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Statistical Analysis of Traffic Crashes on Mountainous Freeway Tunnel Sections

Author(s): ORCID
ORCID

ORCID

Medium: journal article
Language(s): English
Published in: Transportation Research Record: Journal of the Transportation Research Board, , n. 2, v. 2678
Page(s): 1-10
DOI: 10.1177/03611981231172751
Abstract:

Tunnels on mountainous freeways are affected by abrupt changes in brightness, complex geometric alignments, heavy traffic flow, bad weather, and other factors, some of which contribute toward tunnels having more traffic crashes than other sections of the freeway. Previous research, however, has given limited attention to tunnel length and heterogeneity in the parts of the tunnels, such as at the tunnels’ entrance and exit zones. Focusing on 36 tunnels on the Guidu Freeway in China’s Guizhou Province, this study collects data on crashes and their influencing factors over 2 years (2020–2021), constructs a negative binomial panel data random effects model, and analyzes single-vehicle crashes, multi-vehicle crashes, and total crashes. The results show that: 1) multi-vehicle crashes occur throughout the tunnel sections, 2) crashes are more likely to occur in long tunnel sections, 3) the crash frequency from the tunnel entrance zone to the mid zone is higher than in other areas of the tunnel, 4) the crash frequency is higher for circular curve/easy curve tunnel sections than for straight tunnel sections, 5) the crash frequency is higher for downhill and concave curve sections than for flat sections, 6) the crash frequency increases with heavy traffic flow and adverse weather conditions, and 7) the crash frequency increases as road surface skidding resistance and ride quality decrease. These findings can provide theoretical support for engineering improvement and the formulation and revision of specifications for designing freeway tunnel sections, especially in mountainous areas.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/03611981231172751.
  • About this
    data sheet
  • Reference-ID
    10777841
  • Published on:
    12/05/2024
  • Last updated on:
    12/05/2024
 
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