Older drivers and accidents: A meta analysis and data mining application on traffic accident data

Authors:
Evrim Bayam;Jay Liebowitz;William Agresti
Affiliations:
Department of Information Technology, Graduate Division of Business and Management, Johns Hopkins University, 9601 Medical Center Drive, Rockville, MA 20850-3332, USA;Department of Information Technology, Graduate Division of Business and Management, Johns Hopkins University, 9601 Medical Center Drive, Rockville, MA 20850-3332, USA;Department of Information Technology, Graduate Division of Business and Management, Johns Hopkins University, 9601 Medical Center Drive, Rockville, MA 20850-3332, USA
Venue:
Expert Systems with Applications: An International Journal
Year:
2005

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Abstract

Teenage driving and associated accidents have been thoroughly studied. With the graying of our population in the United States, a focus on senior drivers and related accidents is needed. Unfortunately, there is not one comprehensive study that reviews the major existing studies conducted on senior drivers and accidents. In examining the literature, it also appears that data mining has rarely been applied in studying relationships between senior driver characteristics and accidents. This paper addresses these two needs by providing a meta-analysis of the existing literature on senior drivers and showing how data mining techniques could be used in this application.