CRASH MODIFICATION FACTORS IN PRACTICE

Using CMFs to Quantify the Safety 

Performance of Design Decisions 

and Exceptions

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

the Safety Performance of Design Decisions and Exceptions guide 

describes and illustrates several opportunities to incorporate the latest 

methods to quantify safety in the design process using CMFs. The target 

audience includes those who are responsible for developing, reviewing, 

and approving designs and design exceptions. The purpose of this guide 

is to help raise awareness of opportunities to consider and quantify the 

safety impacts of design decisions, with a specific focus on the 

application of CMFs to support the design process. The objectives are 

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

design process, 2) describe various methods available for quantifying 

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

employ each method. By providing safety awareness, designers will 

be better prepared to assess the safety impacts of individual design 

elements and evaluate the overall impact of design exceptions on 

the safety performance of a facility.

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 the safety impacts of design decisions and exceptions. 

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 design process to understand the 

importance of quantifying safety and using appropriate methods 

to do so.

A design exception is a documented decision to select a value 

for a roadway feature that does not meet minimum values or 

ranges established for a particular project. Safety is explicitly 

considered in the development and evaluation of design 

exceptions, but has traditionally centered on a qualitative review. 

Recently developed methods may allow the project team to 

quantify the safety impacts of individual design elements and 

proposed design exceptions on the safety performance of the 

facility. These methods may also provide a means to quantify 

the potential benefit of contemplated mitigation measures.

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.

The 13 controlling 

criteria include 

design speed, lane 

width, shoulder width, 

bridge width, horizontal 

alignment, superelevation, 

vertical alignment, grade, 

stopping sight distance, 

cross slope, vertical 

clearance, lateral offset to 

obstruction, and structural 

capacity.

CONTENTS

1 Introduction

2 Overview of Safety in 

Design and Design 

Exceptions

4 Methods for Quantifying 

the Safety Impacts of 

Design Decisions and 

Exceptions

14 Application of CMF-Related 

Methods in the Design 

Process

18 Case Studies

27 Overcoming Potential 

Challenges

31 References

2

Read more for an overview of quantifying safety impacts of design decisions and 

exceptions 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 design 

process. Examples are provided to illustrate how these methods can be applied 

and case studies illustrate how these methods have been applied in a particular 

state to quantify the safety impacts of design decisions and exceptions. Finally, 

actual and potential challenges are presented with opportunities to 

overcome common application issues. While several examples are provided 

to demonstrate the basic application of CMF-related methods, the State Highway 

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

Division Office can provide further guidance and assistance with the 

application of these methods and the interpretation of results.

OVERVIEW OF SAFETY IN DESIGN AND DESIGN EXCEPTIONS

According to Federal regulation, the FHWA is responsible for establishing 

design standards for the National Highway System (NHS)—a network of 

approximately 220,000 miles of roads deemed vital to the Nation’s economy, 

defense, and mobility. Any roadway project on this system that proposes 

a design value that fails to meet the minimum criteria set forth in these 

standards must be approved by FHWA as a design exception. State and 

local transportation agencies are responsible for addressing any design 

exceptions, waivers, or variances for roadway projects outside of the NHS.

In general, a design exception is “a documented decision to design a 

highway element or a segment of highway to design criteria that do not 

meet minimum values or ranges established for that highway or project” (1). 

Documentation of the design exception is critical for establishing a 

historical record for future reference. Documentation is particularly 

critical during litigation, as it provides evidence that the decision was 

made only after thoughtful and thorough review and consideration of 

design alternatives. Agencies can demonstrate that safety was explicitly 

considered by quantifying the safety impacts of individual design 

elements and evaluating the impact of the proposed design 

exception on the overall safety performance of the facility compared 

to existing conditions and the scenario that meets or exceeds design 

standards.

The term “design exception” is frequently used specifically when 

dealing with controlling criteria, while terms such as “design 

variance” or “design waiver” are used when dealing with other 

design criteria. A controlling criterion is one of the 13 design 

elements identified by the FHWA as having substantial 

importance to the operational and safety performance of any 

highway. As such, a design exception commonly refers to the 

formal means of applying for approval to design one or 

more controlling criteria below current design standards. The 

13 controlling criteria are listed in the Federal-Aid Policy 

Guide (1) and described in FHWA’s Mitigation Strategies for 

Design Exceptions (2). 

While the process may vary for state and local agencies, the 

design exception process adopted by FHWA consists of the 

following six specific steps (2). 

1. Determine Costs and Impacts of Meeting Design Criteria.

2. Develop and Evaluate Multiple Alternatives.
3

3. Evaluate Risk.

4. Evaluate Mitigation Measures.

5. Document, Review, and Approve.

6. Monitor and Evaluate In-Service Performance.

The six-step process is described below, noting the steps where safety considerations and analysis can be 

incorporated. By quantifying safety, agencies can better understand the potential impacts of individual design 

elements and the impacts of a proposed design exception on the overall safety performance of a facility. This is 

particularly useful for risk management and defending against potential litigation. For example, environmental 

or right-of-way restrictions may induce a project team to consider design alternatives and perhaps design 

exceptions to the established design criteria for a given project. Quantifying safety impacts will help to select the 

design that achieves a reasonable balance between cost, safety, operations, and other impacts.

Determine Costs and Impacts of Meeting Design Criteria

Once the potential for a design exception is identified, the design exception process begins with an estimation of 

the costs and impacts of designing the roadway element to meet or exceed the design standard. This provides a 

baseline for the project team to compare the cost and impacts of other design options. This is the first opportunity 

to employ CMF-related methods to quantify safety in the design exception process. 

Develop and Evaluate Multiple Alternatives

If meeting design standards is deemed to be infeasible for a given location, then alternatives should be developed 

and evaluated. The alternatives should be devised in a way that strives to balance safety, mobility, cost, and 

impacts. Once developed, each alternative should be evaluated in terms of these considerations, and its 

performance should be compared relative to the other alternatives and relative to the scenario that meets the 

design standard. 

Safety is explicitly considered in the design exception process, but has traditionally involved a qualitative review. 

The qualitative review may include a summary of the crash history and a discussion of the anticipated effects 

of the design exception (e.g., a standard four-foot shoulder will provide more room for recovery than would a 

proposed two-foot shoulder). The methods discussed in this guide may help quantify the safety impacts of 

individual design elements and the overall impact of proposed design exceptions on the safety performance 

of the facility (e.g., lane departure crashes are anticipated to increase by 13 percent with a proposed two-foot 

shoulder compared to a standard four-foot shoulder for a rural, two-lane road carrying 2,500 vehicles per day). 

Safety impacts can then be converted to a dollar value based on average crash costs. In this way, safety is 

quantified and can be considered with other factors such as cost, operational effects, and environmental impacts.

Evaluate Risk

Before proceeding with a proposed design exception, an agency must evaluate the degree to which the risk of 

safety and/or operational problems could increase or decrease. The results from the previous step can be used 

to compare the estimated safety performance of proposed design exceptions with the scenario of meeting 

the design standard. This will provide an indication of the estimated difference in safety performance. The safety 

performance of a proposed design exception could also be compared to the safety performance of existing 

conditions to demonstrate the intent to improve safety, even though the design does not meet the design standard.

Evaluate Mitigation Measures

Once the need for a design exception is identified and the potential safety and operational impacts are defined, 

the next step is to identify and evaluate mitigation measures. Examples of mitigation measures include advance 

notice to the driver or augmenting the geometric design of other roadway elements to help offset the potential 

negative effects of the design exception. Mitigation techniques for the 13 controlling criteria are provided in 

FHWA’s Mitigation Strategies for Design Exceptions (2). 

