CRASH MODIFICATION FACTORS IN PRACTICE

Using CMFs to Quantify Safety in 

the Value Engineering Process

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

Safety in the Value Engineering Process guide describes and illustrates 

several opportunities to incorporate the latest methods to quantify safety 

in the value engineering (VE) process using CMFs. The target audience 

includes VE program managers, VE study teams, and those supporting 

VE study teams. The purpose of this guide is to help raise awareness of 

opportunities to consider and quantify safety in the VE process, with a 

specific focus on the application of CMFs to support the process. The 

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

steps of the VE 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, 

VE practitioners will be better prepared to evaluate safety-related 

issues and explore opportunities to enhance safety during the VE process.

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 value engineering (VE) process. 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 VE process to understand the importance of 

quantifying safety and using appropriate methods to do so.

A VE study ensures that a project provides the needed functions 

safely, reliably, efficiently, and at the lowest overall cost. The VE review 

and analysis occurs during the concept and/or design phases of 

the project development process and the VE team can provide 

suggestions and recommendations to improve the overall value 

and quality of the project, and reduce the time to complete the 

project. As such, the VE process provides an added opportunity 

to consider safety early in the project development process. It 

also allows the VE team to identify, consider, and recommend 

potential safety enhancements to proactively address safety 

issues before a project is constructed.

Traditionally, safety is a consideration during the VE process, 

but much of the consideration has been qualitative in 

nature. Recently developed methods may allow VE teams to 

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 

Value Engineering Process

7 Methods for Quantifying 

Safety Impacts in the Value 

Engineering Process

18 Application of CMF-Related 

Methods in the Value 

Engineering Process

22 Case Study

28 Overcoming Potential 

Challenges

32 References

2

quantify the safety impacts of various design and operational features. If a VE team 

suggests changes to a specific project element, these methods may help them 

understand the safety implications of those changes and justify their suggestions 

and recommendations. In this way, safety can be considered in conjunction with 

the anticipated operational and environmental impacts. 

Read more for an overview of opportunities to quantify safety in the VE process 

or skip to the section that describes available methods for quantifying safety 

using crash modification factors (CMFs). A decision-support chart is provided to 

help identify when CMF-related methods may be appropriate in the VE process. 

Examples are provided to illustrate how these methods can be applied and a 

case study illustrates how these methods have been applied in a particular 

state to quantify safety impacts in the VE process. Finally, potential challenges 

are presented along with options to overcome common application issues. 

While several examples are provided to demonstrate the basic application of 

CMF-related methods, a VE team may contact their State Highway Safety 

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

Office for further guidance and assistance with the application of these 

methods and the interpretation of results.

OVERVIEW OF SAFETY IN THE VALUE ENGINEERING PROCESS

Value engineering is “a systematic process of review and analysis of a 

project during the concept and design phases by a multidiscipline 

team of persons not involved in the project that is conducted to provide 

recommendations for (1) providing the needed functions safely, reliably, 

efficiently, and at the lowest overall cost; (2) improving the value and 

quality of the project; and (3) reducing the time to complete the project” 

(1). The VE process considers several competing needs, including the cost, 

safety, operations, and environmental impacts. In the concept phase, 

there may be opportunities for large-scale changes in the design. In later 

design stages (e.g., 60-percent design), the major decisions have been 

made, but there are still opportunities to make changes to the project 

elements being designed at the time (i.e., maintenance of traffic, 

constructability, construction phasing, or specific safety strategies).

The multidiscipline VE study team is led by a facilitator through a 

systematic process that allows the team to learn about the project, 

identify high-cost elements of the project, investigate and develop 

potential alternatives, and present recommendations for possible 

incorporation into the project. The VE process typically consists of 

eight phases: 

1. Selection.

2. Investigation.

3. Function Analysis. 

4. Creative.

5. Evaluation.

6. Development. 

7. Presentation. 

8. Closeout/Implementation. 

The following describes the eight-phase process (1), noting the 

opportunities where safety can be considered and quantified. 

By incorporating safety analysis in the VE process, agencies 

can quantify the safety impacts of alternatives and better 

understand the potential effects of the VE team’s suggestions 

and recommendations. The analysis will also demonstrate 
3

that safety was explicitly considered using a quantitative method. This is particularly useful for risk management 

and can help to defend against potential litigation. For example, a VE team may consider several opportunities 

for a given project and select the combination that achieves a reasonable balance between cost, safety, 

operations, and environmental impacts. While additional opportunities may be considered for a given project, 

it is unreasonable to enhance design features or implement additional countermeasures if the potential worth 

does not justify the cost. This is particularly important when resources could be used more cost-effectively on 

another project. 

Selection Phase

The selection phase involves the identification of the project for VE analysis. The responsibility of this task is 

typically outside of the control of the VE study team. Project selection criteria can vary among agencies, but 

may include the following:

• High-cost projects.

• High-priority projects.

• Complex and/or challenging projects.

• Extensive/costly environmental or geotechnical requirements.

• Corridor/route-planning studies.

• Projects involving multiple stakeholders.

Investigation Phase

During the investigation phase, the VE study team reviews available information about the project. The project 

team with knowledge about the project provides background information, identifies challenges, and answers 

any project-related questions for the VE team. Project information should cover all of the primary factors 

including project safety, cost estimates, environmental commitments, design elements, traffic analysis, material 

requirements, and plans.

It is during this phase where the VE team, with the help of the project team, may begin to identify project 

elements (e.g., lanes, shoulders, signs, bridges, and pavement) for further analysis. The VE study team may select 

project elements for further analysis based on factors such as cost, operations, constructability, safety, and other 

project challenges.

Function Analysis Phase

During the first part of the function analysis phase, the VE study team defines the function of each project 

element. The function of each project element is defined using two words—an action verb and a measurable 

noun (that is acted upon). For example, the function of a bridge is to “cross obstacle”, the function of signing is to 

“guide drivers”, the function of pavement is to “improve ride”, and the function of rumble strips is to “alert drivers.”

During the next part of the function analysis phase, the VE study team analyzes project elements to determine 

their cost and worth. The cost is the actual cost to construct and maintain the project element. The worth is the 

least cost way to perform the function of the project element. The three fundamental concepts of VE—function, 

cost, and worth—are then discussed by answering key questions about the overall project and specific project 

elements:

• What is it?

