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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2008. Accident Modification Factors for Traffic Engineering and ITS Improvements. Washington, DC: The National Academies Press. doi: 10.17226/13899.
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2008. Accident Modification Factors for Traffic Engineering and ITS Improvements. Washington, DC: The National Academies Press. doi: 10.17226/13899.
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Page 5
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2008. Accident Modification Factors for Traffic Engineering and ITS Improvements. Washington, DC: The National Academies Press. doi: 10.17226/13899.
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Page 6
Page 7
Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2008. Accident Modification Factors for Traffic Engineering and ITS Improvements. Washington, DC: The National Academies Press. doi: 10.17226/13899.
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Page 8
Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2008. Accident Modification Factors for Traffic Engineering and ITS Improvements. Washington, DC: The National Academies Press. doi: 10.17226/13899.
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4The Problem In order to achieve the greatest return on the investment of their often limited safety budgets, state and local highway safety engineers must continually make program planning decisions concerning whether to implement a specific safety treatment and/or to determine the costs and benefits of alternative treat- ments. Making these program planning decisions requires an accurate measure of safety treatment effectiveness. This meas- ure of effectiveness is referred to as a crash reduction factor (CRF) or accident modification factor (AMF). Both of these terms reflect the percentage reduction (or increase) in crashes that can be expected after implementing a treatment or program, as derived through research studies and program evaluations. The level of effectiveness of a treatment is referred to in much of the current safety literature as a CRF or an AMF. The two terms are simply different ways of expressing treat- ment effectiveness levels. An AMF provides the expected proportional reduction in crash frequency and is developed by dividing the CRF by 100 and subtracting the result from 1.00. Thus, a treatment shown to reduce crashes by 15 percent (CRF = 15%) would have an AMF of 0.85 (1.00 − 15/100). An AMF of 1.00 represents no effect on safety, while AMFs above 1.00 indicate that the treatment can be expected to result in an increase in crashes. The term AMF will be used in this report for consistency with other NCHRP efforts. The importance of AMFs to state department of trans- portation (DOT) safety engineers was documented by a survey conducted as part of this study. The survey was sent to the identified state safety engineer (usually in the traffic engi- neering office) and to a state staff person involved with the intelligent transportation systems (ITS) program. All states were surveyed, and 34 provided responses. Of the 34 states responding, all but two indicated that they use AMFs, and most states use them for multiple purposes. AMFs are used for the following, listed from most frequent use to least frequent use: • Economic analysis of safety treatments, • Treatment selection for short-term programming of safety improvements, • Project development to address safety aspects of large projects, • Design policy development, • The design exception process, and • Public awareness campaigns. In addition to their long-term use by state and local safety engineers, AMFs are key components of the current generation of safety tools and resources being developed for the safety field. They are used in FHWA’s Interactive Highway Safety Design Model (IHSDM) to predict future safety for different alternative roadway designs or rehabilitation designs (1). AMFs are being incorporated into FHWA’s SafetyAnalyst, where they are applied to estimate the safety effectiveness measures within the economic appraisal tool (2). AMFs will be a key component of the Highway Safety Manual (HSM), which is now being produced by a TRB task force and NCHRP (3). Finally, better AMFs will allow AASHTO and NCHRP to update guides already developed or guides to be developed in the future for assisting states and local users with the imple- mentation of AASHTO’s Strategic Highway Safety Plan (4). Even though accurate AMFs are critically important to states and municipalities and to the safety tools previously mentioned, there is no accepted standard set of AMFs. This situation is due to the fact that the accuracy and reliability of many published AMFs is questionable and that no AMFs exist for many impor- tant safety treatments. The lack of AMF reliability, accuracy, and comprehensiveness has been documented in this study, in prior work, and in ongoing HSM development efforts. The sources of the problem include the following: • Origins/Transferability. The origins of AMFs are not always clear to the end user. Some states have developed AMFs using their own crash data. Other states have simply adopted AMFs C H A P T E R 1 Introduction