The documentation of a design exception typically includes a generic discussion of proposed mitigation 

measure(s) and the potential to offset the possible negative impacts of the design feature. The CMF-related 
The estimated cost, 

safety performance, 

and other potential 

impacts should be 

documented for the 

existing conditions, 

design exception, and 

design standard.

Note that while there are several 

methods available to consider 

and quantify the safety impacts of 

design decisions and exceptions, 

there is a clear order of preference 

based on the availability of data 

and reliability of the methods. 

Engineering judgment is an essential 

component of each method.

4

methods discussed in this guide can be used to quantify the safety impacts of 

proposed mitigation measures or combinations of mitigation measures. The results 

from the safety analysis can be combined with average crash costs and compared 

to treatment costs to estimate the cost-effectiveness of each potential mitigation 

measure. This is useful in selecting the final measure(s) to implement, particularly 

when there are multiple potential mitigation measures. 

Document, Review, and Approve

The next step in the process is the documentation, review, and approval of the 

design exception. Documentation is critical for establishing a historical record 

and demonstrating that the decision was made only after thoughtful and 

thorough examination of design alternatives and potential costs and impacts. 

Important aspects to document include the estimated cost, safety performance, 

and other potential impacts for several scenarios, including existing conditions, 

design exception, and scenario of meeting the design standard.

Monitor and Evaluate In-Service Performance

The final step of the process is to monitor and evaluate the safety and 

operational performance of the facility after completion of the construction 

project. A thorough review and analysis of safety performance should be 

conducted for locations where a design exception was implemented for 

a given roadway element. This will provide important information for future 

decisions related to similar design considerations.

METHODS FOR QUANTIFYING THE SAFETY IMPACTS OF DESIGN 

DECISIONS AND EXCEPTIONS

There are several opportunities to identify and address safety impacts 

in the design process. This section focuses on the evaluation of design 

decisions and exceptions as well as potential mitigation measures. 

Several methods and related tools are available to compare the 

safety impacts of individual design elements and the impacts of design 

exceptions on the safety performance of a facility. Safety impacts 

are quantified by estimating the extent to which a design alternative 

is likely to impact the frequency and severity of crashes. The safety 

impacts can then be compared among the design alternatives and 

considered in conjunction with other factors such as operational 

and environmental impacts and overall project cost. 

The safety impacts can be estimated using a number of methods 

which incorporate one or more of the following inputs: crash 

modification factors, safety performance functions, observed 

crash frequency, predicted crash frequency, and expected crash 

frequency. Engineering judgment is an essential component 

of each method. These terms are defined below, followed by a 

discussion of each method. The methods are presented in order 

of increasing reliability, with a discussion of their strengths and 

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

appropriate method depends on the complexity of the decision 

at hand and the availability of required inputs. Related tools 

are then identified and can be used to help implement the 

methods. This section concludes with guidance on how to 

select an appropriate method based on the decision at 

hand and availability of required inputs.
5

Inputs

The required inputs are defined below, followed by a discussion of the various methods. More rigorous methods 

can be employed when more inputs are available; the most rigorous method requires all of the following inputs. 

Crash Modification Factors

A crash modification factor (CMF) is an index of the expected change in safety performance following a 

modification in traffic control strategy or design element. When applied correctly, CMFs can be used to estimate 

the safety effectiveness of a given strategy, compare the relative safety effectiveness of multiple strategies, and 

adjust the crash frequency estimated from observed, predicted, or expected crashes. Readers can refer to the 

Introduction to Crash Modification Factors for more information on CMFs and how they are applied (3).

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 a SPF 

can be multiplied by an applicable CMF to account for differences between the actual site conditions and the 

specified baseline conditions. If a 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 (4) for more information on SPFs 

and how they are applied.

Observed Crashes

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

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

five crashes per year at this location based on the observed crash history. Using the observed 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).

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 a design element or 

exception in conjunction with other factors such as operational and environmental impacts as well as overall 

project cost.
While quality CMFs are 

available for many traffic control 

strategies and design elements, 

they are not currently available 

for all 13 controlling criteria.

6

Methods for Quantifying Safety Impacts

Several methods are available for quantifying safety impacts in the design process. 

The following is a detailed discussion of the various methods, 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 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 Design 

Alternatives using CMFs section.

The advantages of this method include the following:

• It is relatively simple to apply.

• It does not require an estimate of crashes without treatment to which 

the CMF would be applied. 

The limitations of this method include the following:

• It requires applicable CMFs. While quality CMFs are available for 

many traffic control strategies and design elements, they are not 

currently available for all 13 controlling criteria. CMFs related to 

the 13 controlling criteria are further discussed in Availability of 

CMFs in the Overcoming Potential Challenges section, including 

existing CMFs and efforts to develop additional 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 design elements or mitigation 

measures when the applicable CMFs are for different crash 

types or severities.

Observed Crash Frequency with CMF Adjustment

This method is used to estimate the crash frequency for design 

alternatives. The results can be used to compare the safety 

performance of design alternatives or included in a benefitcost analysis to quantify the benefits. The required inputs for 

this method include the following:

• Observed crashes.
7

• 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 

scenarios with different design values (e.g., design standard and design exception). 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 Design Decisions using 

Observed Crashes and CMFs section, comparing the cost-effectiveness of various shoulder widths. 

The advantages of this method include the following:

• It is relatively simple to apply.

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

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

The limitations of this method include the following:

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

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

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

Predicted Crash Frequency

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

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

inputs for this method include the following:

• Applicable SPF.

• Engineering judgment. 

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

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

frequency is computed from an applicable SPF. 

The advantages of this method include the following:

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

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

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

• 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 of interest. It may also be necessary to adjust the SPF 

through calibration to better reflect local conditions or a different study period.

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

Predicted Crash Frequency with CMF Adjustment

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

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

inputs for this method include the following:

• Applicable SPF.

• Applicable CMF(s).

• Engineering judgment. 

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

applicable (e.g., proposed conditions differ drastically from the existing conditions) and where the SPF does 
8

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.

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 a SPF that includes all variables of interest.

The limitations of this method include the following:

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

calibration to better reflect local conditions or a different study period.

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

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

Expected Crash Frequency

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

the safety performance of design alternatives or to quantify the benefits 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 of interest. It may also be necessary to adjust the SPF 

through calibration to better reflect local conditions or a different study period.

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

Expected Crash Frequency with CMF Adjustment

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

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

inputs for this method include the following:

• Observed crashes from an applicable crash history.

• Predicted crashes from an applicable SPF.

• Applicable CMF(s).

• Engineering judgment. 
9

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 a 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 • • • •
10

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 design 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 

(5). The knowledge and methods included in the HSM will allow users to explicitly 

consider and quantify safety in the project development 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 design exception process, Part B is used to help 

guide the diagnosis of safety issues and selection of mitigation 

measures. While safety is currently incorporated in the design 

exception process, a formal safety diagnosis helps to develop more 

targeted strategies to address specific safety issues. Part C and 

Part D are likely the most applicable as SPFs and CMFs are used to 

quantify and compare the safety impacts of design alternatives. Part 

C is used to estimate the safety performance of design alternatives 

in terms of crash frequency and severity. The CMFs from Part D are 

used to assess the safety impacts of individual design elements 

or mitigation measures. Readers can refer to the Introduction to 

Safety Performance Functions (4) for more information on SPFs 

and how they are applied. For more information on the use of 

predictive methods to evaluate design decisions, refer to 

Integrating the HSM into the Highway Project Development 

Process (6). If the application of this approach is beyond the 

expertise of the project team, then they could seek assistance 

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

FHWA Division Office. 

