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A Comprehensive Analysis of Multi-Vehicle Crashes on Expressways: A Double Hurdle Approach

Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea
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Sustainability 2019, 11(10), 2782; https://doi.org/10.3390/su11102782
Received: 4 March 2019 / Revised: 9 April 2019 / Accepted: 7 May 2019 / Published: 15 May 2019
(This article belongs to the Section Sustainable Transportation)
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Abstract

To maintain safe expressways, it is necessary to investigate the causes of severe traffic accidents and establish a strategy. This study aims to analyze crashes and identify the influence of crash-risk factors on multi-vehicle (MV) crashes. Crashes involving three types of vehicles namely passenger cars, buses, and freight trucks were analyzed using a seven-year data spanning 2011 to 2017 which consists of crashes that occurred on expressways in South Korea. We applied a double hurdle approach in which a model consists of two estimators: The first estimation, which is a binary logit model selects MV crashes from the dataset; and the second estimation which is a truncated regression model estimates the number of vehicles involved in the MV crash. We found that driver traffic violations such as the improper distance between vehicles, reversing and passing increases the probability of MV crashes occurring. MV crashes in tunnels and mainlines were found to be positively correlated with the number of vehicles involved in the crash, whereas fewer vehicles were involved in MV crashes at ramps and toll-booths. Further, we found that the hurdle model with an exponential form of conditional mean of the latent variable provides better estimation parameters. View Full-Text
Keywords: multi-vehicle crashes; double hurdle; risk factor; exponential double hurdle; expressway multi-vehicle crashes; double hurdle; risk factor; exponential double hurdle; expressway
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Hong, J.; Tamakloe, R.; Park, D. A Comprehensive Analysis of Multi-Vehicle Crashes on Expressways: A Double Hurdle Approach. Sustainability 2019, 11, 2782.

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