predicted crash frequency, but 

provide a reasonable estimate of 

the percent difference in crashes 

among alternatives.

23

NPredicted (2016 Baseline) = 0.19* 1.50 = 0.29

NPredicted (Alternative 1) = 0.19 * 0.92 = 0.17

NPredicted (Alternative 2) = 0.19 * 0.82 = 0.16

Table 5. Summary of Computations for Predicted Annual Crashes for Segment 1

Scenario NSPF

Equation {1}

CMFCombined

Equation {2}

NPredicted

Equation {3}

2016 Baseline 0.19 1.50 0.29

Alternative 1 0.19 0.92 0.17

Alternative 2 0.19 0.82 0.16

The predicted crash frequency was computed for each of the 242 

homogeneous segments for each year of the study period (2016 – 2036). 

The predicted crashes were then combined to estimate the total predicted 

crashes for the study section over the 20-year analysis period. Finally, the 

observed crash history was incorporated, using the Empirical Bayes 

method, to estimate the expected number of crashes for the study 

section. Recall that expected crash frequency is a weighted average of 

the observed crash history and the predicted crashes. ADOT conducted 

additional analyses to predict the number of crashes by severity using 

Part C of the HSM. Instead of using crash severity proportions provided in 

the HSM ADOT developed its own proportions using crash data from 

similar roadways within the Navajo Nation and Hopi Tribal land. 

Table 6 presents a summary of expected crashes for the baseline 

conditions and alternatives.

Table 6. Expected Crashes by Severity for SR 264 Study Section from 

2016-2036

Crash Severity 2016 Baseline Alternative 1 Alternative 2

Total crashes 636.38 531.58 504.16

Fatal and injury 

crashes 283.40 230.45 216.80

Property 

damage only 

crashes

352.98 301.13 287.36

Based on the expected crashes, both alternatives are expected 

to perform better than the baseline conditions. Alternative 1 is 

expected to reduce total crashes by 104.8 crashes over the 20-year 

study period. This represents a 16 percent reduction in expected 

total crashes. Alternative 2 is expected to reduce total crashes by 

132.2 crashes over the 20-year study period. This represents a 21 

percent reduction in expected total crashes. 

A formal benefit-cost analysis was conducted to determine 

whether or not the additional shoulder width for Alternative 2 

was worth the added project cost. The benefits were estimated 

by converting the crash savings to a dollar value based 

on average crash costs used by ADOT and FHWA Arizona 

Division. The benefit-cost ratio for Alternative 1 was 2.30 and 

the benefit-cost ratio for Alternative 2 was 1.90. Note that 

both alternatives have a benefit-cost ratio greater than 1.0, 
“Arizona DOT has 

found that using a 

predictive method 

with SPFs and CMFs on 

cases like this alternatives 

analysis is more 

reliable for estimating 

quantitative safety 

performances of future 

scenarios. SPFs give us a 

tool to predict the future 

safety performance of 

a facility without relying 

strictly on the past 3-5 years 

of crash data. We have also 

combined the SPF predictions 

with actual crash history 

using the Empirical Bayes 

method to estimate the 

expected crashes for a given 

facility. We have been using 

crash reduction factors for 

over 10 years [and CMF 

Clearinghouse since 2011], and 

we have recently begun to 

integrate the HSM predictive 

methods in our safety projects.” (18)

24

indicating that either option will provide a positive return on investment. Without 

funding constraints, the preferred alternative would be to widen the roadway to 

8-foot shoulders as it would result in the largest reduction in crashes. However, given 

the number of miles of highway in need of improvement and a limited budget, it 

was determined that Alternative 1 is the preferred option as it maximizes the return 

on each dollar spent.

For more information about the case study, please contact Kohinoor Kar, 

Arizona Department of Transportation; Transportation Safety Engineer;

kkar@azdot.gov; 602-712-6857.

Summary of Findings

This case study presented an example of how the Expected Crash Frequency 

with CMF Adjustment method can be used to estimate the expected safety 

impacts of various design alternatives. ADOT used SPFs and CMFs from the 

HSM in this analysis, supported by the IHSDM software. They also incorporated 

observed crash history, using the Empirical Bayes method, to estimate the 

expected crashes for various scenarios. The result was an estimate of total 

expected crashes for the entire study section over a 20-year analysis period. 

This allowed for a quantitative comparison of the safety performance for two 

design alternatives and the existing conditions. ADOT used the results of the 

crash analysis in a benefit-cost analysis to help select the most cost-effective 

alternative.