Contact information for the FHWA 

field offices is available at:

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

field.cfm.
11

Crash Modification Factors Clearinghouse

The CMF Clearinghouse (7) 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 

(3) 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 (8). 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 (9). 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 design 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 design alternatives (e.g., different area type, number of lanes, and/or traffic 

volume). In such cases, it is necessary to conduct a more detailed analysis, preferably using expected crashes 

with or without CMF adjustment. The following table is provided to help users select an appropriate method for 

quantifying safety impacts.
12

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).

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
13

Compare the safety impacts of 

alternatives with different overall 

characteristics (e.g., existing four-lane 

undivided segment and proposed 

three-lane segment with two through 

lanes and a two-way left-turn lane)

Sample 

Scenario 3

Compare the safety impacts of 

alternatives with different safety 

treatments (e.g., shoulder widening 

and shoulder rumble strips)

Question 4

Is an applicable SPF available to 

estimate the predicted crashes for 

the conditions of interest (e.g., does 

the SPF include a variable for number 

of lanes and median type)?

Go to Predicted 

Crash Frequency 

Question 5

Is an applicable crash history 

available to estimate the observed 

crashes for baseline conditions 

(without either treatment)?

Are applicable CMFs available to 

estimate the safety impacts of the 

conditions of interest 

(e.g., shoulder widening 

and shoulder rumble strips)?

Go to Observed Crash 

Frequency with CMF Adjustment

Question 6

Are applicable CMFs available to 

estimate the safety impacts of 

the conditions of interest 

(e.g., shoulder widening and 

shoulder rumble strips)?

Go to Relative Comparison 

of CMFs

Predicted Crash 

Frequency

Process Compute the predicted 

crashes for the conditions of interest.

Applicability1 Simple and 

Complex Scenarios

Observed Crash Frequency 

with CMF Adjustment

Process Compute the observed 

crashes for baseline conditions 

and multiply the observed crashes 

by the applicable CMF to estimate 

crashes for the two conditions.

Applicability1 Simple Scenarios

Relative Comparison 

of CMFs

Process Compare the CMFs to 

estimate the relative impacts of the 

two conditions.

Applicability1 Simple Scenarios

If NO, go to 

Question 5 YES

If NO, go to 

Question 6 YES

If NO, then it is 

not possible 

to quantify the 

safety impacts 

based on 

these methods

YES

If NO, then it is 

not possible 

to quantify the 

safety impacts 

based on 

these methods

YES
The

14

APPLICATION OF CMF-RELATED METHODS IN THE DESIGN PROCESS

There are several opportunities to quantify the safety impacts of design decisions and exceptions. For 

design decisions, the safety impacts can be compared for different values of a particular design element. For 

design exceptions, the safety performance can be estimated and compared for various scenarios such as the 

existing conditions, proposed design exception, and design standard. When comparing the safety performance of 

various scenarios, potential safety issues can be identified along with potential mitigation measures. 

This section focuses on the application of CMFs to quantify the safety impacts of design decisions, including 

the impact of design elements and potential mitigation measures. 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 design process as noted below. Examples are provided, followed by a case study and a discussion 

of opportunities to overcome potential challenges.

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

quantify the safety impacts of design elements and mitigation measures. The first demonstrates the Relative 

Comparison of Design Alternatives using CMFs, which uses CMFs alone to compare the anticipated percent 

change in crashes for different values for a given design element. The second application, Estimating the Safety 

Impacts of Design Decisions using Observed Crashes and CMFs, is slightly more advanced as CMFs are used 

within a benefit-cost analysis. The second application demonstrates the use of observed crash history to estimate 

future crashes for baseline conditions and the application of CMFs to estimate the change in crashes for design 

alternatives. The estimated change in crashes is then converted to a monetary value based on average crash 

costs and compared to the project cost to estimate the benefit-cost ratio of the alternative. The third application 

focuses on the Assessment of Mitigation Measures. The results can be used to compare the safety performance 

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

specific mitigation measure is cost-effective. The case studies provide additional examples, including the use of 

more rigorous methods (i.e., Predicted Crash Frequency with CMF Adjustment) to quantify the safety impacts of 

design alternatives.

Relative Comparison of Design Alternatives using CMFs 

The following steps can be used to compare the relative safety impacts of design alternatives when the Relative 

Comparison of CMFs is identified as an appropriate method.

Step 1: Identify Applicable CMFs for Conditions of Interest

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

Modification Factors (3), the CMF selection process involves several considerations including the availability of 

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

(7) contains more than 3,000 CMFs for various design and operational features and also provides detailed 

information for each CMF to help users identify applicable scenarios and the related quality.

Step 2: Combine CMFs to Estimate Overall Impact of Design Alternatives

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

among design alternatives (e.g., shoulder width), 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 design 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 

(3), 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 (10, 11).

Step 3: Compare CMFs to Quantify Relative Impacts of Design Alternatives

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

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

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

compared to the condition without a spiral transition. In other cases, there may be multiple potential values for a 

given design element (e.g., shoulder width) and the CMFs indicate the expected change in crashes relative to 
15

a baseline shoulder width. 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 design engineer is comparing various shoulder 

widths as part of a reconstruction project on a rural, two-lane, undivided collector with a posted speed limit of 45 

mi/h and an annual average daily traffic volume of 10,000 vehicles per day. 

The existing road has no paved shoulders, and the designer has proposed to increase the shoulder width to 2 feet 

as part of a widening project to address single-vehicle run-off-road crashes. The applicable design standard for 

this road calls for a shoulder width of 4 feet, but this has been deemed infeasible due to right-of-way constraints 

and environmental impacts. As such, the designer is filing a design exception to document the reasons for 

providing 2-ft shoulders and the anticipated safety impacts. The following table summarizes the conditions for the 

existing design, proposed design, and design standard.

Scenario Shoulder Width (ft)

Existing Design 0

Proposed Design 2

Design Standard 4

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

impacts of the design exception because the required inputs and expertise to apply more rigorous methods were 

not available to the designer. Applicable CMFs were identified from the HSM (5). The following table presents 

the CMFs for each scenario along with the baseline conditions and applicability. [Note that all CMFs apply to 

total crashes on rural, two-lane roads and all are relative to the same baseline condition (6-ft shoulders).]

Scenario CMF Baseline

Condition

Applicable

Facility Type

Applicable

Crash Type

Applicable

Crash Severity

Existing Design 

(0-ft shoulders) 1.29 6-ft shoulders Rural two-lane All All

Proposed Design 

(2-ft shoulders) 1.17 6-ft shoulders Rural two-lane All All

Design Standard 

(4-ft shoulders) 1.09 6-ft shoulders Rural two-lane All All

There are three conditions to be compared in this example: 1) 0-ft shoulders (existing), 2) 2-ft shoulders (proposed), 

and 3) 4-ft shoulders (design standard). If the applicable CMFs are relative to the same baseline, which they are 

in this example, then the ratio of any two CMFs can be used to estimate the relative safety impact between the 

two conditions. For example, the safety impact of the proposed design (CMF = 1.17) compared to the existing 

design (CMF = 1.29) is estimated by taking the ratio of the respective CMFs (1.17/1.29 = 0.91). Based on this 

comparison, it is anticipated that crashes will be reduced by nine percent (100*(1-0.91)) by adding 2-ft shoulders 

to an existing rural two-lane road with no shoulders. The following table summarizes the safety impacts for various 

combinations of scenario comparisons.

