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Characterizing the differences of injury severity between single-vehicle and multi-vehicle crashes in China
被引:9
|作者:
Ma, Jingfeng
Ren, Gang
[1
,2
]
Li, Haojie
Wang, Shunchao
Yu, Jingcai
机构:
[1] Southeast Univ, Sch Transportat, Jiangsu Key Lab Urban ITS, Rd 2, Nanjing 211189, Peoples R China
[2] Southeast Univ, Sch Transportat, Jiangsu Prov Collaborat Innovat Ctr Modern Urban, Rd 2, Nanjing 211189, Peoples R China
关键词:
crash injury severity;
single-vehicle crashes;
multi-vehicle crashes;
risk factors;
model comparison;
partial proportional odds model;
ORDERED LOGIT MODEL;
RURAL-AREAS;
URBAN;
HIGHWAYS;
IMPACT;
MOTORCYCLISTS;
HETEROGENEITY;
DRIVERS;
SAFETY;
TIME;
D O I:
10.1080/19439962.2022.2056931
中图分类号:
U [交通运输];
学科分类号:
08 ;
0823 ;
摘要:
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.
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页码:314 / 334
页数:21
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