that were developed in other states. The extent to which AMFs are valid when transferred to places beyond the devel- opment domain (e.g., from one state to another) that have different roadway, traffic, weather, driver and other relevant characteristics, as well as different accident investigation practices, is unknown. • Methodological Issues. Many existing AMFs are derived from before-after analysis of actual countermeasure imple- mentation. Indeed, such before-after analysis, as opposed to cross-sectional/regression-type analysis, produces the best AMF estimates, but only if conducted properly. Unfortu- nately, many current studies reflect changes in crash experi- ence resulting from improvements at sites that experienced an unusually high number of crashes in the before-treatment period. The selection bias that results from this approach can yield significantly exaggerated AMF estimates due to the phenomenon of regression to the mean. Other methodolog- ical problems that are often found include the following: – Failure to properly separate out the safety effects of other changes (e.g., traffic volumes, the impacts of other treat- ments implemented at the same time, crash reporting differences between jurisdictions or across time, and underlying crash trends across time). – Sample sizes that are too small. Large numbers of sites with the same combination of applied countermeasures are needed for a valid analysis. For some treatments and the subsequent type of crash reduction expected, hun- dreds or thousands of locations may be necessary, along with many years of crash data. (Pedestrian treatments and crashes are a good example of this problem.) – Use of comparison groups that are unsuitable for a variety of reasons. – Incorrect interpretation of accuracy of estimates or presentation of results without statements of accuracy. • Variability. The value of an AMF may depend on a vari- ety of factors, such as traffic volumes, crash experience, and site characteristics. Thus, research that results in a sin- gle AMF value may be of limited applicability. Accident modification functions rather than factors may be more appropriate. Several of the AMFs presented in this report are indeed functions. • Crash Migration and Spillover Effects. It is possible that countermeasures implemented in a particular location may be followed by migration of crashes to adjacent locations. For example, the conversion of two-way stop control to all- way stop control at an intersection may lead to an increase in crashes at surrounding intersections that continue to operate as two-way stop control due to driver confusion. Likewise, the prohibition of left turns at an intersection may lead to an increase in left-turn crashes at upstream and downstream intersections. Existing AMFs rarely account for this phenomenon. For AMFs to be useful, they have to account for these effects or, at a minimum, recognize their existence. • Lack of Effectiveness Information. AMFs have not been developed for many ITS improvements and other opera- tional strategies. For example, on many freeways, safety serv- ice patrols have become more common as a way of reducing the impact of incidents and reducing secondary accidents. However, no AMFs exist for this countermeasure. Other ITS countermeasures of high interest for which no reliable AMFs exist include dynamic or changeable message signs (including those related to variable speed limits), real-time warning systems (e.g., severe alignment or adverse weather), and pedestrian safety treatments (e.g., in-pavement cross- walk lighting and countdown signals). • Combinations of Improvements. Most AMFs are designed for individual improvements. However, multiple improve- ments are typically made when a facility is being rebuilt. States use different formulas for combining individual AMFs when considering multiple treatments. However, there is very little sound research on the multitude of actual combinations of treatments that exist in practice. Thus, it is unknown whether current predictions based on combining individual AMFs accurately capture the true combined effect. • Publication/Citation Issues. A less-cited issue that is preva- lent in much of the research is related to the quality of the material that is available and often used in the development of AMFs. Specific problems include the following: – Publication bias—the tendency to only publish studies that produced favorable results for the treatment being evaluated. – Selective citing of results—the tendency to ignore the negative aspects of results such as declining effects over time or unintended consequences that would lead to in- creases in some crash types. In some cases, a sponsoring organization may not want negative results published because it invested significant funds in a countermea- sure/intervention program. In summary, although several AMFs already exist, there are a number of issues related to the quality of those factors now being used in many states and local jurisdictions. There is a need to improve the quality of existing AMFs and to develop additional AMFs where there are currently voids. Project Objective and Overview The objective of this project was to develop reliable AMFs for traffic engineering and ITS improvements. Reliable AMFs, at a minimum, must meet the following criteria: • The AMFs are methodologically and statistically valid. Separate values for AMFs are defined for various influencing 5