Comparison Applicable CMFs Safety Impact of Scenario A

Scenario A Scenario B Scenario A Scenario B Relative to Scenario B

2-ft shoulders 0-ft shoulders 1.17 1.29 0.91 (9% reduction)

4-ft shoulders 0-ft shoulders 1.09 1.29 0.84 (16% reduction)

2-ft shoulders 4-ft shoulders 1.17 1.09 1.07 (7% increase)

While the proposed design exception (2-ft shoulders) does not provide the estimated level of safety associated 

with the design standard (4-ft shoulders), it does provide a safety benefit compared to the existing conditions (0-ft 

shoulders). Specifically, the proposed 2-ft shoulders are anticipated to reduce crashes by nine percent compared 
Note that several methods 

are available for estimating 

crashes without treatment. 

The estimated crash 

frequency without treatment 

should correspond with the 

specific crash type and 

severity for which the CMF 

is applicable. If the CMF 

applies to total crashes, 

then one should estimate the 

total annual crashes without 

treatment. If the CMF applies 

to a specific crash type or 

severity, then the annual 

crashes without treatment 

should be computed for 

that crash type or severity. 

16

to existing conditions; an additional seven percent reduction in crashes would be 

anticipated if 4-ft shoulders are provided. The next step will be to determine whether 

or not the additional reduction in crashes is feasible after comparing the alternatives 

in terms of cost and other factors such as operational and environmental impacts.

This represents a quantitative safety analysis and provides more specific information 

than simply indicating that crashes are likely to increase as shoulder width decreases. 

The safety analysis, however, is only one aspect of the proposed design exception. 

In addition, the cost, operational, and environmental impacts of the various 

alternatives should be considered as well as potential mitigation measures.

If the applicable CMFs are not relative to the same baseline, then one additional 

step is necessary in the previous example to create a common baseline for the 

applicable CMFs before proceeding with the comparison. The same general 

rule is applied, taking the ratio of CMFs to estimate the impact of Scenario A 

relative to Scenario B, but Scenario B would be the same for all ratios before 

proceeding to compare other scenarios. This case is rare but could apply if the 

applicable range of CMFs differs for two studies and the roadway conditions 

in question are not covered by a single study. For example, it would not be 

possible to use a single study for the scenario above if one study developed 

CMFs for shoulder widths of zero to two feet and another study developed 

CMFs for shoulder widths of two to six feet.

Estimating the Safety Impacts of Design Decisions 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 design values 

for a given design element. It does not, however, estimate the change in 

the number of crashes or consider the relative cost of the alternatives. 

If the number of crashes without treatment is estimated, then the CMFs 

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

The change in crashes can then be converted to a monetary value, 

based on average crash costs, to estimate the value of the benefit (or 

disbenefit). Finally, these costs can be compared to the construction 

costs to estimate a benefit-cost ratio. The following example illustrates 

this process. Further details on the step-by-step process can be found 

in the companion guide, CMFs in Practice: Quantifying Safety in the 

Roadway Safety Management Process (12).

Example: Continuing with the previous example, suppose now 

that the designer would like to determine if it is cost-effective (i.e., 

benefit-cost ratio greater than 1.0) to increase the shoulder width 

beyond the existing width and, if so, is it cost-effective to provide 

the minimum design standard (4-ft shoulders). This analysis requires 

an estimate of the benefit and cost of each scenario in terms of 

a dollar value. The following table provides a summary of the 

construction costs, annual operating and maintenance costs, 

and expected service life for the two scenarios compared to 

the existing conditions. [Note that these costs would be based 

on average construction costs provided by the State or local 

agency.]
17

Scenario Construction Cost

(per mile)

Annual Operating 

and Maintenance 

Cost

Service Life

Proposed Design (2-ft shoulders) $200,000 Negligible 12

Design Standard (4-ft shoulders) $500,000 Negligible 12

The five-year average crash frequency for the existing rural two-lane road is 7.2 crashes per mile per year. This is 

used as the estimate of crashes without treatment (i.e., existing 0-ft shoulders). [Note that more rigorous methods 

should be used to estimate crashes without treatment when the required inputs are available.]

Recall that the CMFs for constructing 2-ft shoulders and 4-ft shoulders, relative to the existing 0-ft shoulders are 0.91 

and 0.84, respectively. The CMFs are applied individually to estimate the crashes for each scenario as follows:

Estimated crashes with treatment = CMF * Estimated crashes without treatment

Proposed Design Exception (2-ft shoulders):

Estimated crashes = 0.91 * 7.2 crashes per mile per year = 6.5 crashes/mile-year

Design Standard (4-ft shoulders):

Estimated crashes = 0.84 * 7.2 crashes per mile per year = 6.1 crashes/mile-year

The estimated change in crashes per mile-year is calculated as the estimated crashes under existing conditions 

minus the estimated crashes for the design condition of interest. For the proposed design exception (2-ft 

shoulders), the estimated change in crashes is 0.7 crashes per mile-year (7.2 crashes per mile-year minus 6.5 

crashes per mile-year). For the design standard (4-ft shoulders), the estimated change in crashes is 1.1 crashes 

per mile-year (7.2 crashes per mile-year minus 6.1 crashes per mile-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 (13). The HSM (5) 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 (13). 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 (13). [Note that crash costs vary by type and severity and different costs would apply if 

the analysis was based on different crash types or severities. If possible, the analyst should use local crash costs 

by severity level.] For the proposed design exception (2-ft shoulders), the annual benefit is $21,591 (0.7 crashes 

per mile-year times $32,236 per crash) compared to the existing condition. For the design standard (4-ft 

shoulders), the annual benefit is $35,984 (1.1 crashes per mile-year times $32,236 per crash) compared to the 

existing condition.

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

rate of three percent, and a service life of 12 years for both scenarios. In the following equation, (A) is the annual 

benefit or disbenefit, (i) is the inflation rate, and (n) is the service life.

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

(1 + i)n - 1

i * (1 + i)n

The present value of the safety benefits of the proposed design exception is computed as follows:

Present Value of Proposed Design Exception = $21,591 * ---------------------------------------- = $214,913 (1 + 0.03)12 - 1

0.03 * (1 + 0.03)12
Note that the 

HSM and FHWA 

report, Crash Cost 

Estimates by 

Maximum PoliceReported Injury 

Severity within 

Selected Crash 

Geometries, provide 

costs in 2001 dollars. 

These costs should 

be adjusted by the 

gross domestic 

product (GDP) to 

better reflect the actual 

costs associated with 

the analysis period.

18

The present value of the safety benefits of the design standard is computed as follows:

Present Value of Design Standard = $35,984 * ---------------------------------------- = $358,189 (1 + 0.03)12 - 1

0.03 * (1 + 0.03)12

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

the present value of the total project costs. For the proposed design exception, 

the benefit-cost ratio is 1.1 ($214,913 / $200,000). For the design standard, the 

benefit-cost ratio is 0.7 ($358,189 / $500,000). From this analysis, it is shown that 

only the proposed design exception is economically justified (benefit-cost ratio 

greater than 1.0) and is also more cost-effective (i.e., greater improvement per 

dollar spent) than the design standard.

