Technical Papers
Jan 28, 2022

Factors Affecting Injury Severity of Crashes in Freeway Tunnel Groups: A Random Parameter Approach

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 4

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.

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Data Availability Statement

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This study was funded by: (1) National Key R&D Program of China (2020YFB1600400); (2) the Joint Research Scheme of National Natural Science Foundation of China/Research Grants Council of Hong Kong (Project Nos. 71561167001 and N_HKU707/15); (3) the Natural National Science Foundation of China (Nos. 713711921 and 71901223); (4) Innovation-Driven Project of Central South University (2020CX013); and (5) the Foundation of Central South University (No. 50204501).

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 148Issue 4April 2022

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Received: Nov 19, 2020
Accepted: Aug 31, 2021
Published online: Jan 28, 2022
Published in print: Apr 1, 2022
Discussion open until: Jun 28, 2022

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Ph.D. Student, School of Traffic and Transportation Engineering, Central South Univ., Changsha 410075, Hunan, China. ORCID: https://orcid.org/0000-0001-6283-2871. Email: [email protected]
Helai Huang, Ph.D. [email protected]
Professor, School of Traffic and Transportation Engineering, Central South Univ., Changsha 410075, Hunan, China. Email: [email protected]
Jaeyoung Lee, Ph.D., M.ASCE [email protected]
Professor, Member of the ASCE Transportation Safety Committee School of Traffic and Transportation Engineering, Central South Univ., Changsha 410075, Hunan, China (corresponding author). Email: [email protected]
Chunyang Han, Ph.D. [email protected]
Postdoctoral Researcher, Dept. of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua Univ., Beijing 100084, China. Email: [email protected]
Ye Li, Ph.D. [email protected]
Assistant Professor, School of Traffic and Transportation Engineering, Central South Univ., Changsha 410075, Hunan, China. Email: [email protected]
Xiaoqi Zhai, Ph.D. [email protected]
Ph.D. Student, School of Traffic and Transportation Engineering, Central South Univ., Changsha 410075, Hunan, China. Email: [email protected]

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