factors such as the highway facility, operating condition, weather, time of day, percentage of truck traffic, and pre- existing crash history as appropriate. (Alternatively, a method could be developed for adjusting the AMFs for these influencing factors.) Should expert judgment be used in developing AMFs, it must be analysis-driven. • The applicability of the AMF is known and documented. For example, some AMFs may denote an impact on crashes only at a specific location whereas other AMFs may affect crashes for an entire stretch of roadway. Some AMFs may apply only to specific accident types or to specific pre- existing conditions (e.g., high percentages of wet weather crashes). Some may be applicable only to the state or area where the AMF is developed, and thus adjustment factors must be developed to allow application of the AMF to other regions. • The AMFs reflect improvements or combinations of improvements that are of interest to DOTs. The survey conducted as part of this study requested respondents to indicate which treatments were considered priorities for AMF development. • The AMFs reflect the impact of the improvement on differ- ent crash categories. Crash categories might include total crashes, severe-injury crashes, property-damage-only crashes, and specific crash types (such as rear-end and angle). • The AMFs reflect variability. The best estimate of the AMFs, along with some technique that reflects their vari- ability (such as ranges, confidence intervals, standard deviation, or some other technique) should be presented. • The AMFs reflect the savings in “total harm” provided by the treatments. Many treatments affect both crash fre- quency and crash severity, some affect just crash severity, and some decrease crashes at one level of severity and increase crashes at another level of severity (e.g., traffic sig- nalization can decrease more-severe angle crashes but increase less-severe rear-end crashes). AMFs must capture changes in crash severity as well as changes in crash fre- quency in order to measure “harm savings.” The identification and development of AMFs that meet most of the above requirements involved a project effort with the following eight tasks divided among two phases. Phase I included the following tasks: • Task 1—Review of completed and ongoing studies to doc- ument existing AMFs, • Task 2—Survey of states to determine AMF use and priori- ties and availability of data concerning treatment installation for use in new AMF development, • Task 3—Follow-up interviews with states having poten- tially usable treatments and data, • Task 4—Determination of whether available data from states or other sources could be used in AMF development, • Task 5—Development of interim report and work plan, and • Task 6—Project briefing for oversight committee. Phase II included the following tasks: • Task 7—Execution of work plan to collect necessary data and develop/improve AMFs and • Task 8—Preparation of final report. Thus, Phase I of the effort was focused first on the extrac- tion of information on existing AMFs through a critical review of research literature. The documentation included detailed descriptors of the AMFs, the conditions (e.g., roadway types and locations) for which each AMF was applicable, and a judgment of the level of predictive certainty (i.e., the quality) associated with a given AMF. The remainder of Phase I focused on a series of steps to determine high-priority AMF needs—which existing AMFs should be improved and which new AMFs should be developed within the project budget. This prioritization was based on inputs concerning “most important safety treatments” from a survey of state DOTs combined with other factors concerning the quality of the existing AMF, the size of the crash problem affected by the treatment, and the availability of data needed to develop or improve an AMF. All this information was then used to develop a work plan for the AMF development/upgrade effort. After approval by the oversight panel, the plan was exe- cuted in Phase II of the effort. This execution involved four basic types of analyses: • Empirical Bayes (EB) Before-After Evaluation. Original data were acquired to conduct an analysis and determine the crash-harm effects of a specific high-priority treatment that had been implemented within a state or states (usually at multiple sites) in the late 1990s or early 2000s in order to have a sufficient after-treatment period. The analysis made use of the latest statistical methodologies for before-after studies and produced AMFs with the highest feasible level of confidence. This analysis required not only detailed descriptions of the historic treated sites (e.g., treatment specifics, locations, and dates of installation) and good before-treatment and after-treatment crash, inventory, and traffic data on the treated sites, but also comparable data on a large reference group of somewhat similar sites. Thus, the analysis required either that the project team had easy access to both current and historical crash, inventory, and traffic data, or that the implementing state was willing and able to provide the linkable data files necessary. Since FHWA’s Highway Safety Information System (HSIS) includes historic crash, inventory, and traffic data from nine states, and since most non-HSIS states do not store 6

