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FHWA Home / Safety / Systemic Safety Project Selection Tool

Systemic Safety Project Selection Tool

Appendix

Graphic - This image displays the continuous cycle among three elements, each of which contain specific processes. Element 1 begins with Identity Focus Crash Types & Risk Factors, which feeds into Screen & Prioritize Candidate Locations, followed by Select Countermeasures, and Prioritize Projects. The last process of Element 1 feeds into the one process within Element 2, Identify Funding for Systemic Program & Implement, which feeds into the sole process for Element 3, Perform Systemic Program Evaluation, which in turn feeds back into the first process of Element 1.

Applying Existing Tools and Resources in a Systemic Safety Program

Agencies can incorporate a systemic safety program into their existing tools and resources along with national resources developed specifically for this purpose. Agencies may also wish to develop customized tools for their safety management system based on data availability, staffing resources, policies, and procedures. This appendix discusses the following national-level tools and provides general advice on the type of tasks and outputs they can support:

Strategic Highway Safety Plan

The American Association of Highway and Transportation Officials (AASHTO) SHSP, last updated in 2005, provides a list of contributing factors and crash types that represent the greatest potential to reduce fatal and serious injuries. The topics covered include driver behavior, vehicle type, infrastructure, emergency medical services and data management. Additionally, each state has prepared their own SHSP, using state-level information to identify key emphasis areas within the state. Additionally, many areas are developing regional safety plans for urban areas, counties, or regions/districts. Therefore, it may be appropriate to review all available documents for selected emphasis areas that represent potential focus crash types.

Roadway Departure and Intersection Safety Implementation Plans

FHWA provided several states with assistance in developing implementation plans to address severe roadway departure or intersection crashes. These plans include an analysis of the states' crash data that is directly applicable in Element 1 of the Systemic Safety Project Selection Tool. For example, the roadway departure safety implementation plans include information useful for focus facility type selection. Additionally, the example roadway departure plan also includes information useful to identify average daily traffic (ADT) ranges where severe crashes are concentrated, which could be a risk factor as defined in Element 1 of the Systemic Safety Project Selection Tool. Furthermore, the intersection safety implementation plan methodology suggests an approach to disaggregate total intersection crashes by jurisdiction, urban and rural area types, and traffic control type. This method is similar to the approach highlighted in the Minnesota Department of Transportation (MnDOT) Case Study. Whether the process is applied to severe or total intersection crashes, it can help agencies select the focus facility types (e.g., differentiating the relative importance between urban signalized versus rural STOP controlled intersections). Both plans identify low-cost countermeasures for systematic deployment at locations that meet minimum crash level thresholds. These example countermeasures are appropriate treatments in a systemic safety program and were identified from a process similar to that outlined in the Systemic Safety Project Selection Tool. FHWA has also prepared an example data analysis package that agencies can use if they were not part of the program to develop these plans. Through numerous examples, the example data analysis package provides a framework for roadway and intersection crashes, which agencies can modify as necessary.

The key difference between the implementation plan process and the Systemic Safety Project Selection Tool is the criteria that allow the location to be eligible for treatment. The implementation plan process suggests crash frequency thresholds to identify priority locations and then treating the locations with the highest frequencies. While crash frequency can be a risk factor in the systemic safety planning process, it does not have to be the only criteria used to prioritize locations. Instead, the tool allows the agency to identify multiple risk factors. Thus, a site could be identified as a candidate for safety investment if it has multiple risk factors but no crash history.

Fatality Analysis Reporting System

The National Highway Traffic Safety Administration (NHTSA) maintains an online database of fatal crash records that could be used by agencies with no crash records. These data records contain much of the same information that was suggested for consideration when selecting focus crash types and facility types. However, it contains limited information about the road and traffic characteristics (e.g., shoulder width and type) needed for identifying, evaluating, and selecting risk factors. FARS has an online query tool that creates pin maps to display crash locations. Agencies can use pin maps to locate the fatal crashes within their jurisdiction and identify associated road and traffic characteristics. If there are enough fatal crashes within the jurisdiction, a risk factor can be determined from patterns identified in the crash characteristics.

Crash Modification Factors Clearinghouse

The CMF Clearinghouse is an online, searchable database of CMFs from past safety effectiveness studies. The FHWA allows researchers to submit recently completed studies to keep the information current. Submitted studies are rated to provide the Clearinghouse user with information about the quality of the study design and reliability of the results.

The CMF Clearinghouse can serve two purposes in a systemic safety planning process. The first is identifying and selecting countermeasures. The searchable database allows users to identify countermeasures that address the focus crash type for the focus facility type. The CMF and the study's quality rating are used to determine whether the specific countermeasure is reliable and appropriate for a systemic safety program.

The CMF Clearinghouse is also beneficial for instances where an agency does not have the capability to link crash records with road or traffic information for the purpose of identifying characteristics that are overrepresented in severe crashes, i.e., risk factors. Reviewing local crash records is the preferred way to select risk factors; however, information from the CMF Clearinghouse can identify characteristics found through research to have a proven impact on safety performance. For example, narrow travel lanes and shoulder surface type are roadway characteristics with CMFs available in the Clearinghouse for which an agency could use as potential risk factors for a rural lane departure focus crash type. When using CMFs in this way, make sure the facility types in the study are representative of the systemic safety program's focus facility types. For example, lane width CMFs from rural or interstate studies are not appropriate to consider for an urban program. If available, state or local studies can augment the consideration and may help confirm if the characteristic is a risk factor within the jurisdiction.