• What must it do (i.e., what is the primary function)? 

• What else does it do (i.e., what are the secondary functions)?

• What does it cost?

• What is it worth?

The value of a project or project element is based on a comparison of the cost and worth. The value of a project 

is reduced if proposed changes to a project element sacrifice the needed function. Functions beyond those that 

are needed are also of little value; hence, the value of a project is increased if unneeded functions are eliminated. 

The objective of the VE team is to develop a design for which the costs closely match the worth. At the conclusion 

of the function analysis phase, the VE team identifies a list of project elements that have the greatest potential 

for value improvement.
The value of project safety improvements may be quantified by determining the cost 

and worth of the proposed improvement(s). The societal worth of a project increases 

when safety is improved by a project element. There is value added to a project when 

the worth of safety improvements is greater than the cost of the improvements. The 

safety-related cost and worth can be quantified in the evaluation phase.

Creative Phase

Once the team determines which project elements should be analyzed for 

improved value, the team looks at the function of each element to generate 

potential opportunities to improve cost, delivery time, quality, and/or 

operations. This is called the “creative” phase because the team uses

brainstorming techniques and an innovative spirit to identify opportunities to 

improve the project elements identified in the previous phase. 

Multiple opportunities may provide the same function, but not at the same 

cost or the same level of safety. For example, the function of a median barrier 

is to “redirect vehicles.” While there are several types of median barriers that 

can provide this function, there are tradeoffs in the relative cost and safety 

performance among the different types of barriers. The opportunities are 

further analyzed in the evaluation phase to determine the relative costs 

and impacts.

Evaluation Phase

During the evaluation phase, each of the opportunities is evaluated to 

determine which should be carried forward as either recommendations 

or suggestions. The advantages and disadvantages of each opportunity 

are evaluated as part of this process. Opportunities are compared on 

a number of project factors, including cost, safety impacts, operational 

performance, environmental impacts, and constructability. 

Safety should be considered as a factor for all applicable project 

elements. Common project elements that impact safety include those 

related to the roadway geometry (e.g., lane and shoulder width), 

traffic operations (e.g., traffic control devices), and roadside design 

(e.g., slope of embankments). For example, a VE team may 

consider shoulder narrowing as an opportunity, focusing on the potential 

advantages related to project costs (reduced cost) and 

environmental impacts (improved worth). However, the VE team 

should realize that shoulder narrowing can impact safety and 

reduce the worth of the project element. Safety should also be 

considered as a factor for project elements that affect 

visibility, guidance, and vehicle performance. For example, the 

selection of materials such as sign sheeting and surface type 

affect visibility, guidance, and vehicle performance (i.e., sign

visibility is dependent on the retroreflectivity provided by the type 

of sign sheeting and vehicle performance is dependent on the 

level of friction provided by the road surface). 

4
The New York State DOT 

conducted a VE Study 

dedicated primarily to 

Work Zone Safety. This study 

varied considerably from 

more traditional VE studies in 

that savings were not measured in dollars, but rather in 

terms of safety considerations 

and enhancements.

5

Example: A VE study was conducted for a bridge replacement project. The existing 

structure was classified as “Structurally Deficient” due to a poor deck rating and 

“Functionally Obsolete” due to inadequate clearance under the bridge. The purpose 

and need of the bridge replacement project is to improve structural deficiencies 

and maintenance needs, eliminate the functionally obsolete condition, and address 

the scour critical needs as well as the roadway geometric deficiencies.

The VE team identified key issues for consideration, including cost ($), environmental 

impacts (E), operational performance (O), constructability (C), likelihood of 

acceptance (LOA), and safety (S). A rating system was developed to assess these 

six factors for each opportunity as shown below.

Rating $ E O C LOA S

3 Significant 

Savings

Significant 

Improvement

Significant 

Improvement

Significant 

Improvement Very Likely Significant Improvement

2 Some 

Savings

Moderate 

Improvement

Moderate 

Improvement

Some

Improvement Likely SomeImprovement

1 No 

Savings

Minor 

Improvement No Change No Change Possible No Change

0 Additional 

Costs

Increased 

Impact

Decreased 

Performance More Complex Unlikely NegativeImpact

The VE team considered 21 opportunities related to the design and 

construction phasing of the bridge replacement. The individual ratings 

for each of the six factors were combined during the evaluation phase 

to compare the relative advantages and disadvantages of each 

opportunity. The following table shows a sample of the 21 opportunities 

and associated ratings. Higher overall ratings do not necessarily reflect 

the best ideas, solutions, or suggestions, but do help to generate 

discussion and support the decision-making process. It is clear that safety 

may not be applicable to all opportunities (e.g., #6: use grid and panel 

system); however, it is important to identify opportunities that negatively 

impact the overall safety performance of the facility (e.g., #3: 

eliminate shoulders on the bridge).

Opportunity $ E O C LOA S Total

1. Reduce outside shoulders from 10’ to 8’ 2 2 1 1 2 0 8

2. Reduce lane width from 12’ to 11’ 2 2 1 1 1 0 7

3. Eliminate shoulders on the bridge 2 3 0 1 0 0 6

4. Deck replacement only 3 3 0 0 1 1 8

5. Close bridge and build new bridge on existing 

footprint (utilizing detours to divert traffic) 3 3 1 0 0 1 8

6. Use grid & panel system – build supports under the 

existing bridge, and remove it in pieces 0 1 1 0 0 1 3

A combination of the overall and individual ratings can be used 

to screen opportunities for further discussion. For example, the 

VE team further considered opportunities that received an 

overall rating of 7 or higher, and a level of acceptance (LOA) 

of at least 1. Using these criteria, they eliminated opportunities 

#3 (eliminate shoulders on the bridge) and #6 (use grid and 

panel system). 
6

The VE team further considered the remaining opportunities to identify an 

alternative that achieves a balance among the six factors. They eliminated 

opportunity #2 (reduce lane width from 12 feet to 11 feet), recognizing that it would 

create an inconsistent design with the approaches (12-ft lanes) and would have a 

negative impact on safety. Opportunity #4 (deck replacement only) was dismissed 

because the structure is scour critical and deck replacement would not address 

the scour issue. Opportunity #5 (close bridge during construction) was dismissed 

for operational reasons (i.e., there are no viable detours available for motorists). In 

the end, Opportunity #1 (reduce outside shoulders from 10’ to 8’) was selected. 

