Real-Time Estimation of Accident Likelihood for Safety Enhancement
Publication: Journal of Transportation Engineering
Volume 131, Issue 5
Abstract
Unlike conventional traffic safety studies that focused on histrionic data analyses, this study attempts to identify traffic conditions that might lead to a traffic accident from real-time freeway traffic data. An innovative feature of the study is to apply the concept, real-time and preaccident, to accident studies by integrating real-time capabilities in advanced traffic management and information systems (ATMIS). In this study, the traffic conditions leading to more accidents are defined as real-time accident likelihood, and the accident likelihood is estimated by employing a nonparametric Bayesian model. The main goal of the study is to remove hazardous traffic condition prior to accident occurrence by incorporating the real-time accident likelihood into ATMIS. This study estimates real-time accident likelihood from empirical data on I-880 freeway in California, and shows its applicability as an accident precursor.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 131 • Issue 5 • May 2005
Pages: 358 - 363
Copyright
© 2005 ASCE.
History
Received: Mar 5, 2004
Accepted: Jul 21, 2004
Published online: May 1, 2005
Published in print: May 2005
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