Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China

Purpose: Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type inv...

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Main Authors: Quan Yuan, Meng Lu, Athanasios Theofilatos, Yi-Bing Li
Format: Article
Language:English
Published: Elsevier 2017-02-01
Series:Chinese Journal of Traumatology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1008127516301833
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spelling doaj-2a107e7dc6594121b379cdbd69ad12ea2020-11-24T21:35:38ZengElsevierChinese Journal of Traumatology1008-12752017-02-01201202610.1016/j.cjtee.2016.10.002Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, ChinaQuan Yuan0Meng Lu1Athanasios Theofilatos2Yi-Bing Li3State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, ChinaNational Technical University of Athens, Athens, GreeceState Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, ChinaPurpose: Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle (FV). Methods: This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. Moreover, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. Results: The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers' age, weight difference between vehicles, visibility condition and lane number of road significantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. Conclusion: All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers' age and drivers' original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beijing on weekdays.http://www.sciencedirect.com/science/article/pii/S1008127516301833Rear-end crashTrucksContributing factorsInjury severity
collection DOAJ
language English
format Article
sources DOAJ
author Quan Yuan
Meng Lu
Athanasios Theofilatos
Yi-Bing Li
spellingShingle Quan Yuan
Meng Lu
Athanasios Theofilatos
Yi-Bing Li
Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China
Chinese Journal of Traumatology
Rear-end crash
Trucks
Contributing factors
Injury severity
author_facet Quan Yuan
Meng Lu
Athanasios Theofilatos
Yi-Bing Li
author_sort Quan Yuan
title Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China
title_short Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China
title_full Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China
title_fullStr Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China
title_full_unstemmed Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China
title_sort investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in beijing area, china
publisher Elsevier
series Chinese Journal of Traumatology
issn 1008-1275
publishDate 2017-02-01
description Purpose: Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle (FV). Methods: This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. Moreover, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. Results: The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers' age, weight difference between vehicles, visibility condition and lane number of road significantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. Conclusion: All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers' age and drivers' original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beijing on weekdays.
topic Rear-end crash
Trucks
Contributing factors
Injury severity
url http://www.sciencedirect.com/science/article/pii/S1008127516301833
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