Empirical Bayes Identification of High Hazard Locations for Older Drivers
1994-10
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Empirical Bayes Identification of High Hazard Locations for Older Drivers
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1994-10
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Minnesota Department of Transportation
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Report
Abstract
As part of an emphasis on improving road safety, the Minnesota Department of Transportation seeks to identify
the locations where older drivers were over-represented in accident records. This research project reports on the
use of three methods to help improve the accuracy of identifying locations where older drivers were at increased
risk: a basic statistical model, the Empirical Bayes statistical method and a clustering method.
Overall, the basic statistical model preformed the best. The clustering method and the Empirical Bayes method
could both be usefully applied to the traditional task of high-hazard identification--that of automatically screening
a large number of accident sites to identify potential candidates for improvement. This information can point the
way to areas that may require a more detailed engineering analysis.
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Minnesota Department of Transportation
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Davis, Gary A.. (1994). Empirical Bayes Identification of High Hazard Locations for Older Drivers. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/156513.
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