While the reduced shoulder width is associated with a negative safety impact 

compared to the proposed design, it is consistent with the shoulder width on 

the approaches and would result in substantial cost savings and reduced 

environmental impacts due to the 4-ft reduction in total bridge width. 

The evaluation phase is the primary opportunity to employ CMFs and related 

methods and tools to quantify safety impacts in the VE process. The 

application of these methods may allow the VE team to quantify safety 

impacts as they determine and discuss the advantages and disadvantages 

of each opportunity. Safety performance is typically considered as part 

of VE studies but is often based on a qualitative analysis or quantified using 

rough approximations of expected cost savings at the corridor level. 

The CMF-related methods discussed in this guide can be used to more 

rigorously quantify the safety impacts of alternatives. Safety impacts 

(either benefits or disbenefits) can then be converted to a dollar 

value based on average crash costs to help determine the overall 

worth of an opportunity. In this way, safety is quantified and can be 

considered with other factors such as the cost to construct the 

opportunity, operational effects, and environmental impacts.

Development Phase

Once the viable opportunities have been determined, team members 

further develop the recommendations or suggestions in the 

development phase to clearly communicate the concept to 

engineers involved with the project. This includes cost estimates, 

sketches, validation of design elements, documentation of 

assumptions, and other technical work needed to develop 

recommendations. This is the final step before the VE team presents 

its recommendations.

Opportunities to integrate safety in the development phase

include the documentation of safety analyses and consideration 

of potential mitigation measures. If safety is considered as 

a factor in the evaluation phase, then the process and 

results of the safety analysis should be documented in the 

development phase. If the VE team identifies safety-related 

disadvantages in the evaluation phase, then potential mitigation 

measures can be considered at this time. For example, a VE 

team is developing an opportunity to narrow the cross-section, 

including lane and shoulder width, as a means to improve 

the overall value by reducing construction costs (reduce 

cost) and environmental impacts (improve worth). Based on a 

safety analysis conducted in the evaluation phase, the VE 

team recognized that crashes may increase under this

scenario, which is a disadvantage of the opportunity. 

To mitigate the potential negative safety impact, 

Safety should be 

considered not only 

when it is identified 

as a project factor in the 

investigation phase, but 

anytime when a suggested 

change in the design 

impacts the safety of the 

facility.
Note that while there are several 

methods available to quantify 

safety impacts in the VE process, 

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.

7

the VE team is considering shoulder rumble strips during the development of the 

recommended alternative.

Presentation Phase

In the presentation phase, the VE study team presents the findings of 

the analysis and its recommendations to the decision makers. The team 

documents each recommendation or suggestion in a formal report that 

identifies the steps taken to accomplish each phase of the analysis, 

including the team’s discussions and considerations that led to its 

recommendations. If needed, a presentation may also be given to 

ensure proper understanding of the information. The safety analysis can 

play a valuable role in this phase by supporting or justifying the 

suggestions and recommendations of the VE study team. Presenting the 

results of the safety analysis in conjunction with the other factors 

will demonstrate the thought process used to determine the final 

suggestions and recommendations, which will help decision-makers to fully 

understand the alternatives developed by the VE team and the potential 

impact on the safety of the project.

Closeout/Implementation Phase

In the closeout phase, the project decision-makers consider each 

recommendation from the VE analysis and decide on the appropriate 

action. The estimated safety performance, along with other factors, 

can help guide these decisions and manage the risk of potential 

litigation. While it is not always feasible or reasonable to select the 

alternative or design features that result in the highest level of safety 

performance, it is important to justify why they are not selected. 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. After 

approved recommendations have been incorporated into the 

project, an evaluation should be conducted to determine the actual 

cost savings.

METHODS FOR QUANTIFYING SAFETY IMPACTS IN THE VALUE 

ENGINEERING PROCESS

There are several opportunities to identify and address safety 

impacts in the VE process. This section focuses on the Evaluation 

Phase and identifies several methods and related tools that can 

be used to compare the safety impacts of various opportunities 

or project elements. Safety impacts are quantified by 

estimating the extent to which each opportunity 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: CMFs, safety performance function (SPF), observed 

crash frequency, predicted crash frequency, and expected 

crash frequency. Engineering judgment is an essential 

component of each method. These terms are defined below, 
8

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 each method. 

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 (2).

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 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 for more information 

on SPFs and how they are applied (3).

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 crash history 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).
X

Area type defines 

the general 

characteristics 

of the surrounding 

environment as 

rural, suburban, 

or urban.

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 crash history 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., regression-to-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 opportunities 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 VE process. 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 element. For 

example, a CMF may be identified for the radius of curve and 

used to estimate the percent change in crashes when the 

9
X

radius is changed from 300 to 400 feet. CMFs are also used to compare the relative 

safety benefits of potential mitigation measures when selecting a strategy to 

address an identified safety issue. For example, CMFs may be identified 

for shoulder widening and shoulder rumble strips to determine which would 

likely be more effective in reducing total crashes. A numerical example is 

provided later in this document in the Relative Comparison of Opportunities 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 opportunities 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 opportunities 

of interest. The results can be used to compare the safety performance for 

opportunities of interest 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 element 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 for opportunities of 

interest. 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 Opportunities using 

Observed Crashes and CMFs section, comparing the safety 

effectiveness of shoulder widening and shoulder rumble strips. 

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).

10
X

Predicted Crash Frequency

This method is used to estimate the crash frequency for opportunities of interest. 

The results can be used to compare the safety performance for opportunities of 

interest 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.

• 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 shoulder width 

if this was a design feature related to an opportunity. 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 opportunities 

of interest. The results can be used to compare the safety performance 

for opportunities of interest 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 shoulder width. The SPF would be used to 

estimate the predicted crashes for baseline conditions and 

CMFs would be applied to estimate the impacts of different 

shoulder widths.

11
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 opportunities 

of interest. The results can be used to compare the safety performance 

for opportunities of interest 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.

• 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 shoulder width if this was a design feature related to an 

opportunity. 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.