When using CMFs from the Clearinghouse or any other source, it is important to note that some CMFs were developed from before-after studies when the countermeasure was implemented at a high crash location. Not enough information is available at this time to determine how appropriate these CMFs might be for predicting the success of a systemic safety program. Specifically, it is unknown whether the countermeasure will be as effective at reducing crashes in a systemic safety program as it was for a specific location identified through the site analysis approach. Until systemic safety programs mature and are evaluated, understand that some CMFs may not accurately reflect expected outcomes of a countermeasure implementation on a systemic basis.

NCHRP Report 500 and FHWA's Nine Proven Safety Countermeasures

The NCHRP Report 500 series and FHWA's Nine Proven Safety Countermeasures provide a similar resource to the CMF Clearinghouse. The NCHRP Report 500 series is a 24-volume set that contains hundreds of countermeasures covering topics in the areas of engineering, enforcement, education, emergency medical services, and data management. Each document provides information regarding implementation cost and what was known regarding effectiveness when the guide was published. (Note: The CMF Clearinghouse may contain results from newer studies. Countermeasures identified in the NCHRP 500 series should be checked in the CMF Clearinghouse to find the latest available safety effectiveness information.) The Nine Proven Safety Countermeasures, first published in 2008 and updated in 2012, generally represent low-cost countermeasures appropriate for systemwide implementation.

Like the CMF Clearinghouse, these resources assist with assembling an initial list of countermeasures for the systemic safety program. Like the CMF Clearinghouse, these resources may help identify characteristics that could be used as risk factors if local crash data cannot be linked with geometric and traffic data sets.

The Highway Safety Manual

The HSM represents a collection of information and recommended practices for safety management and evaluation. Currently, the HSM includes predictive methods for rural two-lane, rural multi-lane, and urban/suburban arterials. The basis of the predictive method is crash prediction models, which are equations that use geometry, traffic and/or land use information to predict annual crash frequency for an intersection or a roadway segment. As research continues, AASHTO will update the HSM with new predictive methods and CMFs.

The HSM predictive method represents two potential uses for a systemic safety program. The first potential use is a means to identify risk factors. Based on national-level research, the inputs into the predictive method are found to directly impact crash frequency. In fact, some of the inputs (e.g., bus stops, schools, alcohol sales establishments) for the vehicle-pedestrian prediction model are surrogates to identify areas with high pedestrian densities or possibly at-risk users, such as school-age children. These factors do not necessarily cause crashes, but the models acknowledge that their presence indicates greater potential for a vehicle-pedestrian crash. Therefore, predictive method inputs could be considered as potential risk factors in a systemic safety program. Using the output of the crash prediction models is a second potential application of the HSM for a systemic safety program. The models provide a predicted average number of crashes per year, which is an estimate of the average crash potential for the site, i.e., a measurement of risk. In some cases, crash prediction model results are separated by severity and/or crash types, and then the different severities and crash types are summed together to generate the total crash potential. In such a case, the result that most closely matches the focus crash type is the ideal choice. For example, a predictive method may have one model which predicts single vehicle crashes resulting in fatalities or injuries. This might be the best and most direct comparison if the focus crash type is fatal road departure crashes and may be a more appropriate estimate of the risk being addressed by the systemic safety program than total predicted crashes. Likewise, instead of total predicted crashes, a pedestrian systemic safety program could incorporate the results of a vehicle-pedestrian crash prediction model.

SafetyAnalyst and Interactive Highway Safety Design Model

SafetyAnalyst and IHSDM are software programs that provide state-of-the-art analytical tools useful to identify and manage a systemwide program of site-specific improvements that enhance highway safety. SafetyAnalyst is capable of summarizing crashes by type and facility, which is useful to identify focus crash types and focus facilities. Additionally, SafetyAnalyst can apply the HSM predictive method for locations with data input into the software. Therefore, an agency with their system imported into the software could apply the predicted method as a means to quantify risk potential. Additionally, the systemic analysis for prioritizing locations could use some of the methods in the network screening module.

IHSDM applies the HSM predictive methods for existing and proposed corridors. The software performs detailed design reviews of corridors and is not a tool applicable to network screening. As a result, IHSDM's application in a systemic safety program is to complete a thorough estimate of crash reduction when multiple countermeasures are considered.

United States Road Assessment Program

The U.S. Road Assessment Program (usRAP), sponsored by the AAA Foundation for Traffic Safety, systematically addresses risk to identify locations where fatal and serious injury crashes can be reduced by implementing countermeasures. usRAP aims to ensure that highway infrastructure improvements are programmed based on rational assessment of risk. usRAP has developed a risk-mapping protocol that highway agencies can use to create color-coded risk maps that show variations in the level of crash risk across a road network. The results can guide priorities for highway infrastructure improvements and targeted enforcement strategies. usRAP also provides highway agencies with usRAP Tools software that can develop a recommended program of location-specific crash countermeasures for any road network based on benefit-cost analysis. A strength of the usRAP Tools software is that it uses input data based on roadway and traffic control features to assess risk and does not require site-specific crash data. While the usRAP Tools software can be used by any highway agency, it is particularly well suited for highway agencies that lack good crash data or have lower volume roads with sparse crash experience. The roadway and traffic control input data can be obtained from existing highway agency databases or, with simple training, can be coded from Internet-based photo images with an average of 20 minutes of labor per mile.

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Page last modified on August 12, 2015.
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