Assessment of Mitigation Measures

Similar to quantifying the impacts of design decisions and exceptions on the 

safety performance of a facility, these methods can be used to estimate the 

safety impact of implementing mitigation measures. The procedure is identical 

to those described in the previous applications, but the level of effort required 

for the analysis depends on the desired output. If it is sufficient to compare 

the estimated percent reduction in crashes, then the Relative Comparison 

of CMFs is employed. If it is desired to estimate the number of crashes after 

implementing the mitigation measure, then it would be necessary to employ 

a more rigorous method such as Expected Crash Frequency with CMF 

Adjustment. Other methods such as Observed Crash Frequency with CMF 

Adjustment or Predicted Crash Frequency with CMF Adjustment could also 

be used depending on the situation. For help selecting an appropriate 

method, refer to the section titled: Selecting an Appropriate Method.

CASE STUDIES

CMFs can be applied to quantify the safety impacts of design 

elements and estimate the effects of mitigation measures. Combined, 

these results can be used to evaluate the overall impacts of a 

design exception on the estimated safety performance of a facility. The 

following case studies illustrate how CMFs have been applied by the 

California Department of Transportation (Caltrans) and the Missouri 

Department of Transportation (MoDOT) in the design process. 

Case Study #1: Evaluating Design Exceptions using Observed 

Crash Frequency with CMF Adjustment

The following case study illustrates how the Observed Crash 

Frequency with CMF Adjustment method has been used to assess 

the safety impact of individual design elements and evaluate 

the overall impact of design exceptions on the safety 

performance of a facility. Information for the case study was 

provided by Caltrans.

Project Description

In response to 24 collisions that occurred in a three-year 

period within a section of US 199 in Northern California, District 

1 of Caltrans proposed a series of engineering improvements 
19

to address potential safety issues. The project limits are within United States Forest Service Lands in Del Norte 

County, approximately two miles north of Hiouchi. The limits extend from 0.9 to 1.1 miles north of South Fork Road. 

The existing alignment consists of two curves with a short tangent transition, forming a reverse curve. Curve 2 

was the primary focus of the engineering improvements as all 24 crashes occurred along this curve during the 

three-year period. The study location is characterized by the following variables and circled in Figure 1.

• Area type: rural.

• Terrain: mountainous.

• Number of lanes: two-lane road.

• Annual average daily traffic (AADT): 

• Year 2010: 4,300 vehicles per day.

• Year 2016 (construction year): 4,560 vehicles 

per day.

• Posted speed: 55 mph (also the design speed).

• Horizontal curvature:

• Curve 1: 750 ft radius.

• Curve 2: 300 ft radius.

• Lane width: 11 ft.

• Shoulder width: 0 – 2 ft.

Documentation of Design Exceptions

Design exceptions were proposed for design 

elements related to the superelevation runoff 

length, superelevation runoff transition, and 

alignment consistency (14). Further discussion 

of each of these elements is provided below.

Superelevation Runoff Length

The Caltrans Highway Design Manual indicates 

that “when horizontal curves reverse, the connecting 

tangents should be long enough to accommodate 

the standard superelevation runoffs.” For this project, 

Caltrans proposed to increase the existing runoff 

length, but the proposed length was still less than 

standard. As further justification for the proposed 

design exception, it was noted that the proposed runoff 

lengths are similar to those at adjacent sections of US 

199 and, as such, are not anticipated to violate driver 

expectation.

Superelevation Runoff Transition

The Caltrans Highway Design Manual specifies that “two-thirds of the superelevation runoff should be on the 

tangent and one-third within the curve.” In order to meet this standard, the length of the tangent section would 

need to be increased.

Alignment Consistency

The Caltrans Highway Design Manual indicates that “where physical restrictions on curve radius cannot be 

overcome and it becomes necessary to introduce curvature of lower standard than the design speed of the 

project, the design speed between successive curves should change not more than 10 mph. Introduction of 

curves with lower design speeds should be avoided at the end of long tangents, steep downgrades, or at other 

locations where high approach speeds may be anticipated”. In order to meet the standard, the radius of Curve 

2 would need to be increased from 300 feet to 700 feet. For this project, Caltrans proposed to increase the radius 

of Curve 2 from 300 feet to 400 feet.

Figure 1: Project Location (14)
Note that while CMFs 

were used to compare 

the estimated safety 

impacts of the proposed 

design exceptions with 

respect to the existing 

conditions, it is also 

desirable to compare the 

estimated safety impacts 

of the proposed design 

exceptions with respect to 

the design standards.

Note that while Caltrans only used 

CMFs from the HSM (5), the CMF 

Clearinghouse (7) is another source 

of CMFs. For example, CMFs for 

shoulder rumble strips are available 

in the CMF Clearinghouse.

20

Summary of Other Factors

The following were documented as requirements to meet the standard runoff length, 

runoff transition, and alignment consistency:

• Excavation of 50-ft tall rock slopes to accommodate realignment.

• Additional and taller retaining walls. 

• Additional fill due to increasing the wall height.

• Additional drainage work.

In addition, the historical Cold Springs Mountain Trail, located adjacent to this 

segment of US 199, would also have to be realigned to accommodate the larger 

radii. This would result in excessive costs due to the significant impacts to the 

right-of-way and environment. 

The documentation of the design exception explains the effort required to 

comply with the Caltrans Highway Design Manual, proposes exceptions to 

specific design elements, and identifies measures to mitigate the potential 

safety impacts of exceptions to the Caltrans Highway Design Manual. It was 

anticipated that curve-related crashes would be reduced by increasing 

the radius of Curve 2, but not to the extent that they could be reduced by 

increasing the radius to meet the applicable design criteria. To further 

enhance safety on Curve 2, mitigation measures were proposed, including 

increasing the superelevation, lane width, and shoulder width within the 

sub-standard section. These mitigation measures are expected to further 

reduce curve-related crashes, particularly single-vehicle roadway 

departures. CMFs were applied to demonstrate the safety benefit of the 

proposed design exceptions and mitigation measures compared to the 

existing conditions. The application of CMFs is detailed in the following 

section, Practical Application of CMFs.

Practical Application of CMFs

The following CMFs and computations are associated with Curve 2 since 

this was the focus of the engineering improvements, design exception 

requests, and safety analysis. Recall that all 24 crashes occurred within 

Curve 2 during the three-year study period. The existing and proposed 

conditions are summarized in Table 1. 

Table 1. Summary of Existing and Proposed Conditions

Feature Existing Proposed

Curve 2 Radius (ft) 300 400

Curve 2 Length (mi) 0.0536 0.0536

Superelevation 0.072 0.120

Lane Width (ft) 11 12

Shoulder Width (ft) 0 - 2 8

In addition to these improvements, Caltrans proposed to increase 

the runoff lengths and install shoulder rumble strips. However, 

CMFs are currently not listed in the HSM for these improvements 

and thus were not used in the calculations.

Table 2 identifies the CMFs associated with the existing 

and proposed conditions as well as their applicability and 

baseline conditions. Note that all CMFs apply to all crashes 
21

on rural, two-lane curves. From the HSM (5), the following equation is used to estimate the CMF for a given curve 

radius compared to a tangent section.

CMFcurve = -----------------------------------------------

1.55Lc + ---------- - 0.012S

1.55Lc

80.2

R

Where: 

CMFcurve = CMF for the effect of horizontal alignment on total crashes compared to a tangent section.

Lc = length of horizontal curve (miles) which includes spiral transitions, if present.

R = radius of curvature (feet).

S = 1 if spiral transition curve is present; 0 if spiral transition curve is not present; 0.5 if a spiral transition curve is 

present at one but not both ends of the horizontal curve.

