TY - GEN
T1 - The Effect of Weather Temporal Instability on the Injury Severity in Single-Vehicle Crashes
T2 - 23rd COTA International Conference of Transportation Professionals: Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation, CICTP 2023
AU - Wang, Jingyi
AU - Tan, Huachun
AU - Ding, Fan
AU - Wen, Zoutao
N1 - Publisher Copyright:
© ASCE.
PY - 2023
Y1 - 2023
N2 - Nowadays, most current studies on weather factors are qualitative analyses and do not consider temporal instability in prediction models. To this end, with road traffic crash data from 2015 to 2017 in Hong Kong and real-time weather data of 1-min accuracy, this study explores the temporal instability of the weather impact on the injury severity of single-vehicle crashes. To use Stata software for the contributing factors selection and multicollinearity test, we matched the Hong Kong crash data with the high-precision weather data from the Hong Kong Observatory. Then, we used NLOGIT to establish fixed parameter logit models, mixed logit models, and mixed logit models with mean heterogeneity, respectively. The results show that the model parameters affecting the injury severity of single-vehicle crashes have significant temporal instability. The injury severity of single-vehicle crashes increases in fall when the humidity is over 80% or the air temperature is between 20℃ and 25℃, as the opposite of the winter.
AB - Nowadays, most current studies on weather factors are qualitative analyses and do not consider temporal instability in prediction models. To this end, with road traffic crash data from 2015 to 2017 in Hong Kong and real-time weather data of 1-min accuracy, this study explores the temporal instability of the weather impact on the injury severity of single-vehicle crashes. To use Stata software for the contributing factors selection and multicollinearity test, we matched the Hong Kong crash data with the high-precision weather data from the Hong Kong Observatory. Then, we used NLOGIT to establish fixed parameter logit models, mixed logit models, and mixed logit models with mean heterogeneity, respectively. The results show that the model parameters affecting the injury severity of single-vehicle crashes have significant temporal instability. The injury severity of single-vehicle crashes increases in fall when the humidity is over 80% or the air temperature is between 20℃ and 25℃, as the opposite of the winter.
UR - http://www.scopus.com/inward/record.url?scp=85174025126&partnerID=8YFLogxK
U2 - 10.1061/9780784484869.151
DO - 10.1061/9780784484869.151
M3 - Conference contribution
AN - SCOPUS:85174025126
T3 - CICTP 2023: Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation - Proceedings of the 23rd COTA International Conference of Transportation Professionals
SP - 1579
EP - 1591
BT - CICTP 2023
A2 - Chen, Yanyan
A2 - Ma, Jianming
A2 - Zhang, Guohui
A2 - Wang, Haizhong
A2 - Sun, Lijun
A2 - He, Zhengbing
PB - American Society of Civil Engineers (ASCE)
Y2 - 14 July 2023 through 17 July 2023
ER -