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Genetic algorithm based signal optimizer for oversaturated urban signalized intersection

机译:基于遗传算法的过饱和城市信号交叉口信号优化器

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Relieving traffic congestion is an urgent call for traffic engineering. Although various adaptive control strategies have been reported in literature to reduce the travel delay, most of them are not tested under oversaturated condition, where the traffic demand is higher than the road capacity. Therefore, this work proposes genetic algorithm (GA) to optimize the traffic signals for reducing the average delay at the at-grade crossed intersection under oversaturated condition. A comprehensive traffic model has been developed as the testbed. The average delay experienced by every vehicle to traverse the intersection is taken as performance metric to evaluate the performances of the formulated GA. The simulation results show the formulated GA is able to optimize the traffic signals and minimize the average delay of the intersection to 55.2 sec or equivalent to level-of-service (LOS) D.
机译:缓解交通拥堵是对交通工程的紧急呼叫。虽然在文献中报告了各种自适应控制策略以降低旅行延迟,但大多数在过饱和条件下都没有测试,交通需求高于道路容量。因此,这项工作提出了遗传算法(GA),以优化在过饱和条件下降低AT级交叉口处的平均延迟的业务信号。综合交通模型已成为测试平台。每个车辆遍历交叉点的平均延迟被视为性能指标,以评估配制的GA的性能。仿真结果表明,配制的GA能够优化交通信号,并最大限度地减少交叉点的平均延迟至55.2秒或等同于服务水平(LOS)D.

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