From the HSM (5), the following equations are used to estimate the CMF for the superelevation variance of a 

horizontal curve (i.e., the difference between the actual superelevation and the superelevation identified by 

AASHTO policy). When the actual superelevation meets or exceeds that in the AASHTO policy, or when the 

superelevation variance is less than 0.01, the value of the superelevation CMF is 1.00.

CMFsv = 1 + 6(SV - 0.01) for 0.01 ≤ SV < 0.02

CMFsv = 1.06 + 3(SV - 0.02) for SV ≥ 0.02

Where:

CMFsv = CMF for the effect of superelevation variance on total crashes.

SV = superelevation variance (ft/ft), which represents the superelevation rate contained in the AASHTO Green 

Book minus the actual superelevation of the curve.

From the HSM (5), the CMFs for 11-ft lanes and 12-ft lanes are 1.05 and 1.00, respectively. The CMFs for 0-ft 

shoulders, 2-ft shoulders, and 8-ft shoulders are 1.50, 1.30, and 0.87. Note that the CMFs for lane and shoulder 

width apply to run-off-road, head-on, and sideswipe crashes. Using the following equation from the HSM, the 

CMFs are adjusted to estimate the impact on total crashes. A slightly different equation is used when the 

shoulder type changes.

CMFtotal = (CMFrelated - 1.0) * Pr + 1.0

Where:

CMFtotal = CMF for total crashes.

CMFrelated = CMF for related crashes (i.e., run-off-road, head-on, and sideswipe crashes).

Pr = proportion of total crashes constituted by related crashes (default = 0.574).

Table 2. Summary of CMFs for Existing and Proposed Conditions

Feature CMF Baseline Condition Applicability

Existing Radius (300 ft) 4.23 Tangent All crashes on rural, two-lane curves

Proposed Radius (400 ft) 3.42 Tangent All crashes on rural, two-lane curves

Existing Superelevation (0.07) 1.14 0.12 All crashes on rural, two-lane curves

Proposed Superelevation (0.12) 1.00 0.12 All crashes on rural, two-lane curves

Existing Lane Width (11 ft) 1.03 12-ft All crashes on rural, two-lane roads

Proposed Lane Width (12 ft) 1.00 12-ft All crashes on rural, two-lane roads

Existing Shoulder Width (0 ft) 1.29 6-ft All crashes on rural, two-lane roads

Existing Shoulder Width (2 ft) 1.17 6-ft All crashes on rural, two-lane roads

Proposed Shoulder Width (8 ft) 0.93 6-ft All crashes on rural, two-lane roads
Note that CMFs should 

only be multiplied if they 

apply to the same crash 

types and severities and 

the HSM urges caution 

in multiplying more than 

three CMFs.

Note that Caltrans multiplied 

four CMFs whereas the HSM 

urges caution in multiplying 

more than three CMFs.

22

The safety impact of the proposed design compared to the existing design is 

estimated by taking the ratio of the respective CMFs (CMF for proposed design 

divided by CMF for existing design). Table 3 summarizes the safety impacts for the 

scenarios of interest. Since the existing shoulder width varied between zero and two 

feet, Caltrans took the average of the CMFs for the two conditions to represent the 

CMF for the existing condition. Hence, a CMF of 1.23 (average of 1.17 and 1.29) 

was used to represent the CMF for the existing shoulder width.

Table 3. Summary of CMFs and Estimated Safety Impacts

Feature Proposed 

Condition

Existing 

Condition

CMF

(Proposed)

CMF 

(Existing)

Safety Impact of Proposed

Relative to Existing Design

Radius 400 ft 300 ft 3.42 4.23 0.81 (19% reduction)

Superelevation 0.120 0.072 1.00 1.14 0.88 (12% reduction)

Lane Width 12 ft 11 ft 1.00 1.03 0.97 (3% reduction)

Shoulder Width 8 ft 0-2 ft 0.93 1.23 0.76 (24% reduction)

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

proposed design exception and mitigation measures compared to the 

existing conditions. As recommended in the HSM (5), the CMFs were 

multiplied to estimate the cumulative effect of the combined treatments.

In this case, all 24 observed crashes within Curve 2 are considered as “total 

crashes” since the study section includes the curve only. As such, the CMFs 

in Table 2 apply to the same crash types and severities. Therefore, it was 

acceptable to multiply the CMFs to estimate the combined safety impact.

The following shows the calculation and resulting CMF for the estimated 

combined effect.

Combined CMF = 0.81 * 0.88 * 0.97 * 0.76 = 0.53

The three-year observed crash history (24 crashes) was used to 

estimate the annual crashes without treatment (i.e., no changes to 

existing conditions) as shown in the following calculation. 

Estimated Annual Crashes without Treatment = 24 crashes / 3 years = 

8.0 crashes/year 

The combined CMF can then be applied to the estimated annual

crashes without treatment to estimate the annual crashes 

with treatment (i.e., proposed design) as shown in the following 

calculation.

Estimated Annual Crashes with Treatment = 0.53 * 8.0 crashes/

year = 4.24 crashes/year

Based on the above calculations, the proposed design exception 

and mitigation measures are anticipated to perform better 

than the existing conditions. Specifically, the proposed design is 

anticipated to reduce crashes by 3.8 crashes per year (8.0 

crashes per year minus 4.24 crashes per year). While the 

proposed design is anticipated to improve safety compared 

to the existing conditions, the design standard would provide 

a higher level of safety. In the future, the same process can 

be used to estimate the safety performance of the design 
23

standard. The safety performance of the proposed design can then be compared to the existing 

conditions and design standard. The estimated safety impacts can then be considered in conjunction 

with other factors such as project cost, operational performance, and environmental impacts.

For more information about the case study, please contact Thomas M. Schriber, Caltrans; Traffic Liaison & 

Reviewer; 916-654-7138; thomas_schriber@dot.ca.gov. 

Summary of Findings

CMFs can be applied to quantify the safety impacts of design elements and estimate the effects of mitigation 

measures. Combined, these results can be used to evaluate the overall impacts of design exceptions on the 

estimated safety performance of a facility. In this case, District 1 of Caltrans used CMFs in order to quantify the 

safety impacts of increasing the radius of a curve, increasing the superelevation, increasing the width of the 

travel lane, and increasing the shoulder width. Even though some of the proposed changes did not meet the 

design standard based on California’s design documents, the use of CMFs demonstrated that the proposed 

improvements could result in a substantial reduction in crashes compared to the existing conditions. Further 

analysis could compare the estimated safety impact of proposed design exceptions with respect to design 

standards. The results of the safety analysis could also be considered in conjunction with other factors such as 

project cost, operational performance, and environmental impacts.

Case Study #2: Evaluating Design Decisions 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 assess the safety impact of individual design elements and evaluate the overall impact of design 

exceptions on the safety performance of a facility. 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 

design exception process. To promote data-driven decision-making, MoDOT established a policy to conduct a 

safety analysis as part of the evaluation of design exceptions when the design exception “involves safety related 

features that are adequately addressed in the AASHTO Highway Safety Manual.” Examples of safety related 

features identified in the MoDOT policy include lane width, shoulder width, shoulder type, rumble strips, turn lanes, 

bridge width, bridge approach rail, horizontal alignment, vertical alignment, grade, horizontal clearance, vertical 

clearance, and guardrail, but not all of these features are adequately addressed in the HSM. MoDOT also notes 

that this list is not inclusive and “any other items that may be perceived as a safety concern will also follow these 

requirements.”

