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An evacuation model based on co-evolutionary multi-particle swarms optimization for pedestrian–vehicle mixed traffic flow

机译:基于共进多粒子群优化的行人载体混合交通流量的疏散模型

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In a large common place, a huge number of pedestrians may flood into the surrounding region and mix with the vehicles which originally existed on the roads when emergent events occur. The mutual restriction between pedestrians and vehicles as well as the mutual effect between evacuation individuals and the environment which evacuees are situated in, will have an important impact on evacuation effects. This paper presents a pedestrian–vehicle mixed evacuation model to produce optimal evacuation plans considering both evacuation time and density degree. A co-evolutionary multi-particle swarms optimization approach is proposed to simulate the evacuation process of pedestrians and vehicles separately and the interaction between these two kinds of traffic modes. The proposed model and algorithm are effective for mixed evacuation problems. An illustrating example of a study region around a large stadium has been presented. The experimental results indicate the effective performances for evacuation problems which involve complex environments and various types of traffic modes.
机译:在一个大的公共场所,大量的行人可能会涌入周围地区,并在出现紧急事件时与原本存在于道路上的车辆混合。行人和车辆之间的相互限制以及疏散人员与撤离的环境之间的相互影响,将对疏散效应产生重要影响。本文提出了一种行人 - 车辆混合抽空模型,以产生考虑到疏散时间和密度度的最佳疏散计划。建议分别模拟行人和车辆的疏散过程以及这两种交通模式的互动。所提出的模型和算法对于混合疏散问题是有效的。已经介绍了大体育场周围的研究区域的示例。实验结果表明了疏散问题的有效性能,包括复杂的环境和各种类型的交通模式。

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