Literature DB >> 10440555

Analysis of injury severity and vehicle occupancy in truck- and non-truck-involved accidents.

L Y Chang1, F Mannering.   

Abstract

The impact that large trucks have on accident severity has long been a concern in the accident analysis literature. One important measure of accident severity is the most severely injured occupant in the vehicle. Such data are routinely collected in state accident data files in the U.S. Among the many risk factors that determine the most severe level of injury sustained by vehicle occupants, the number of occupants in the vehicle is an important factor. These effects can be significant because vehicles with higher occupancies have an increased likelihood of having someone seriously injured. This paper studies the occupancy/injury severity relationship using Washington State accident data. The effects of large trucks, which are shown to have a significant impact on the most severely injured vehicle occupant, are accounted for by separately estimating nested logit models for truck-involved accidents and for non-truck-involved accidents. The estimation results uncover important relationships between various risk factors and occupant injury. In addition, by comparing the accident characteristics between truck-involved accidents and non-truck-involved accidents, the risk factors unique to large trucks are identified along with the relative importance of such factors. The findings of this study demonstrate that nested logit modeling, which is able to take into account vehicle occupancy effects and identify a broad range of factors that influence occupant injury, is a promising methodological approach.

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Mesh:

Year:  1999        PMID: 10440555     DOI: 10.1016/s0001-4575(99)00014-7

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  7 in total

1.  Analysis of Factors Contributing to the Injury Severity of Overloaded-Truck-Related Crashes on Mountainous Highways in China.

Authors:  Huiying Wen; Yingxin Du; Zheng Chen; Sheng Zhao
Journal:  Int J Environ Res Public Health       Date:  2022-04-02       Impact factor: 3.390

2.  Investigation of Key Factors for Accident Severity at Railroad Grade Crossings by Using a Logit Model.

Authors:  Shou-Ren Hu; Chin-Shang Li; Chi-Kang Lee
Journal:  Saf Sci       Date:  2010-02-01       Impact factor: 4.877

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

Authors:  Quan Yuan; Meng Lu; Athanasios Theofilatos; Yi-Bing Li
Journal:  Chin J Traumatol       Date:  2016-11-09

4.  A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions.

Authors:  Xiaojun Shao; Xiaoxiang Ma; Feng Chen; Mingtao Song; Xiaodong Pan; Kesi You
Journal:  Int J Environ Res Public Health       Date:  2020-01-07       Impact factor: 3.390

5.  Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network.

Authors:  Arshad Jamal; Waleed Umer
Journal:  Int J Environ Res Public Health       Date:  2020-10-14       Impact factor: 3.390

6.  Geographical Detection of Traffic Accidents Spatial Stratified Heterogeneity and Influence Factors.

Authors:  Yuhuan Zhang; Huapu Lu; Wencong Qu
Journal:  Int J Environ Res Public Health       Date:  2020-01-16       Impact factor: 3.390

7.  Injury Severity and Contributing Driver Actions in Passenger Vehicle-Truck Collisions.

Authors:  Jingjing Xu; Behram Wali; Xiaobing Li; Jiaqi Yang
Journal:  Int J Environ Res Public Health       Date:  2019-09-22       Impact factor: 3.390

  7 in total

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