RESEARCH ARTICLE


Effects of Shock Waves on Freeway Crash Likelihood



Chris Lee*, Steven Volpatti
Department of Civil and Environmental Engineering, University of Windsor, Windsor, Ontario, N9B 3P4 Canada.


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Creative Commons License
© 2010 Lee and Volpatti;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Correspondence: * Address correspondence to this author at the Department of Civil and Environmental Engineering, University of Windsor, Windsor, Ontario, N9B 3P4 Canada; Tel: + 1-519-2533000; Fax: + 1-519-9713686; E-mail: cclee@uwindsor.ca


Abstract

This study examines how the formation and dissipation of a queue indicated by shock waves affect the likelihood of crash occurrence on freeways. Using one-minute average volume and density data collected from a section of the Gardiner Expressway in Toronto, changes in volume and density 3-10 minutes prior to the time of crash occurrence were observed. Types of shock wave and the shock wave speeds were estimated and related to the frequencies of the crashes where the shock wave existed before they occurred. It was found that typical shock wave types vary in different time periods of day due to different traffic conditions. The comparison with the volume-density data for the non-crash cases using logistic regression models shows that crashes are more likely to occur when the forward shock wave speed is lower. This indicates that slower vehicle progression in near-capacity conditions and slower dissipation of a queue in congested conditions are more likely to cause crashes. The results provide insights into better understanding of how shock waves affect the crash likelihood.

Keywords: Crash, freeway, shock, wave, real-time, logistic regression.