Citation

Kar P, Venthuruthiyil SP, Chunchu M. Accid. Anal. Prev. 2024; 199: e107521.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.aap.2024.107521

PMID

38428243

Abstract

Heavy commercial vehicles (HCVs) face elevated crash risks in mountainous terrains due to the challenging topography and intricate geometry, posing a significant challenge for transportation agencies in mitigating these risks. While safety studies in such terrains traditionally rely on historical crash data, the inherent issues associated with crash data have led to a shift towards proactive safety studies using surrogate safety measures (SSM) in recent years. However, the scarcity of accurate microscopic data related to HCV drivers has limited the application of proactive safety studies in mountainous terrains. This study addresses this gap by employing an SSM known as anticipated collision time (ACT) to explore the impact of horizontal curves on the crash risk of HCVs in mountainous terrain. To perform the crash risk analysis, a collection of videos was gathered from horizontal curves in the mountainous terrain along the Guwahati-Shillong bypass in the Northeastern region of India. Subsequently, trajectories were extracted from these videos using semi-automated image processing software. Traffic conflicts were identified using ACT, and the crash risk was estimated through the Peak-Over Threshold (POT) approach of the Extreme Value Theory (EVT). The findings indicate that Run-Off-Road (ROR) traffic events happen more frequently on or near the horizontal curves falling in mountainous terrain. However, the frequency of severe ROR traffic events is lower, indicating the lower propensity for such collisions on the selected curves. The threshold for the safety margin of ROR traffic events involving HCVs was 2 s. The study revealed that stationary models exhibit an overestimation of crash frequency (0, 6) compared to the observed crash frequency (0, 2). Consequently, non-stationary crash risk models were developed, incorporating road geometry and the braking and yaw rates of HCVs as covariates. The results demonstrate that the estimated confidence bounds (1, 2) align with the observed crash frequency (0, 2), emphasizing the applicability of POT models for safety analysis in mountainous terrains in India. The study identified curve radius, length of the approach tangent, and the distance between the center points of horizontal and vertical curves as influential factors affecting the Run-Off-Road (ROR) crash risk of HCVs. Notably, sharp curves with radii less than 200 m or more are associated with a significantly higher crash risk. Additionally, an increased distance between the midpoints of horizontal and vertical curves beyond 1 m was found to escalate the ROR crash risk of HCVs. To mitigate these risks, it is recommended to reduce the length of the approach tangent to prevent high-speed travel on sharp curves. Furthermore, proper signage should be strategically placed to warn drivers and avert potential hazards.

Language: en

Keywords

Crash risk; Extreme value theory; Horizontal curves; Mountainous terrain; Run-off road; Surrogate safety measure