12
13

Expected Crash Frequency with CMF Adjustment

This method is used to estimate the crash frequency for opportunities of interest. The results can be used to 

compare the safety performance for opportunities of interest 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. 

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 • • • •
Contact information for the FHWA 

field offices is available at: http://

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

14

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 VE process. 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 state-of-the-art in highway safety analysis (4). 

The knowledge and methods included in the HSM may allow users to explicitly 

consider and quantify safety in the VE process. The HSM includes four parts as 

follows:

• 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 VE process, Part B is used to help guide the diagnosis 

of safety issues and the countermeasure selection process; however, 

this is already incorporated in the traditional VE approach. 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 

opportunities. Part C is used to estimate the safety performance of 

alternatives in terms of crash frequency and severity, but this may 

be beyond the expertise of a typical VE study team. Readers can 

refer to the Introduction to Safety Performance Functions (3) for 

more information on SPFs and how they are applied. For more 

information on the use of predictive methods to evaluate 

opportunities, refer to Integrating the HSM into the Highway 

Project Development Process (5). If it is necessary to conduct this 

type of analysis, the VE study team could seek assistance from 

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

Division Office.
15

Crash Modification Factors Clearinghouse

The CMF Clearinghouse (6) 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 (2) 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. 

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 (7). 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 (8). 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 VE process. 

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.
16

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).
17

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
18

APPLICATION OF CMF-RELATED METHODS IN THE VALUE ENGINEERING PROCESS

There are several opportunities to integrate safety in the VE process. The identification and development of 

safety opportunities can be accomplished during the investigation, function analysis, creative, evaluation, and 

development phases. The actual analysis to compare or quantify safety impacts would occur in the evaluation 

and development phases. 

This section focuses on the application of CMFs to quantify the safety impacts of specific project elements during 

the evaluation phase of a VE study. 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 VE process as noted 

below. Specifically, it focuses on the quantification of safety in the evaluation phase when safety is a project 

factor and crash frequency and/or severity is the performance measure. 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 opportunities in the evaluation phase. The first demonstrates the Relative Comparison 

of Opportunities using CMFs, which uses CMFs alone to compare the anticipated percent change in crashes 

for various opportunities. 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 a given opportunity. 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 benefit-cost ratio of the opportunity. The results can be used to compare the safety performance 

of opportunities in terms of estimated crashes or determine whether or not an enhanced design feature or 

specific countermeasure is cost-effective. The case study provides an additional example, featuring the 

Predicted Crash Frequency with CMF Adjustment method. For more information on the Expected Crash 

Frequency with CMF Adjustment method, refer to Part C of the HSM (4) and related documentation, Integrating 

the HSM into the Highway Project Development Process (5).

Relative Comparison of Opportunities using CMFs

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

phase when:

• Safety is identified as a project factor.

• The opportunity is relevant (i.e., CMF is available for the opportunity). 

• The relative comparison of CMFs is 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 (2), 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

(6) 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 

(2), 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 (9, 10).

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 
19

condition. For example, a CMF may indicate the expected change in crashes if lighting is installed compared to 

the condition without lighting. 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.

Example: The following example presents a scenario where a VE study team is considering various alternatives 

to reduce the time and cost associated with a reconstruction project on a rural two-lane road. The length of the 

study section is one mile and the annual average daily traffic is 15,000 vehicles per day. The proposed design 

includes 11-ft lanes and 4-ft shoulders, which would require the acquisition of additional right-of-way. The VE study 

team identified opportunities to reduce the time and cost of the project by keeping all work within the existing 

right-of-way. The primary opportunity is to maintain the existing shoulder width, which is defined as “shoulder 

narrowing” compared to the proposed design. Understanding that shoulder narrowing may impact the overall 

safety performance, the VE study team also considered shoulder rumble strips as an opportunity to mitigate 

potential safety impacts. As part of the evaluation phase, the VE study team would like to quantify the potential 

safety impacts of shoulder narrowing with and without rumble strips compared to the proposed design. The safety 

impacts can then be considered in conjunction with other project factors such as time and cost. The following table 

summarizes the conditions for the proposed design and two opportunities identified for the evaluation phase.

Scenario Lane Width (ft) Shoulder Width (ft) Presence of Shoulder 

Rumble Strips

Proposed Design 11 4 No

Existing Design 11 2 No

Alternative Design 11 2 Yes

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

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

were not available to the VE study team. Applicable CMFs were identified from the HSM (4) and CMF 

Clearinghouse (6). The following table presents the CMFs for each opportunity along with the baseline condition 

and applicability. [Note that all CMFs apply to total crashes on rural, two-lane roads.]

Opportunity CMF Baseline

Condition

Applicable

Facility Type

Applicable

Crash Type

Applicable

Crash Severity

Reduce 

shoulder width 

(4 ft to 2 ft)

1.071 4-ft shoulder Rural 2-Lane All All

Install shoulder

rumble strips 0.852 No rumblestrips Rural 2-Lane All All

1 American Association of State Highway and Transportation Officials (AASHTO). Highway Safety Manual, 1st Edition, Washington, DC, 2010.

2 Torbic, D.J., Hutton, J.M., Bokenkroger, C.D., Bauer, K.M., Harwood, D.W., Gilmore, D.K., Dunn, D.K., Ronchetto, J.J., Donnell, E.T., Sommer III, 

H.J., Garvey, P., Persaud, B., and Lyon, C. Guidance for the Design and Application of Shoulder and Centerline Rumble Strips. National 

Cooperative Highway Research Program (NCHRP) Report 641, Transportation Research Board, Washington, DC, 2009. Also available online 

from the CMF Clearinghouse: http://www.cmfclearinghouse.org/detail.cfm?facid=3516. 

The first opportunity (existing design) includes changes to only one feature (i.e., shoulder width) compared to the 

proposed design. As such, it is not necessary to combine CMFs (Step 2). Based on the CMF for shoulder narrowing, 

the existing design (shoulder narrowing without rumble strips) is expected to increase crashes by seven percent 

(100*(1-1.07)) compared to the proposed design. 