OVERCOMING POTENTIAL CHALLENGES

Potential challenges may arise when quantifying safety in the 

development and analysis of alternatives. Some are directly related 

to limitations in the progress of safety research, while others apply 

to a lack of training. General challenges related to limitations in the 

progress of safety research include availability of CMFs, applicability 

of CMFs, and estimating the effects of multiple treatments. Specific 

challenges related to the quantification of safety in the development 

and analysis of alternatives include insufficient expertise (i.e., 

understanding how to select and apply appropriate methods) and 

complex scenarios.

Availability of CMFs

A general challenge is the availability of CMFs for specific 

countermeasures. The CMF Clearinghouse (9) 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 following table provides a summary of the design 

elements and mitigation measures for which the safety 

impacts can be assessed using the predictive method and 

CMFs in Part C of the HSM. Other CMFs are available in the 

CMF Clearinghouse (9) and recently completed research 

studies such as NCHRP Project 17-45 (11). Additional research is 

underway to develop CMFs for other design elements and 

facility types where CMFs are currently unavailable. For 

example, NCHRP Project 17-53, Evaluation of the 13 
25

Controlling Criteria for Geometric Design, is developing CMFs to help fill-in current gaps for several of the priority 

design criteria. 

The CMF Clearinghouse (9) 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.

Design Element Rural 

2-Lane

Rural 

Multilane

Urban/Suburban

Arterials

Segments

Lane Width

Shoulder Width

Shoulder Type

Horizontal Alignment

Vertical Alignment

Driveway Density

Centerline Rumble Strips

Passing Lanes

Short Four-Lane Section

Two-Way Left-Turn Lane

Roadside Hazard Rating

Lighting

Automated Speed Enforcement

Median Type

Median Width

Side Slopes

On-Street Parking

Number of Lanes

Roadside Fixed-Objects

Intersections

Number of Intersection Legs

Traffic Control Type

Intersection Skew Angle

Left-Turn Lanes

Right-Turn Lanes

Lighting

Left-Turn Phasing

Right-Turn on Red

Red Light Cameras

Bus Stops

Schools

Alcohol Sales Establishments
CDOT indicated that 

CMFs are typically 

obtained from FHWA 

resources such as the 

CMF Clearinghouse, 

the Desktop Reference 

for Crash Reduction 

Factors, information 

packets on specific 

features like roundabouts, 

and case studies. They 

have also used these 

resources to develop an 

“in-house” list of CMFs for 

common strategies such 

as roundabouts. This 

reduces the effort to search 

for CMFs during the project 

development process and 

also helps to maintain 

consistency among analyses.

Contact information for the FHWA 

field offices is available at: http://

www.fhwa.dot.gov/about/field.cfm.

26

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 

HSM (7) and CMF Clearinghouse (9) 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 strategy 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 anticipated 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 (9) 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 (7) and 

posted on the CMF Clearinghouse (9). 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 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 (12, 13).

Insufficient Expertise

A specific challenge for the project team could be that there is 

insufficient expertise within the team to quantify safety impacts 

using CMFs and related methods. The HSM and related resources 

are relatively new tools. As such, they have only recently gained 

popularity among transportation professionals and their use has 

been mostly limited to applications within the roadway safety 

management process. There are a number of opportunities 

to quantify safety impacts in other aspects of the project 

development process (e.g., development and analysis of 

alternatives), but it may be necessary to solicit input or 

assistance from those who are more familiar with the selection 

and application of CMFs and related methods. If the study 

team does not have the needed expertise, then they can 

solicit outside expertise from the State Highway Safety Engineer 

(or equivalent), FHWA Division Office, or consultants for 

further guidance and assistance with the selection and/or 
CDOT has and 

continues to 

incorporate safety 

estimates in many 

areas of their 

transportation 

planning and 

design processes. 

They continue to 

push forward with 

development of new 

SPFs based on data in 

their state and 

identification of CMFs 

that are useful and 

relevant to their 

operations. David 

Swenka (CDOT, safety and 

traffic engineer), stated 

that “the application of 

CMFs for this assessment 

in concert with other 

prediction models (i.e., 

SPFs) was both a necessary 

and effective way in 

establishing crash projections 

for a multitude of proposed 

alternatives with a variety of 

different geometric 

configurations. We have and 

will continue to rely on the 

credibility that comes inherent 

with accepted CMFs developed 

through empirically based

 research.” (19).

27

application of CMF-related methods 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). 

