CONTACT US: Contact info
|
Citation |
Pervez A, Huang H, Lee J, Han C, Li Y, Zhai X. J. Transp. Eng. A: Systems 2022; 148(4): e04022006. |
|
Copyright |
(Copyright © 2022, American Society of Civil Engineers) |
|
DOI |
|
PMID |
unavailable |
|
Abstract |
On mountainous freeways, some tunnels are located adjacent to each other, composing a tunnel group where the safety conditions are more challenging compared to a single tunnel. However, most of the existing studies have focused on single tunnel safety, and the research efforts to investigate traffic safety, especially the injury-severity analysis of the tunnel group crashes, is scarce. Therefore, the present study employed a random parameter logit model to examine the factors affecting the injury severity of the freeway tunnel group crashes. The analysis is based on a five-year of police-reported data set of 377 crashes collected from six tunnel groups in Hunan Province, China. The results indicate that the daytime, weekdays, entrance zone, downgrades, elder drivers, speeding, fatigue driving, and rollover collisions are positively associated, while winter, curves, and sideswipes are negatively associated with severe crashes and have signs consistent with engineering intuition. More importantly, due to the complex driving environment of the tunnel groups, the summer, access zone, connecting zone, and drivers with less driving experience increases the probability of severe crashes. Also, the effects of the access zone, elderly drivers, speeding, and sideswipe collisions were found to be best modeled with random parameters in this study. Multiple countermeasures are provided to improve tunnel groups traffic safety, including the provision of variable message signs to provide information to the drivers regarding the speeding limits and distance to the tunnel, periodic maintenance of the illumination according to the lighting guidelines in the tunnel groups, implementation of the automatic section speed control for speeding, and public awareness about the complex driving environment of the tunnel groups. Language: en |
|
Keywords |
Crash severity; Random parameter model; Traffic safety; Tunnel group |