Identifying Accident-Prone Locations Using Fuzzy Pattern Recognition
Publication: Journal of Transportation Engineering
Volume 121, Issue 4
Abstract
This paper describes a method to identify accident-prone locations (APLs) based on an assessment of factors that contribute to accidents. Current methods to identify APLs make no distinction between accidents that result from road- and nonroad-related factors. Combining accidents that are treatable and nontreatable by road improvements can be misleading and may lead to a misallocation of funds by road authorities. This paper presents a computerized procedure that uses safety experts' knowledge on classifying accidents into a finite set of categories. In practice, the categories can include any one or a combination of the three basic highway system components: the driver, the vehicle, and the road environment. Realizing the complex interaction of these components within the accident environment, the procedure employs fuzzy pattern recognition techniques for the classification process. Accidents that do not belong to the road environment category are excluded from the identification of APLs. The method is tested using data from the accident database of the British Columbia Ministry of Transportation and Highways. The method and results are described.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 121 • Issue 4 • July 1995
Pages: 352 - 358
Copyright
Copyright © 1995 American Society of Civil Engineers.
History
Published online: Jul 1, 1995
Published in print: Jul 1995
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