The alternative design includes changes to two features (i.e., shoulder width and rumble strips) compared to the 

proposed design. As such, it is necessary to combine the CMFs (Step 2) before comparing safety impacts of the 

opportunity. It is assumed that the two CMFs are multiplicative as they both apply to the same crash type and 

severity (i.e., total crashes). The combined CMF for shoulder narrowing with shoulder rumble strips is 0.91 (1.07*0.85). 

Based on the combined CMF, the alternative design (shoulder narrowing with rumble strips) is expected to 

reduce crashes by nine percent (100*(1-0.91)) compared to the proposed design. 
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. 

20

In this example, CMFs are used to assess the safety impacts of opportunities in the 

evaluation phase of a VE study where safety is a project factor and crash frequency 

is the performance measure. Based on the relative comparison of CMFs, it appears 

that the alternative design would enhance safety performance compared to the 

existing and proposed designs. As such, the VE study team may recommend the 

alternative design because it would enhance safety performance without the 

requirement of additional right-of-way for the proposed design; however, the final 

decision would also consider other project factors such as the time and cost of the 

opportunities. 

Estimating the Safety Impacts of Opportunities 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, identify the expected 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 (11).

Example: Continuing with the previous example, suppose now that the VE 

study team would like to determine if the opportunities are economically 

justified (benefit-cost ratio greater than 1.0). This analysis requires an 

estimate of the benefit and cost of each opportunity in terms of a dollar 

value. The observed crash frequency with CMF adjustment method 

is used to estimate the change in crashes. First, the proposed design 

(4-ft shoulders) is compared to the existing design (2-ft shoulders without 

rumble strips). Next, the safety impacts of the alternative design 

(2-ft shoulders with rumble strips) are compared to the existing design.

The cost to construct an additional two feet of shoulder (2 ft to 4 ft) for 

the proposed design compared to the existing design is estimated to 

be $300,000 per mile. The service life for shoulder widening is 12 years 

and the annual maintenance costs are negligible. The cost of installing 

shoulder rumble strips on both sides of the road is estimated to be 

$5,000/mile. The service life for rumble strips is seven years and the 

annual maintenance costs are negligible. [Note: These costs would 

be based on average construction costs provided by the State or 

local agency.]

The observed crash frequency for the existing 1.0 mile study 

section is estimated to be 5.20 crashes per year based on the 

most recent five-year crash history. This is used as the estimate 

of crashes for the existing conditions (without treatment). [Note 

that more rigorous methods should be used to estimate crashes 

without treatment when the required inputs are available.] The 

applicable CMFs are then applied to estimate the crashes for 

the proposed and alternative designs as follows:

Estimated crashes with treatment = CMF * Estimated crashes 

without treatment
21

Since the existing conditions are used as the baseline scenario, it is necessary to adjust the CMFs from the 

previous example accordingly. Instead of using a CMF of 1.07 for reducing the shoulder width from 4 ft to 2 ft, we 

now use a CMF of 0.93 (1.00/1.07) to represent the proposed design scenario of increasing the shoulder width 

from 2 ft to 4 ft. This is simply the reciprocal of the previous CMF. When comparing the alternative design to the 

existing design, it is now only necessary to apply the CMF for shoulder rumble strips (0.85) to the estimated crashes 

without treatment since the shoulder width is the same for the existing and alternative designs.

Proposed Design Compared to Existing Design: Increase shoulder width (2 ft to 4 ft)

Estimated crashes with treatment = 0.93 * 5.20 crashes per year = 4.84 crashes/year

Alternative Design Compared to Existing Design: Install shoulder rumble strips

Estimated crashes with treatment = 0.85 * 5.20 crashes per year = 4.42 crashes/year

The estimated change in crashes per year is calculated as the difference in estimated crashes for any two 

conditions. Comparing the proposed and existing designs, the estimated change in crashes is 0.36 crashes per 

year (5.20 crashes per year minus 4.84 crashes per year). Comparing the alternative and existing designs, the 

estimated change in crashes is 0.78 crashes per year (5.20 crashes per year minus 4.42 crashes per year).

The dollar value of the annual safety benefit is then computed by multiplying the change in crashes per mile-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 (12). The HSM (4) also provides 

comprehensive crash costs by severity level, which are based on the data from the FHWA report, Crash Cost 

Estimates by Maximum Police-Reported Injury Severity within Selected Crash Geometries (12). 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 (12). [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 level.] The annual benefit of the proposed design compared to the existing design is $11,734 (0.36 crashes 

per year times $32,236 per crash). The annual benefit of the alternative design compared to the existing design 

is $25,144 (0.78 crashes per year times $32,236 per crash).

The following equation is used to compute the present value for the proposed and alternative designs compared 

to the existing conditions, assuming an inflation rate of three percent. 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 benefit of the proposed design compared to the existing design is computed as 

follows, assuming a service life of 12 years:

Present Value of Shoulder Widening = $11,734 * ---------------------------------------- = $116,799 (1 + 0.03)12 - 1

0.03 * (1 + 0.03)12

The present value of the safety benefit of the alternative design compared to the existing design is computed as 

follows, assuming a service life of seven years:

Present Value of Rumble Strips = $25,144 * ---------------------------------------- = $156,655 (1 + 0.03)7 - 1

0.03 * (1 + 0.03)7

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

costs. Comparing the proposed design to the existing design, the benefit-cost ratio is 0.4 ($116,799 / $300,000). 

Comparing the alternative design to the existing design, the benefit-cost ratio is 31.3 ($156,655 / $5,000). From this 

analysis, it is shown that the alternative design is economically justified with respect to safety compared to the 

existing design (benefit-cost ratio greater than 1.0), while the proposed design is not economically justified. The 

safety impacts can then be considered in conjunction with other project factors.
22

CASE STUDY: EVALUATING OPPORTUNITIES USING PREDICTED CRASH FREQUENCY 

WITH CMF ADJUSTMENT

The following case study illustrates how the Predicted Crash Frequency with CMF 

Adjustment method has been used to explicitly consider the safety impacts of 

opportunities during the VE process. Specifically, it focuses on the quantification of 

safety in the evaluation phase when safety is a project factor and crash frequency 

is the related performance measure. Information for the case study was provided 

by the Missouri Department of Transportation (MoDOT).

MoDOT integrates data-driven decision-making in many of their planning and 

design practices, including the VE process. While not part of their VE policy, 

MoDOT encourages the use of the AASHTO Highway Safety Manual to better 

understand the safety implications of design-related decisions.

