Characterizing the differences of injury severity between single-vehicle and multi-vehicle crashes in China. Issue 3 (4th March 2023)

• Record Type: Journal Article
• Authors: Ma, Jingfeng; Ren, Gang; Li, Haojie; Wang, Shunchao; Yu, Jingcai
• Is Part Of: Journal of transportation safety & security. Volume 15:Issue 3(2023)
• Page Start: 314
• Page End: 334
• Publication Date: 2023-03-04
• Subjects: crash injury severity -- single-vehicle crashes -- multi-vehicle crashes -- risk factors -- model comparison -- partial proportional odds model; Transportation -- United States -- Safety measures -- Periodicals; Transportation -- Security measures -- United States -- Periodicals; Transportation -- Safety measures; Transportation -- Security measures; United States; Periodicals; 353.9805
• DOI: 10.1080/19439962.2022.2056931
• Languages: English
• ISSNs: 1943-9970

Abstract

Abstract: It is of paramount importance for mitigating road crash losses to characterize the relationship between crash injury severities and contributing factors. Existing studies have revealed mechanism differences of single-vehicle (SV) and multi-vehicle (MV) crashes. This study positions itself at exploring the differences from spatiotemporal, road-environment, driver-vehicle, and collision characteristics. A model comparison as well as the elasticities for the optimal model (partial proportional odds model) is implemented based on 18, 083 SV crashes and 22, 162 MV crashes in China. The results evidenced the great differences that time, road, speed, lighting, and weather are found to have a positive correlation with only SV crash injury severity, yet negatively related with only MV crash injury severity. Area, location, and angle are significant only for SV crashes, while day, interference, and wind are significant only for MV crashes. The findings revealed that gender, age, collision, location, and time are more influencing factors in SV crashes, while collision, age, gender, vehicle, and wind have more contributions to MV crashes. The findings could provide an insightful reference for prioritizing effective countermeasures to mitigate traffic crash losses.