Citation

Lee J, Chae J, Yoon T, Yang H. Accid. Anal. Prev. 2018; 112: 1-10.

Affiliation

WISE Institute, 11F Centennial Complex, Hankuk University of Foreign Studies, 81 oedae-ro, Mohyeon-myeon, Cheoin-gu Gyeonggi-do, 17035, Republic of Korea. Electronic address: hobakzzz@hufs.ac.kr.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.aap.2017.12.013

PMID

29306084

Abstract

Weather conditions are strongly correlated with traffic accident severity. In particular, rain-related factors are an important cause of traffic accidents due to the poor visibility and reduced friction resulting from slippery road conditions. This paper presents a systematic approach to analyze the extent to which the rainfall intensity and level of water depth are responsible for traffic accidents using Seoul City, Korea, as a case study. The rainfall and traffic accident data over a nine-year period (from 2007 to 2015) for Seoul were analyzed through Structural Equation Modeling to identify the relationships among variables by handling endogenous and exogenous variables simultaneously. In the model, four latent variables, namely those representing the road; traffic, environmental, and human factors; and rain and water depth factors, were defined and the coefficients of the latent, endogenous, and exogenous variables were estimated to obtain the level of accident severity. Furthermore, a statistical goodness of fit index was suggested for model fitting. In conclusion, traffic, environmental, and human factors; rain and water depth factors; and road factors are mutually correlated with the level of accident severity. Compact cars, young drivers, female drivers, heavy rain, deep water, and roads with a long drainage length are more likely to be associated with an increase in the level of accident severity, as are features like a tangent, down slope, right-hand curve, and shorter curve length.

Copyright © 2017 Elsevier Ltd. All rights reserved.

Language: en

Keywords

Level of accident severity; Rainfall intensity; Road factor; Structural Equation Modeling; Water depth