Project Description

MoDOT Southeast District proposed a roadway improvement project on a 

rural, two-lane section of Route 34 in Bollinger County, MO. The existing 2.8-

mile study section is characterized by a narrow cross-section with several 

horizontal curves and relatively unforgiving roadside. The proposed project 

involved resurfacing, lane and shoulder widening, horizontal realignment, 

installation of centerline rumble strips, and roadside improvements. The 

project was also listed on the district’s VE work plan, which is created by the 

District Value Engineering Coordinator (DVEC) to identify priority projects 

for VE study. Suggested selection criteria are provided at the following link 

to aid the DVEC in selecting projects for the VE work plan: http://epg.

modot.org/files/c/c0/130_VE_Project_Selection_Criteria.doc.

A VE study was conducted during the design phase of the project to 

review the proposed design and to identify opportunities to add value 

to the project. As part of the investigation phase, the VE study team 

reviewed the project information and original proposed design, 

focusing on three major factors: 1) grading and drainage, 2) base 

and surface, and 3) miscellaneous. Several project elements were 

identified and their functions were defined as part of the function 

analysis. In the creative phase, the VE study team proposed several 

opportunities, including an alternative alignment that would 

modify the design of one curve and two adjacent tangents. 

During the evaluation phase of the VE study, the District conducted 

an analysis, using the Part C Predictive Methods of the Highway 

Safety Manual, to predict the safety performance of the original 

proposed design and VE proposed design compared to the existing 

conditions. The remainder of this case study focuses on the 

analysis conducted as part of the evaluation phase. 

Table 1 provides a summary of the existing conditions, 

original proposed design, and VE proposed design. The baseline 

conditions from the Highway Safety Manual are also provided 

in Table 1 (4). The primary differences among the alternatives 

include the following:

• Lane width: The existing roadway includes 10-ft lanes while the 

original proposed and VE proposed designs would include 

11-ft lanes.

• Shoulder width/type: The existing road includes no paved 

shoulders while the original proposed and VE proposed 

designs would include 4-ft paved shoulders.
23

• Horizontal alignment: The existing design includes 11 horizontal curves with an 

average radius of 591 feet. The original proposed design would include substantial 

improvements to the realignment and while the number of curves would remain 

the same (11 curves) the average radius would increase to 8,436 feet. The VE 

proposed design would include 12 curves with an average radius of 8,194 feet. 

The VE proposed design is nearly identical to the original proposed design, but 

recommends a compound curve in place of a single curve to better balance 

the cut and fill, which would reduce project costs.

• Centerline rumble stripes: The existing roadway does not include centerline 

rumble stripes while the original proposed and VE proposed designs would 

both include centerline rumble stripes.

• Roadside hazard rating: The existing roadway has a roadside hazard rating of 

5, which is characterized by a clear zone width between 5 and 10 feet, virtually 

non-recoverable sideslope (1V:3H), and may have roadside objects including 

guardrail (offset 0 to 5 feet) or rigid obstacles or embankment (offset 6.5 to 

10 feet). The original proposed and VE proposed designs would both include 

roadside improvements to upgrade the roadside hazard rating to 3, which 

is characterized by a clear zone width of 10 feet, marginally recoverable 

sideslope (between 1V:3H and 1V:4H), and a rough roadside surface.

Table 1. Summary of Roadway Characteristics and Baseline Conditions

Roadway Characteristics Existing 

Conditions1

Original 

Proposed Design1

VE Proposed 

Design1 Baseline2

Traffic volume 2,800 2,800 2,800 0 – 17,800

Length (mi) 2.8 2.8 2.8 Not specified

Lane width (ft) 10.0 11.0 11.0 12

Shoulder width (ft) 0 4 4 6

Shoulder type Turf Paved Paved Paved

Horizontal curve length (mi) Varies Varies Varies 0

Radius of curvature (ft) Varies Varies Varies 0

Spiral transition curve (yes/no) No No No No

Superelevation variance (ft/ft) 0 0 0 0

Grade (%) 0 0 0 0

Driveway density (driveways/mi) 5 5 5 5

Centerline rumble stripes (yes/no) No Yes Yes No

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

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

Roadside hazard rating (1-7 scale) 5 3 3 3

Segment lighting (yes/no) No No No No

Auto speed enforcement (yes/no) No No No No

Notes:

1. Volumes on the side roads were low and the District did not consider intersections to be a significant factor in the study. Also, there is 

no change in the relative intersection conditions for the three scenarios. As such, intersections were not included in the analysis.

2. The baseline conditions represent those associated with the HSM Part C Predictive Method for Rural Two-Lane Roads.
24

Practical Application of Predicted Crash Frequency with CMF Adjustment

For this analysis, MoDOT utilized the predictive method for two-lane rural roads from 

Part C of the Highway Safety Manual. Using the predictive method, a user specifies 

an applicable 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 1 (4).

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).

Before applying the predictive method from the Highway Safety Manual, it 

is first necessary to divide the study section into homogeneous segments. A 

homogeneous segment has similar roadway, roadside, and operational 

characteristics. For example, a new segment would be created where there 

is a change in traffic volume. The segmentation resulted in 23 homogenous 

segments, including 12 tangents and 11 curves. 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 (i.e., 

existing, original proposed design, and VE proposed design). 

