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<p>In this paper, we have developed a dynamical simulation model that combines micro- and macro-traffic flows and is calibrated using empirical data collected in a tunnel environment. Leveraging this model, a macro-level control strategy for tunnel traffic signals is formulated to optimize the flow and routing of vehicular traffic. The traffic flow and lane speed distributions under accident and congestion scenarios are simulated using the Simulation of Urban MObility (SUMO) software. Simulation results show that strict traffic restrictions during accidents lead to a large waste of road resources, on the contrary, the implementation of speed limiting strategies can significantly reduce traffic congestion and effectively shorten queue length and congestion duration.</p>

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Road and Speed Restriction Strategies for Alleviating Tunnel Congestion Based on SUMO Traffic Simulation

  • 期刊论文

  • 发表日期：

    2025年6月11日

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  • Xinyuan Wang,
  • Honglin Mu,
  • Yunsong Fan,
  • Jing Huang,
  • Dengmin Xiao,
  • Yonghua Zhang

摘要

In this paper, we have developed a dynamical simulation model that combines micro- and macro-traffic flows and is calibrated using empirical data collected in a tunnel environment. Leveraging this model, a macro-level control strategy for tunnel traffic signals is formulated to optimize the flow and routing of vehicular traffic. The traffic flow and lane speed distributions under accident and congestion scenarios are simulated using the Simulation of Urban MObility (SUMO) software. Simulation results show that strict traffic restrictions during accidents lead to a large waste of road resources, on the contrary, the implementation of speed limiting strategies can significantly reduce traffic congestion and effectively shorten queue length and congestion duration.