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Abstract
Tunnels are an engineering solution that has gained prominence for constructing freeways in mountainous regions. The length of the tunnels can vary, depending on the geological conditions, engineering requirements, and budget constraints. Car-following is the predominant driving behavior observed in tunnels, and understanding how drivers follow each other in different types of tunnels is crucial for ensuring smooth traffic flow and safety. Each type of tunnel environment can uniquely impact car-following behavior, which allows for targeted studies to optimize traffic management. In this research, natural driving data in freeway tunnels were collected through a driving experiment conducted on the Baomao Freeway in Chongqing, China. Then, the correlations and differences in car-following data between various tunnels and sections were analyzed. Finally, car-following models were developed considering various tunnel scenarios, and the influence of tunnel types on traffic flow was analyzed by simulation. The study revealed notable variations in car-following behavior across different types of tunnels, as well as within consecutive sections of the same tunnel. As tunnel length increased, the driving stability of following vehicles decreased, but the level of driving safety risk was not positively correlated with tunnel length. Significant vehicle trajectory oscillation was observed within the inner sections of long and extra-long tunnels, and a significant relationship between the acceleration of following vehicles and the location within the tunnel section was found. Additionally, the longer the tunnel, the greater the fluctuations in traffic flow, and the negative impact of the tunnel environment on traffic flow stability increased periodically downstream. These findings offer valuable insights for understanding and modeling car-following behavior in freeway tunnels, which ultimately facilitate traffic safety and mobility.
Published Version
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