historic roadway inventory data, attempts were made to find treatments implemented in these HSIS states. • Reanalysis of Existing/Supplemental Data. An existing AMF was improved by applying a more rigorous evaluation methodology to existing data from a prior study. The pre- ferred methodology was again the EB before-after approach. Again, this required adequate data for both treatment and non-treatment sites. In many cases, supplemental data (e.g., data for the development of a reference group) were acquired to meet this requirement and enhance the analysis. • Analysis-Driven Expert Panel. An expert panel was con- vened to review the existing studies concerning a specific AMF and then define a consensus AMF based on the stud- ies reviewed. The expert panel included expert researchers (knowledgeable about the AMFs of interest and the strengths and weaknesses of study methods) and a group of expert state and local AMF users (i.e., safety engineers) with knowledge of the specifics of the AMFs needed and the real- world conditions under which those evaluated treatments were probably implemented. At times, limited additional analyses were conducted. The use of an expert panel required that the body of literature be robust enough to be subject to assimilation/meta-analysis by team members and then presented to an expert panel to develop a reliable AMF with at least a medium-high level of confidence. • Cross-Section Modeling. A cross-sectional model was de- veloped and used for the derivation of an AMF for a specific treatment. Some treatments of interest are not installed or changed in a manner that allows for a before-after evalua- tion. For example, it is unlikely that changes would be made to roadside slopes without making other changes, such as addition of a shoulder, at the same time. For these types of treatments, the development of road safety models is still an alternative to determine safety effectiveness. It is important to note that other AMF projects were going on at the same time as NCHRP Project 17-25. At approximately the same time that NCHRP Project 17-25 was initiated, NCHRP and a TRB task force also began a series of projects aimed at the planned 2008 publication of the first edition of the Highway Safety Manual (HSM) (see www.highwaysafetymanual.org/) (3). The HSM will be a repository of (1) current knowledge related to roadway safety treatments, (2) tools for use in pre- dicting the safety effects of different roadway design alternatives for various classes of roadways, and (3) tools for identifying sites needing safety improvements and the best treatments for them. NCHRP has funded the following projects in support of the HSM: • NCHRP Project 17-18(04), Highway Safety Manual, was a scoping study that included the development of the initial concept, outline, and prototype procedure chapter. • NCHRP Project 17-27, Parts I and II of the Highway Safety Manual, included documentation of the state of current safety knowledge and preparation of chapters that in- cluded AMFs. • NCHRP Project 17-26, Methodology to Predict the Safety Performance of Urban and Suburban Arterials, included the development of predictive tools and an HSM chapter for urban and suburban arterials. • NCHRP Project 17-29, Methodology to Predict the Safety Performance of Rural Multilane Highways, included the development of predictive tools and an HSM chapter for rural multilane highways. • NCHRP Project 17-34, Prepare Parts IV and V of the High- way Safety Manual, included the development of chapters for roadway safety management and safety evaluations. • NCHRP Project 17-36, Production of the First Edition of the Highway Safety Manual, was preparation of the first edition of the HSM for publication. The safety knowledge documented in the HSM is being stated in terms of AMFs, and the HSM safety prediction tools include AMFs as a key component. Because the AMFs devel- oped in NCHRP Project 17-25 are so closely related to the AMFs developed for and documented in the HSM and because the safety predictive tools for urban and suburban arterials and for rural multilane roads both require AMFs, this project and NCHRP Projects 17-26 and 17-29 were closely coordinated by the different teams, with information being shared on a regular basis. The criteria developed in NCHRP Project 17-25 for assessing AMF quality served as the basis for criteria used in NCHRP Project 17-27. However, there were differences in how the final decisions on what con- stituted “acceptable AMFs” were made. There are also differ- ences in AMFs chosen for publication here and those AMFs that will be in the HSM. While the AMFs published here are only those judged to have high or medium-high levels of predictive certainty, the HSM will be more inclusive, publishing AMFs with lower levels of predictive certainty ac- companied by a rating and warnings concerning use. The re- search team for NCHRP Project 17-25 conducted a detailed comparative review of the AMFs developed for this project and the AMFs developed for the HSM under NCHRP Project 17-27. This review led to some changes in the final procedures used in NCHRP Project 17-27 and to a high level of consis- tency between the AMF-related results of the two projects for the higher-certainty AMFs. In addition, to develop AMFs for treatments on urban/suburban arterials (NCHRP Project 17-26) and on rural multilane highways (NCHRP Project 17-29), researchers for NCHRP Project 17-25 organized two analysis-driven expert panels jointly with the two project teams, again ensuring both coordination of the efforts and consistency in the results. 7

