Crash analysis of mountainous freeways with high bridge and tunnel ratios using road scenario-based discretization.

Sun, Zongyuan; Liu, Shuo; Li, Dongxue; Tang, Boming; Fang, Shouen · 2020 · DOAJ

DOI: 10.1371/journal.pone.0237408

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Summary

This study addresses the safety challenges associated with mountainous freeways characterized by high bridge and tunnel ratios, a road type increasingly prevalent in China’s middle and western regions. Due to complex driving environments involving frequent cross-section switching, abrupt longitudinal changes, and alternating light conditions, the crash mechanisms on these roads remain poorly understood. The research aims to clarify how various road structures and their associated driving environments influence traffic safety by establishing a scenario-based discretization method to analyze crash patterns across different road sections. To achieve this, the authors developed a methodology that defines "traffic influence areas" for elementary structures (tunnels, bridges, interchanges, and service areas) and composite structures (groups of these elements). Influence distances were calculated based on driver visual adaptation needs, stopping sight distances, and traffic organization behaviors. For instance, tunnel exit influence distances ranged from 250 to 400 meters depending on tunnel length, while bridge influence was limited to stopping sight distances. Composite structures were defined when the distance between adjacent structures fell below a calculated safety-critical distance, indicating overlapping influence areas. The study applied this framework to a 254.12 km section of the Chongqing-Hunan freeway in China, which has a 61.85% bridge and tunnel ratio. Data comprised 1,739 police-recorded crashes from 2014 to 2016, which were matched to 324 discretized sub-sections. The results revealed distinct crash patterns across different road types. Crash rates were highest at interchanges and service areas (1.78 accidents per million vehicle-kilometers), approximately six times higher than in tunnels (0.30). Ordinary road sections exhibited higher crash rates (0.46) than most unique structural sections, with tunnels having the lowest rate. Among composite structures, bridge groups had the highest crash rate (0.40), while tunnel groups had the lowest (0.34). Regarding crash severity, bridges and bridge groups showed significantly higher severity than other sections, primarily due to single-vehicle crashes. In contrast, crashes in tunnels were mostly attributed to collisions with fixtures. The study also identified that annual average daily traffic and driving adaptability were related to crash occurrences. The significance of this research lies in its validation of a scenario-based discretization method for analyzing complex freeway environments. By demonstrating that crash risks and severities vary significantly by road structure type, the findings provide specific implications for road design and traffic management. The results suggest that safety measures should be tailored to specific sections, such as addressing single-vehicle crash risks on high bridges and managing collision risks with fixtures in tunnels, thereby enhancing the overall safety of mountainous freeways with high infrastructure density.

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Topics

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• incidence prevalence
• urban rural setting
• crash typology

Information type

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• Empirical Findings: crash risk outcomes