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A Crash Surrogate Metric considering Traffic Flow Dynamics in a Motorway Corridor

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Indexed by:期刊论文

Date of Publication:2018-01-01

Journal:JOURNAL OF ADVANCED TRANSPORTATION

Included Journals:SCIE、SSCI

Volume:2018

ISSN No.:0197-6729

Abstract:We proposed a new crash surrogate metric, i.e., the maximum disturbance that a car following scenario can accommodate, to represent potential crash risks with a simple closed form. The metric is developed in consideration of traffic flow dynamics. Then, we compared its performance in predicting the rear-end crash risks for motorway on-ramps with other two surrogate measures (time to collision and aggregated crash index). To this end, a one-lane on-ramp of Pacific Motorway, Australia, was selected for this case study. Due to the lack of crash data on the study site, historical crash counts were merged according to levels of service (LOS) and then converted into crash rates. In this study, we used the societal risk index to represent the crash surrogate indicators and built relationships with crash rates. The final results show that (1) the proposed metric and aggregated crash index are superior to the time to collision in predicting the rear-end crash risks for on-ramps; (2) they have a relatively similar performance, but due to the simple calculation, the proposed metric is more applicable to some real-world cases compared with the aggregated crash index.

Date of Publication:2018-01-01

Liu Kai

Gender:Male Alma Mater:Nagoya University Degree:Doctoral Degree School/Department:School of Economics and Management Business Address:Room D435, School of Economics and Management Contact Information:+86-411-84706221 E-Mail:liukai@dlut.edu.cn