Driving Characteristics of Drivers Avoiding Lateral Obstacles in Mountain Highway Tunnels: A Dynamic Lateral Safety Distance Prediction Model

Abstract

A natural driving real-vehicle test was conducted in nine tunnels in Chongqing, China. The driving trajectories and speeds of 40 drivers were recorded to better understand drivers’ driving characteristics under the mutual influence of various tunnel lengths and numerous lateral obstacles on mountainous highways. According to the driver’s need for lateral safety distance in different scenarios, the conditions and scope of the occurrence of the shy away effect are defined, and a dynamic avoidance prediction model is established in multiple scenarios. It was demonstrated that, when there were no lateral dynamic obstacles, drivers were influenced by the tunnel sidewalls to drift away from them. However, when lateral dynamic obstacles were present, drivers’ driving trajectories were corrected to be closer to the inside of the lane. The influence of vehicles of the same type resulted in the trajectory offset to the left by 0.2 m (extra-long tunnel), 0.7 m (long tunnel), 0.5 m (medium tunnel), and 0.7 m (short tunnel) compared with the driving trajectory without the influence of the obstacle. The influence of trucks causes the trajectory offset to the left compared with the driving trajectory without obstacles by 0.2 m (extra-long tunnel), 0.5 m (long tunnel), 1 m (medium tunnel), and 1.75 m (short tunnel). There is some variation in the degree of risk to the driver from different obstacles under different tunnels. The lateral distance between the driver and the dynamic obstacle is related to the nature of the available driving distance ahead. A sufficiently long driving maneuver distance enables the subject vehicle to gradually overtake the lateral dynamic obstacle in a more stable state. Dynamic avoidance models with fitting accuracies of 0.6–0.99 were implemented to predict vehicle trajectories in different tunnels and under the influence of various lateral dynamic obstacles. The study of the correlation of vehicle trajectories under the influence of various factors in tunnels is completed by the research findings, which can serve as a foundation for the design of driving behavior regulation, an improvement in traffic safety facilities, traffic management, and monitoring of lateral safety distances of intelligent vehicles in tunnels.