Project Description

MoDOT Central District proposed a project on a rural, two-lane section of Route 42 in Kaiser, MO. The existing 

conditions included a narrow cross-section with lane widths of 10.5 feet and unpaved shoulders. The proposed 

conditions included paved shoulders (2 feet in both directions) and shoulder and centerline rumble stripes. The 

design guidelines for minor roads in Missouri identify minimum expectations for several design features, including 

a consistent shoulder width of 2 to 4 feet. In this case, the District conducted an analysis, using Part C Predictive 

Methods of the HSM, to document the potential safety benefits of the proposed conditions compared to the 

existing conditions. A separate analysis is also provided to compare the safety performance of different shoulder 

widths (2 feet versus 4 feet). The existing (1-ft turf shoulders), proposed (2-ft paved shoulders), and alternative 

conditions (4-ft paved shoulders) for Route 42 are summarized in Table 4. The baseline conditions from the HSM 

are also provided in Table 4 (5).
24

Table 4. Summary of Roadway Characteristics and Baseline Conditions

Roadway Characteristics Existing1 Proposed1 Alternative1 Baseline2

Traffic volume 4,250 4,250 4,250 0 – 17,800

Length (mi)3 1.0 1.0 1.0 Not specified

Lane width (ft) 10.5 10.5 10.5 12

Shoulder width (ft) 1 2 4 6

Shoulder type Turf Paved Paved Paved

Horizontal curve length (mi) 0 0 0 0

Radius of curvature (ft) 0 0 0 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

Shoulder rumble stripes (yes/no) No Yes Yes Not 

applicable

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) 4 4 4 3

Segment lighting (yes/no) No No No No

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

Notes:

1. The purpose of the analysis was to estimate the relative change in safety for the three scenarios. While some of the elements listed in 

the table are present along the corridor (e.g., horizontal curvature and vertical grade), there is no change in the relative conditions for 

these elements among the three scenarios. As such, the values are assumed to be zero. Intersections were not included in the analysis 

for a similar reason.

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

3. The study section is longer than one mile, but a one-mile section was assumed for the analysis. This was acceptable because the

purpose of the analysis was to estimate the relative change in safety for the three scenarios, and the segment length remained 

constant among the three scenarios. As such, the results are presented in crashes per mile per year.

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 HSM. 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 4 (5).

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

Where:

NSPF = Predicted total crash frequency for baseline conditions.

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

L = Segment length (mi).

Applying Equation {1} to the existing conditions with an AADT of 4,250 vehicles per day and a segment length of 

1.0 mile, the predicted total crash frequency for the baseline conditions is computed as follows:

NSPF = 4,250 * 1.0 * 365 * 10-6 * e-0.312

NSPF = 1.14 crashes per year
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.

25

CMFs were then identified to reflect the conditions of interest. The HSM Part C 

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

SPF from Equation {1}. The CMFs are provided in Table 5 (5).

Table 5. Summary of CMFs for Conditions of Interest

Roadway Characteristics Existing Proposed Alternative

Lane width 1.10 1.10 1.10

Shoulder width and type 1.24 1.17 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

Shoulder rumble stripes 1.00* 0.87* 0.87*

Passing lanes 1.00 1.00 1.00

Two-way left-turn lane 1.00 1.00 1.00

Roadside design 1.07 1.07 1.07

Lighting 1.00 1.00 1.00

Automated speed enforcement 1.00 1.00 1.00

* Note that Part C of the HSM does not include a CMF for shoulder rumble stripes. Instead, MoDOT obtained the CMF from workshop 

materials prepared by FHWA (15) and used the CMF to reflect the expected safety impacts of the shoulder rumble stripes.

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

the conditions of interest. As recommended in the HSM (5), 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, 

proposed, and alternative conditions are 1.46, 1.13, and 1.05 

respectively.

CMFCombined (Existing) = 1.10*1.24 *1.07*1.0010 = 1.46

CMFCombined (Proposed) = 1.10*1.17*0.94*0.87*1.07*1.008 = 1.13

CMFCombined (Desired) = 1.10*1.09*0.94*0.87*1.07*1.008 = 1.05

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.
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. 

Note that calibrated SPFs provide 

more reliable results than noncalibrated SPFs for predicting 

crash frequency. As such, 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

NPredicted = NSPF * CMFCombined {3}

Where:

NPredicted = Predicted total crash frequency for conditions of interest.

Computations for the three scenarios of interest are shown below and 

summarized in Table 6. Note that the baseline predicted crashes are identical for 

the three scenarios.

NPredicted (Existing) = 1.14 * 1.46 = 1.66

NPredicted (Proposed) = 1.14 * 1.13 = 1.29

NPredicted (Desired) = 1.14 * 1.05 = 1.20

Table 6. Summary of Computations for Predicted Annual Crashes per Mile

Scenario NSPF 

Equation {1}

CMFCombined

Equation {2}

NPredicted

Equation {3}

Percent Reduction

(Compared to Existing)

Existing 1.14 1.46 1.66 --

Proposed 1.14 1.13 1.29 22%

Alternative 1.14 1.05 1.20 28%

Note that the results reflect crashes per mile per year because the segment length was specified as one mile. Projected over a 10-year 

period or over a longer segment, the proposed and alternative design conditions will provide a notable reduction in crashes compared 

to the existing conditions. Recall that certain roadway characteristics (e.g., horizontal curvature, vertical grade, and intersections) were 

not included in the analysis because the related conditions did not change among the three scenarios. As such, the comparison of the 

relative safety impacts of the three scenarios is based on the percent change in crashes rather than the predicted number of crashes.

Based on the above calculations, the proposed design is predicted to 

perform better than the existing conditions with respect to safety. 

Specifically, the proposed design is predicted to reduce total crashes by 

0.37 crashes per mile per year (1.66 crashes per year minus 1.29 crashes 

per mile per year). This represents a 22 percent reduction in predicted 

total crashes. The alternative scenario is predicted to provide a higher 

level of safety than both the existing and proposed conditions.

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.highwaysafetymanual.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.

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 
If a calibrated SPF 

is used to estimate 

the predicted 

crash frequency, 

then a formal 

cost-benefit analysis 

could be conducted 

to determine whether 

or not the additional 

shoulder width for the 

alternative scenario 

is worth the added 

project costs.

It is desirable to compare 

the estimated safety 

performance of the 

proposed conditions 

with respect to both the 

existing conditions and 

design standards.

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.

Note that 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.

27

understand the potential safety impacts of individual design elements and 

design exceptions. MoDOT conducts similar safety analyses as part of the 

evaluation of design exceptions that involve safety related features. 

In this case, Central District of MoDOT used the Predicted Crash Frequency with 

CMF Adjustment method in order to quantify the safety impacts of installing 

a paved shoulder with shoulder and centerline rumble stripes. Two different 

scenarios are compared to the existing conditions. The proposed condition 

included a paved shoulder width of two feet, while the alternative condition 

based on design guidelines is a paved shoulder width of four feet. The 

use of this quantitative method demonstrated that the proposed improvements 

could result in a substantial reduction in crashes compared to existing 

conditions. 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 the safety impacts of 

design decisions. Some are directly related to limitations in the progress of safety 

research, while others apply to a lack of training. General challenges related 

to limitations in the progress of safety research include availability of CMFs, 

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

Specific challenges related to the quantification of safety performance for 

design decisions include insufficient expertise (i.e., understanding how to 

select and apply appropriate methods) and complex scenarios.

