Assessment of Two-Vehicle and Multi-Vehicle Freeway Rear-End Crashes in China: Accommodating Spatiotemporal Shifts

Chenzhu Wang, Yangyang Xia, Fei Chen (), Jianchuan Cheng and Zeng’an Wang
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Chenzhu Wang: School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China
Yangyang Xia: School of Transportation, Tibet University, Lhasa 850001, China
Fei Chen: School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China
Jianchuan Cheng: School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China
Zeng’an Wang: Jiangsu Expressway Company Limited, Nanjing 210049, China

IJERPH, 2022, vol. 19, issue 16, 1-30

Abstract: Accounting for the growing numbers of injuries, fatalities, and property damage, rear-end crashes are an urgent and serious topic nowadays. The vehicle number involved in one crash significantly affected the injury severity outcomes of rear-end crashes. To examine the transferability and heterogeneity across crash types (two-vehicle versus multi-vehicle) and spatiotemporal stability of determinants affecting the injury severity of freeway rear-end crashes, this study modeled the data of crashes on the Beijing-Shanghai Freeway and Changchun-Shenzhen Freeway across 2014–2019. Accommodating the heterogeneity in the means and variances, the random parameters logit model was proposed to estimate three potential crash injury severity outcomes (no injury, minor injury, and severe injury) and identify the determinants in terms of the driver, vehicle, roadway, environment, temporal, spatial, traffic, and crash characteristics. The likelihood ratio tests revealed that the effects of factors differed significantly depending on crash type, time, and freeway. Significant variations were observed in the marginal effects of determinants between two-vehicle and multi-vehicle freeway rear-end crashes. Then, spatiotemporal instability was reported in several determinants, including trucks early morning. In addition, the heterogeneity in means and variances of the random parameters revealing the interactions of random parameters and other insignificant variables suggested the higher risk of determinants including speeding indicators, early morning, evening time, and rainy weather conditions. The current finding accounting for spatiotemporal instability could help freeway designers, decision-makers, management strategies to understand the contributing mechanisms of the factors to develop effective management strategies and measurements.

Keywords: injury severity; spatiotemporal stability; freeway rear-end crashes; random parameters logit model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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