For this case study, the detailed calculations are shown for Segment 1 

(the first tangent segment) and the results are summarized for the study 

corridor as a whole. Applying Equation {1} to the existing conditions 

with an AADT of 2,800 vehicles per day and a segment length of 0.146 

miles, the predicted total crash frequency for the baseline conditions is 

computed as follows:

NSPF = 2,800 * 0.146 * 365 * 10-6 * e-0.312

NSPF = 0.109 crashes per year

The length of Segment 1 was reduced to 0.095 miles for the original 

proposed design and the VE proposed design based on the 

realignment of the horizontal curves. Applying Equation {1} to the 

proposed conditions with an AADT of 2,800 vehicles per day and a 

segment length of 0.095 miles, the predicted total crash frequency 

for the baseline conditions is computed as follows:

NSPF = 2,800 * 0.095 * 365 * 10-6 * e-0.312

NSPF = 0.071 crashes per year

CMFs were then identified to reflect the conditions of interest for 

Segment 1. The Highway Safety Manual Part C Predictive Method 

for Rural Two-Lane Roads provides specific CMFs for use with the 

SPF from Equation {1}. The CMFs for Segment 1 are provided in 

Table 2 (4). Note that the CMFs related to horizontal curvature 

would change for the curve segments based on the length 

and radius of curve.
25

Table 2. Summary of CMFs for Segment 1 Conditions of Interest

Roadway Characteristics Existing 

Conditions

Original 

Proposed Design

VE Proposed 

Design

Lane width 1.17 1.03 1.03

Shoulder width and type 1.29 1.09 1.09

Horizontal curves 1.00 1.00 1.00

Super-elevation 1.00 1.00 1.00

Grades 1.00 1.00 1.00

Driveway density 1.00 1.00 1.00

Centerline rumble stripes 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 1.14 1.00 1.00

Lighting 1.00 1.00 1.00

Automated speed enforcement 1.00 1.00 1.00

The CMFs were then combined to estimate the overall safety impact of the 

conditions of interest for Segment 1. As recommended in the Highway Safety 

Manual (4), 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:

CMFCombined = Crash modification factor for combined set of roadway 

characteristics.

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 existing 

conditions, original proposed design, and VE proposed design are 

1.721, 1.050, and 1.050 respectively.

CMFCombined (Existing) = 1.17*1.29 *1.14 *1.009 = 1.721

CMFCombined (Original Proposed) = 1.03*1.09 *0.94 *1.009 = 1.050

CMFCombined (VE Proposed) = 1.03*1.09 *0.94 *1.009 = 1.050

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.

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.
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, MoDOT 

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.

26

Computations for the three scenarios of interest are shown below and summarized 

in Table 3. Note that the original proposed design and VE proposed design are 

identical for Segment 1. As such, the predicted crashes are identical for the original 

and VE proposed designs.

NPredicted (Existing Design) = 0.109* 1.721 = 0.188

NPredicted (Original Proposed Design) = 0.071* 1.050 = 0.075

NPredicted (VE Proposed Design) = 0.071* 1.050 = 0.075

Table 3. Summary of Computations for Predicted Annual Crashes for Segment 1

Scenario NSPF

Equation {1}

CMFCombined

Equation {2}

NPredicted

Equation {3}

Existing Conditions 0.109 1.721 0.188

Original Proposed Design 0.071 1.050 0.075

VE Proposed Design 0. 071 1.050 0.075

Using the procedure outlined above, Equations 1 through 3 were applied 

to each of the 23 homogeneous segments individually to compute the 

predicted annual crashes for each segment under each of the three 

conditions. The predicted crashes were then summed over the 23 

segments to predict the total crashes for the corridor as a whole for the three 

conditions of interest. Table 4 presents a summary of the predicted annual 

crashes for each of the 23 homogeneous segments and the corridor 

as a whole. Note that for some individual segments, the existing design 

performs better than the proposed designs with respect to predicted 

crashes (i.e., segments 3, 5, 7, 9, and 21). This is due to the length of the 

analysis segments where the segment length of the existing design 

is shorter than the proposed designs in these cases. The primary 

difference between the original proposed design and VE proposed 

design is the design of segments 3 through 5. The VE study identified an 

opportunity to better balance the cut and fill by modifying one of the

curves (Segment 4) and the two adjacent tangents (Segment 3 and 

Segment 5). Specifically, the VE proposed design would include a 

compound curve with two different radii rather than a single curve 

with constant radii as in the original proposed design.
27

Table 4. Summary of Predicted Annual Crashes (NPredicted) by Segment

Segment Existing Conditions Original Proposed Design VE Proposed Design1

1 0.188 0.075 0.075

2 0.203 0.100 0.100

3 0.054 0.225 0.071

4 0.189 0.178 0.144 / 0.186

5 0.053 0.103 0.122

6 0.291 0.037 0.037

7 0.148 0.253 0.253

8 0.428 0.125 0.125

9 0.052 0.202 0.202

10 0.158 0.133 0.133

11 0.706 0.042 0.042

12 0.204 0.073 0.073

13 0.364 0.123 0.123

14 0.215 0.180 0.180

15 0.477 0.056 0.056

16 0.310 0.084 0.084

17 0.193 0.038 0.038

18 0.153 0.089 0.089

19 0.101 0.036 0.036

20 0.140 0.069 0.069

21 0.074 0.240 0.240

22 0.098 0.048 0.048

23 0.431 0.023 0.023

Total 5.228 2.532 2.549

1 For segment 4, the VE proposed design would include a compound curve with two different radii rather than a single curve as in the 

existing and original proposed designs. As such, the predicted crashes for both curves within the compound curve are shown for the VE 

proposed design.

Based on the above calculations, the two alternative designs are 

predicted to perform better than the existing conditions with respect 

to safety. Specifically, the proposed alternatives are predicted to 

reduce total crashes by nearly 2.7 crashes per year, a 48 percent 

reduction, compared to existing conditions. The VE proposed 

design provides added value compared to the original proposed 

design by reducing project costs. Therefore, the VE proposed 

design is predicted to provide a similar level of safety to the 

original proposed design at a reduced cost.

MoDOT employs Microsoft Excel spreadsheets to assist with 

the computations. The spreadsheets can be used to estimate 

predicted crashes when the observed crash history is not 

available or applicable. When the observed crash history is 

available and applicable, the spreadsheets can be used to 

estimate the expected crashes using the Empirical Bayes method. 

Similar spreadsheets are available at: www.highwaysafety

manual.org. For more information about the case study, 

please contact Ashley Reinkemeyer, MoDOT; Senior Traffic 

Studies Specialist; 573-751-3728; Ashley.Reinkemeyer@modot.

mo.gov. 

It is possible to conduct 

additional analyses to predict 

the number of crashes by crash 

type and severity using Part C of 

the Highway Safety Manual.

