Modeling the Probability of Freeway Rear-End Crash Occurrence
Publication: Journal of Transportation Engineering
Volume 133, Issue 1
Abstract
A microscopic model of freeway rear-end crash risk is developed based on a modified negative binomial regression and estimated using Washington State data. Compared with most existing models, this model has two major advantages: (1) It directly considers a driver’s response time distribution; and (2) it applies a new dual-impact structure accounting for the probability of both a vehicle becoming an obstacle and the following vehicle’s reaction failure . The results show for example that truck percentage-mile-per-lane has a dual impact, it increases and decreases , yielding a net decrease in rear-end crash probabilities. Urban area, curvature, off-ramp and merge, shoulder width, and merge section are factors found to increase rear-end crash probabilities. Daily vehicle miles traveled (VMT) per lane has a dual impact; it decreases and increases , yielding a net increase, indicating for example that focusing VMT related safety improvement efforts on reducing drivers’ failure to avoid crashes, such as crash-avoidance systems, is of key importance. Understanding such dual impacts is important for selecting and evaluating safety improvement plans for freeways.
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Acknowledgments
The writers thank the Washington State Department of Transportation and the Highway Safety Information System, Federal Highway Administration for their help in providing the data used in this study. The writers also thank the anonymous reviewers, whose constructive comments significantly improved the paper.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 133 • Issue 1 • January 2007
Pages: 11 - 19
Copyright
© 2007 ASCE.
History
Received: Feb 14, 2006
Accepted: May 16, 2006
Published online: Jan 1, 2007
Published in print: Jan 2007
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