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Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion

机译:下一路改道:缓解意外城市交通拥堵的多智能体系统

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摘要

During peak hours in urban areas, unpredictable traffic congestion caused by en route events (e.g., vehicle crashes) increases drivers' travel time and, more seriously, decreases their travel time reliability. In this paper, an original and highly practical vehicle rerouting system, which is called Next Road Rerouting (NRR), is proposed to aid drivers in making the most appropriate next road choice to avoid unexpected congestions. In particular, this heuristic rerouting decision is made upon a cost function that takes into account the driver's destination and local traffic conditions. In addition, the newly designed multiagent system architecture of NRR allows the positive rerouting impacts on local traffic to be disseminated to a larger area through the natural traffic flow propagation within connected local areas. The simulation results based on both synthetic and realistic urban scenarios demonstrate that, compared with the existing solutions, NRR can achieve a lower average travel time while guaranteeing a higher travel time reliability in the face of unexpected congestion. The impacts of NRR on the travel time of both rerouted and nonrerouted vehicles are also assessed, and the corresponding results reveal its higher practicability.
机译:在城市的高峰时段,由途中事件(例如,交通事故)引起的不可预测的交通拥堵增加了驾驶员的出行时间,更严重的是,降低了他们的出行时间可靠性。在本文中,提出了一种原始且高度实用的车辆改道系统,称为“下一路改道(NRR)”,以帮助驾驶员做出最合适的下一路选择,以避免意外的拥堵。尤其是,此启发式重新路由决定是基于考虑驾驶员的目的地和当地交通状况的成本函数做出的。此外,新设计的NRR多代理系统架构允许通过连接区域内自然流量的传播将对本地流量的积极路由影响传播到更大的区域。基于综合和现实城市情景的仿真结果表明,与现有解决方案相比,NRR可以实现更低的平均行驶时间,同时在遇到意外拥堵的情况下保证更高的行驶时间可靠性。还评估了NRR对改行和未改行车辆行驶时间的影响,相应的结果显示了其较高的实用性。

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