It may be possible to employ the 

Empirical Bayes method to increase 

the reliability of the results. The 

Empirical Bayes method combines 

the observed crash history for the 

location of interest with the predicted 

crashes from an applicable SPF. The 

Empirical Bayes method is preferred 

when observed crash data are 

available and applicable.
28

Summary of Findings

SPFs can be used to predict crashes for baseline conditions and CMFs can be 

applied to adjust the baseline estimate to reflect specific conditions of interest. This 

is useful for quantifying and comparing the safety performance of scenarios 

with different design features and can aid in the decision-making process. 

Specifically, this approach can help an agency to better understand the potential 

safety impacts of individual design elements and changes proposed as part of 

a VE study when safety is a project factor and crash frequency and/or severity 

is the performance measure. In this case, Southeast District of MoDOT used 

the Predicted Crash Frequency with CMF Adjustment in order to quantify the 

safety impacts of road widening in conjunction with horizontal realignment, 

centerline rumble strips, and roadside improvements. Two alternative alignments 

(original proposed design and VE proposed design) were compared to the 

existing conditions. While the two alternative designs provide nearly identical 

levels of safety based on total predicted crashes, the VE proposed design 

would reduce project costs. The use of the Predicted Crash Frequency with 

CMF Adjustment demonstrated that the proposed improvements could result 

in a substantial reduction in crashes compared to existing conditions. It also 

showed that the VE proposed design would provide a similar level of safety to 

the original proposed design while providing additional benefits. Recall that 

non-calibrated SPFs may overestimate or underestimate the predicted crash 

frequency, but provide a reasonable estimate of the percent difference in 

crashes among alternatives. As such, it is desirable to use a calibrated SPF 

if it is necessary to estimate the change in predicted crash frequency or 

conduct a formal economic analysis.

OVERCOMING POTENTIAL CHALLENGES

Potential challenges may arise when quantifying safety in the VE 

process. 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 integration of safety in the VE 

process include insufficient expertise (i.e., understanding how to 

select and apply appropriate methods), scheduling and 

coordination with safety experts, and complex scenarios.

Availability of CMFs

A general challenge is the availability of CMFs for specific design 

elements or mitigation measures. The CMF Clearinghouse (6)

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 (6) and recently completed research studies 

such as NCHRP Project 17-45 (8). Additional research 

is underway to develop CMFs for other design elements and 
29

facility types where CMFs are currently unavailable. For example, NCHRP Project 17-

53, Evaluation of the 13 Controlling Criteria for Geometric Design, is developing CMFs 

to help fill-in current gaps for several of the priority design criteria. 

The CMF Clearinghouse (6) 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
Contact information for the 

FHWA field offices is available at: 

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

field.cfm.

30

Applicability of CMFs

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

CMF may be available for a given design element, it may not be appropriate for the 

scenario of interest. For example, there may be significant differences between the 

characteristics of a study site and the sites used to develop the CMF (e.g., different 

area type, number of lanes, or traffic volume). The HSM (4) and CMF Clearinghouse 

(6) provide information to help users identify the applicability of CMFs.

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

and conditions. This is particularly challenging when multiple studies have 

estimated CMFs for the same feature 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 situations 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 (6) 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 (4) and 

posted on the CMF Clearinghouse (6). 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 (9, 10).

Insufficient Expertise

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

insufficient expertise within the team to identify and apply 

appropriate methods to quantify safety impacts. 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 integrate safety analysis in other aspects of 

the project development process (e.g., VE process), but it may 

be necessary to solicit input or assistance from those who are 

more familiar with these methods. If the VE team does not have 

the requisite 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 application of 

CMF-related methods and interpretation of results. The 

National Highway Institute also offers several courses related 
31

to the quantification of safety using CMFs, including the Application of CMFs (#380093) 

and Science of CMFs (#380094). 

Scheduling and Coordination

The VE process is typically completed within one week. If the VE team does not 

have the expertise to apply CMFs and quantify safety impacts, then it may be 

difficult to coordinate with others to provide this support. Three options are 

provided to help overcome this potential issue.

Option 1: Include a safety expert on the VE team. If it is necessary to conduct 

a detailed safety analysis (i.e., applying CMF-related methods), and this is 

recognized in advance of the VE study, then it may be useful to include an 

experienced CMF user or safety analyst as a member of the VE team. 

Option 2: Coordinate with a road safety audit (RSA) team. The FHWA defines 

an RSA as a “formal safety performance evaluation of an existing or future 

road or intersection by an independent, multidisciplinary team” (13). RSAs 

can be used to evaluate road safety issues and identify opportunities for 

improvement on any type of facility during any stage of the project 

development process.

Many aspects of the RSA and VE processes are similar, and the RSA team 

generally includes a member with safety analysis experience. Under this 

option, an RSA could be conducted in coordination with the VE study to 

identify specific safety issues and develop suggestions for consideration 

by the VE team. The RSA team (or individual with safety analysis 

experience) could then join the VE team or provide safety-related 

support, including the selection and/or application of appropriate 

methods to quantify safety impacts. For more information on RSAs 

and their link to VE studies, refer to the FHWA Road Safety Audit

Guidelines (13). 

Option 3: Coordinate with a safety engineer. A safety engineer could 

be contacted prior to the VE study to communicate the timeframe of 

the study and identify the level of assistance that may be needed. 

This way, the safety engineer can be prepared to conduct the 

necessary analysis within the timeframe of the VE study.

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 (4) and related documentation, Integrating 

the HSM into the Highway Project Development Process (5).
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/

REFERENCES

1. “The Value Engineering (VE) Process and Job Plan,” Value Engineering, 

Federal Highway Administration, 7 April 2011, accessed 11 November 2011, 

<http://www.fhwa.dot.gov/ve/veproc.cfm>.

2. 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/. 

3. Introduction to Safety Performance Functions. Publication FHWA-SA-13-014, 

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

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

4. American Association of State Highway and Transportation Officials (AASHTO). 

Highway Safety Manual, 1st Edition, Washington, DC, 2010.

5. 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

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

Administration. Available online at: www.cmfclearinghouse.org

7. 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

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

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

Applications.” Public Roads. Federal Highway Administration, 

Washington, D.C., 2011.

10. 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.

11. 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/.

12. 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/

13. Federal Highway Administration, FHWA Road Safety Audit 

Guidelines, Publication FHWA-SA-06-06, Washington, DC, 2006. 

Available online at: http://safety.fhwa.dot.gov/rsa/guidelines/

FHWA-SA-13-014