Unknown

Dataset Information

0

Investigation of injury severity in urban expressway crashes: A case study from Beijing.


ABSTRACT: Urban expressway is the main artery of traffic network, and an in-depth analysis of the crashes is crucial for improving the traffic safety level of expressways. This study intended to address the injury severity of expressways in Beijing by proposing Bayesian ordered logistic regression model. Crash data were collected from urban express rings and expressways in 2015 and 2016. The results showed that crash location, time and crash season are significant variables influencing injury severity. The findings revealed that the proposed model can address the ordinal feature of injury severity, while accommodating the data with small sample sizes that may not adequately represent population characteristics. The conclusions can provide the management departments with valuable suggestions for the injury prevention and safety improvement on the urban expressways.

SUBMITTER: Yuan Q 

PROVIDER: S-EPMC6957292 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

altmetric image

Publications

Investigation of injury severity in urban expressway crashes: A case study from Beijing.

Yuan Quan Q   Xu Xuecai X   Zhao Junwei J   Zeng Qiang Q  

PloS one 20200113 1


Urban expressway is the main artery of traffic network, and an in-depth analysis of the crashes is crucial for improving the traffic safety level of expressways. This study intended to address the injury severity of expressways in Beijing by proposing Bayesian ordered logistic regression model. Crash data were collected from urban express rings and expressways in 2015 and 2016. The results showed that crash location, time and crash season are significant variables influencing injury severity. Th  ...[more]

Similar Datasets

| S-EPMC7156062 | biostudies-literature
| S-EPMC7289378 | biostudies-literature
| S-EPMC8005247 | biostudies-literature
| S-EPMC4340813 | biostudies-literature
| S-EPMC4816857 | biostudies-literature
| S-EPMC5839015 | biostudies-literature
| S-EPMC7864427 | biostudies-literature
| S-EPMC5033524 | biostudies-literature
| S-EPMC9912102 | biostudies-literature
| S-EPMC8673618 | biostudies-literature