Availability of CMFs

A general challenge is the availability of CMFs for specific design 

elements or mitigation measures. The CMF Clearinghouse (7) contains 

over 3,000 CMFs for a wide range of safety countermeasures under a 

variety of conditions. However, CMFs are still lacking for a large number 

of design elements and treatments, including many of the 13 controlling 

criteria, combination treatments, and those treatments 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 safety effects of the 

13 controlling criteria, including a reference to specific CMFs when 

available. CMFs are included in the HSM for five of the 13 design 

criteria for rural, two-lane roads and two design criteria for rural 

multilane roads. Other CMFs are available in the CMF 

Clearinghouse (7) and recently completed research studies such 

as NCHRP Project 17-45 (9). Additional research is underway 

to develop CMFs for design criteria and 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 (7) provides a “Most Wanted List” for 

CMFs. Users can access the website and add to the list by 

submitting ideas for future CMF research or current needs. While 

the research would need to be completed, this link provides 

users with the opportunity to share their CMF needs.
Caltrans noted that CMFs were 

not available in the HSM for all 

proposed conditions in the design 

exception case study. While this 

is a limitation of existing research, 

FHWA’s CMF Clearinghouse provides 

additional CMFs that may be 

considered for future safety 

analysis of design elements.

28

Design Criteria Rural 

2-Lane

Rural 

Multilane

Urban 

Arterial

Suburban 

Arterial Freeway

Design Speed -- -- -- -- --

Lane Width CMF in HSM 

Section 13.4.2.1

CMF in HSM 

Section 13.4.2.1 -- 1 -- 1 -- 2

Shoulder Width CMF in HSM 

Section 13.4.2.4

CMF in HSM 

Section 13.4.2.4 -- -- -- 3

Bridge Width -- 4 -- -- -- --

Horizontal 

Alignment

CMF in HSM 

Section 13.6.2.1 -- 5 -- -- -- 6

Vertical 

Alignment -- -- -- -- --

Grade CMF in HSM 

Section 13.6.2.3 -- -- -- --

Stopping Sight 

Distance -- -- -- -- --

Cross Slope -- -- -- -- --

Superelevation CMF in HSM 

Section 13.6.2.2 -- -- -- --

Horizontal 

Clearance / 

Lateral Offset

-- 7 -- 7 -- 7 -- 7 -- 7

Vertical 

Clearance -- -- -- -- --

Structural 

Capacity -- -- -- -- --

-- Indicates that a CMF is not available in the current edition of the HSM.

1 The HSM Chapter 12 (Predictive Method for Urban and Suburban Arterials) does not include a CMF for lane width on urban and 

suburban arterials. Recent research from NCHRP Project 3-72 found little to no difference in safety performance for urban and suburban 

arterials in the range of lane widths from 10 to 12 feet. 

2 The HSM currently does not include a CMF for lane width on freeways; however, NCHRP Project 17-45 has developed a proposed HSM 

safety prediction methodology for freeways that includes lane width.

3 The HSM currently does not include a CMF for freeway shoulder widths; however, NCHRP Project 17-45 has developed a proposed HSM 

safety prediction methodology for freeways that includes width for right (outside) and left (inside) shoulders.

4 The FHWA CMF Clearinghouse has some information and provides CMFs for changing bridge widths for certain roads and volumes. 

5 The HSM Chapter 11 (Rural Multilane Highways) does not include a CMF for horizontal curves. There are several CMFs for horizontal 

curve radius in the FHWA CMF Clearinghouse for certain roads and conditions.

6 The HSM currently does not include a CMF for horizontal curves on freeways; however, NCHRP Project 17-45 has developed a proposed 

HSM safety prediction methodology for freeways that includes the safety effects of horizontal curves.

7 The HSM does not contain CMFs for lateral offset. The CMFs for shoulder width in part reflect the safety effects of lateral offset.

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 (5) and CMF Clearinghouse (7) 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 
Caltrans indicated that 

CMFs were used to 

estimate the safety impacts

of design elements. The 

results of the analysis 

were included in the 

documentation of the 

design exception, but were 

not directly used in the 

decision making process. 

Instead, Caltrans used the 

results as a ‘point of discussion’. 

Part of the reason was that for 

District 1, this was the first 

application of CMFs in the 

design exception process, 

and the design team was not 

comfortable with the use of the 

results due to their lack of 

familiarity. This will hopefully 

change in the future as agencies 

continue to adopt the procedures 

in the HSM and incorporate CMFs 

in the project development process, 

particularly in estimating the safety 

impacts of design elements.

Contact information for the FHWA 

field offices is available at: http://

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

29

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 (7) under FAQs.

Estimating the Effects of Multiple Treatments

The current practice for many agencies is to assume that CMFs are 

multiplicative; this is the current method presented in the HSM (5) and posted 

on the CMF Clearinghouse (7). There are relatively few studies that estimate 

CMFs for combinations of countermeasures. It is far more common for 

studies to estimate CMFs for individual treatments. Consequently, it is 

difficult to accurately estimate the effects of combinations of treatments. In 

brief, the recommended approach 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 (10, 11).

Insufficient Expertise

A specific challenge for the design engineer could be that they have 

insufficient expertise to quantify safety impacts using CMFs and related 

methods. The HSM and related resources are relatively new tools. As 

such, they have only recently gained popularity among transportation 

professionals and their use has been mostly limited to applications 

within the roadway safety management process. There are a number 

of opportunities to quantify safety impacts in other aspects of the 

project development process (e.g., design decisions and exceptions), 

but it may be necessary to solicit input or assistance from those who 

are more familiar with the selection and application of CMFs and 

related methods. If the design engineer does not have the needed 

expertise, then they can solicit outside expertise from the State 

Highway Safety Engineer (or equivalent), FHWA Division Office, or 

consultants for further guidance and assistance with the selection 

and/or application of CMF-related methods and interpretation of 

results. The National Highway Institute also offers several courses 

related to the quantification of safety using CMFs, including the 

Application of CMFs (#380093) and Science of CMFs (#380094).
District 1 of 

Caltrans did not 

have access to 

applicable SPFs. 

As such, the 

number of 

observed crashes 

(three-year history) 

was used to estimate 

the crashes without 

treatment. The 

estimated treatment 

effect is a function 

of the CMFs and is 

applicable regardless 

of whether or not SPFs 

are used to estimate 

the crashes without 

treatment. SPFs, 

particularly in 

combination with the 

observed crash history, 

offer a more rigorous 

method to estimate the 

crashes without treatment.

30

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 of this guide 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 (5) and related documentation, Integrating the HSM into the 

Highway Project Development Process (6).
31

REFERENCES

1. Federal Aid Policy Guide. Subchapter G – Engineering and Traffic Operations, 

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

Washington, DC, 1997.

2. Stein, W.J. and Neuman, T.R. Mitigation Strategies for Design Exceptions. 

Publication FHWA-SA-07-011. Federal Highway Administration, Washington, DC, 

2007.

3. 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/. 

4. Introduction to Safety Performance Functions. Publication FHWA-SA-13-016, 

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

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

5. American Association of State Highway and Transportation Officials 

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

6. 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

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

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

8. 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.

9. 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/Freeways

Interchanges/ISATe_V06i.xls

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

Its Applications.” Public Roads. Federal Highway Administration, 

Washington, D.C., 2011.

11. 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.

12. 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/.

13. 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/.

14. Fact Sheet Exception(s) to Advisory Design Standard(s)

(EA: 01-0B260K), prepared by Caltrans.

15. Federal Highway Administration (FHWA). Highway Safety 

Manual Practitioner’s Guide for Two-Lane Rural Highways 

Workshop, May 2009. 
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/

FHWA-SA-13-013