Organization of Report This report provides a description of the processes followed to document existing AMFs and to determine the focus of additional AMF development efforts. The results of new AMF-related research conducted in this study are included along with recommendations for future research. The com- ponents of this report are as follows: • Chapter 2: Status of Existing AMFs and Identification of AMF Needs includes a description of the processes used to develop an initial list of important traffic engineering and ITS treatments, the process and criteria used to rate the qual- ity of AMFs discovered for these treatments, details of the AMFs that were judged to be of high or medium-high qual- ity and thus included in NCHRP Research Results Digest 299 (5), and the processes used to prioritize and select other treatments for additional analyses and AMF development. • Chapter 3: Development of New AMFs through Analysis or Reanalysis of Crash Data includes a description of the treatments studied, the data used in the evaluations, the sta- tistical methodology used, and the results of each evaluation. • Chapter 4: Development of New AMFs through Expert Panels includes a listing of the participants in each of the two panels, a description of the overall process followed for the two panels with respect to identifying and prioritizing the treatments to be explored, and the results of the panel discussions. • Chapter 5: Compilation of Recommended AMFs includes a listing of all AMFs verified, modified, or developed in this research effort along with a summary page for each AMF. • Chapter 6: Conclusions includes a summary of the study objectives, project findings, and recommendations for future AMF research. 8

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TRB's National Cooperative Highway Research Program (NCHRP) Report 617: Accident Modification Factors for Traffic Engineering and ITS Improvements explores the development of accident modification factors (AMFs) for traffic engineering and intelligent transportation system improvements. AMFs, also known as crash reduction factors, are designed to provide a simple and quick way of estimating the safety impacts of various types of engineering improvements, encompassing the areas of signing, alignment, channelization, and other traffic engineering solutions.

The following appendices to NCHRP Report 617 are available online:

* Appendix A: Methodology for Determining Crash-Harm Rating for Treatments

* Appendix B: Effects of Converting Rural Intersections from Stop to Signal Control

* Appendix C: Safety Effects of Four-Lane to Three-Lane Conversions

* Appendix D: Safety Effects of Improving Pavement Skid Resistance

* Appendix E: Evaluation of the Safety Effectiveness of Urban Signal Treatments

* Appendix F: An Empirical Examination of the Relationship Between Speed and Road Accidents

* Appendix G: Accident Modification Factors for Median Width

Two AMF treatment summaries that appear in the printed version of NCHRP Report 617 contain incorrect information. These treatments are "Add Intersection Lighting" and "Add Roadway Segment Lighting." The information in these two AMF treatment summaries has been corrected in the online version of the report.

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