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First published January 2004

Development of a Safety Resource-Allocation Model in Michigan

Abstract

Traffic crashes, injuries, and fatalities on roads and highways are of great concern to safety professionals in the United States. These problems are often caused by infrastructure inadequacies, increasing traffic, and inappropriate driver behavior. Reduction of traffic crashes and injuries is possible if an effective statewide safety-improvement program is implemented. Development of such a program requires careful investigation and analysis of historical traffic-crash data and use of an intelligent resource-allocation strategy. A statewide traffic-crash analysis was performed with crash and exposure data for the entire state of Michigan. Typically, the resources available for safety projects and programs are not sufficient to undertake a comprehensive set of safety initiatives for the entire state. Therefore, it is important that the available resources are used optimally to achieve the greatest overall safety benefits. The Office of Highway Safety Planning (OHSP), a division of the State Police Department of Michigan, provides funding to local governmental agencies for a variety of safety projects and programs to alleviate traffic crashes and injuries. Most of the projects funded by OHSP involve safety initiatives related to alcohol, the use of safety-restraint systems, enforcement of traffic regulations, and programs related to driver behavioral issues. A comprehensive analysis of traffic crashes and injuries was performed with the past five years' crash data for all 83 counties in the state of Michigan. The high-priority areas for implementing safety initiatives in the state were identified and prioritized through a safety performance index (SPI) developed as a part of this research. The SPI involves the use of historical crash data and multiple exposure variables. The development, analysis, benefits, and uses of SPI are described. Based on the SPI values, development of an optimal resource-allocation model using linear programming techniques is also presented.

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References

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Article first published: January 2004
Issue published: January 2004

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© 2004 National Academy of Sciences.
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Authors

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Kohinoor Kar
Department of Civil and Environmental Engineering, Wayne State University, 5050 Anthony Wayne Drive, 2152 Engineering Building, Detroit, MI 48202
Tapan K. Datta
Department of Civil and Environmental Engineering, Wayne State University, 5451 Cass Avenue, 208 Schaver Building, Detroit, MI 48202

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