Complex Scenarios

Another potential challenge is that certain methods (i.e., Relative Comparison 

of CMFs) are not appropriate to analyze complex scenarios. For example, a 

relative comparison of CMFs may not be appropriate when there are significant 

differences among the alternatives (e.g., different area type, number of lanes, 

and/or traffic volume). In these cases, it would be necessary to apply more 

rigorous methods to estimate the safety performance for each scenario 

separately. A decision-support table is provided in the section titled: 

Selecting an Appropriate Method, to help users identify an appropriate 

method for quantifying safety impacts. For more information on predictive 

methods, refer to Part C of the HSM (7) and related documentation, 

Integrating the HSM into the Highway Project Development Process (8).

REFERENCES

1. Meyer, M. and E. Miller, Urban Transportation Planning: A Decision Oriented 

Approach. New York: McGraw-Hill, 2001.

2. Sinha, K. and S. Labi. Transportation Decision Making: Principles of Project 

Evaluation and Programming, Hoboken, New Jersey: John Wiley & Sons, 

2007.

3. Federal Aid Policy Guide. Subchapter G – Engineering and Traffic 

Operations, Part 625 – Design Standards for Highways. Federal Highway 

Administration, Washington, DC, 1997.

4. Gross, F. Crash Modification Factors in Practice: Using CMFs to 

Quantify the Safety Performance of Design Decisions and Exceptions. 

Publication FHWA-SA-13-013, Federal Highway Administration. 

Washington, DC, 2013. Available online at: http://safety.fhwa.dot.

gov/tools/crf/resources/cmfs/.

5. Introduction to Crash Modification Factors. Publication FHWA-SA-13-

015, Federal Highway Administration. Washington, DC, 2013. Available 

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

6. Introduction to Safety Performance Functions. Publication FHWASA-13-016, Federal Highway Administration. Washington, DC, 

2013. Available online at: http://safety.fhwa.dot.gov/tools/crf/

resources/cmfs/. 

7. American Association of State Highway and Transportation 

Officials (AASHTO). Highway Safety Manual, 1st Edition, 

Washington, DC, 2010.

8. Van Schalkwyk, I., Wemple, E.A., and Neuman, T.R. Integrating the 

HSM into the Highway Project Development Process. Publication 

FHWA-SA-11-50, Federal Highway Administration, Washington, 

DC, 2012. Available online at: http://safety.fhwa.dot.gov/hsm/

hsm_integration/hsm_integration.pdf

9. Crash Modification Factors (CMF) Clearinghouse. 

Federal Highway Administration. Available online at: 

www.cmfclearinghouse.org.

10. Interactive Highway Safety Design Model (IHSDM). 

Federal Highway Administration. Available online at: 

http://www.fhwa.dot.gov/research/tfhrc/projects/safety/

comprehensive/ihsdm/softwaredownload.cfm.

11. Bonneson, J., Pratt, M.P., Geedipally, S., Lord, D., Neuman, 
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/

T.R., and Moller, J.A. Enhanced Safety Prediction Methodology and Analysis Tool 

for Freeways and Interchanges, Project 17-45, National Cooperative Highway 

Research Program (NCHRP), Transportation Research Board, Washington, DC. 

ISATe tool and manual available online at: http://www.highwaysafetymanual.

org/Documents/FreewaysInterchanges/ISATe_V06i.xls

12. Gross, F. and Yunk, K. “Crash Modification Factors: An Overview of Its Applications.” 

Public Roads. Federal Highway Administration, Washington, D.C., 2011.

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

Methods for Combining Multiple CMFs. Federal Highway Administration, 

Washington, D.C., 2011. Available online at: www.cmfclearinghouse.org.

14. Gross, F. Crash Modification Factors in Practice: Quantifying Safety in the 

Roadway Safety Management Process. Publication FHWA-SA-13-010, 

Federal Highway Administration. Washington, DC, 2013. Available online at: 

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

15. 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/.

16. North Meadows Extension to US 85 and I-25, Douglas County, Colorado: 

Environmental Assessment. CDOT Project CC 0252-373, Douglas County 

Project CI 05-024, Submitted March 23, 2010. 

17. Traffic Safety Evaluation: Using the Highway Safety Manual and the 

Interactive Highway Safety Design Model SR 264 Burnside Jct. – Summit, 

Arizona Department of Transportation, Intermodal Transportation 

Division, Traffic Safety Section, October 2012 (unpublished).

18. Kar, Kohinoor. Arizona Department of Transportation, Traffic Safety 

Section. Email correspondence, December 2012.

19. Swenka, David. Colorado Department of Transportation, Safety and 

Traffic Engineering Branch, Denver, Colorado. Phone and email 

correspondence, May 2012.

FHWA-SA-13-012