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

Xinlu Zong, Chunzhi Wang () and Hongwei Chen ()
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Xinlu Zong: School of Computer Science and Technology, Hubei University of Technology, Wuhan 430068, P. R. China
Chunzhi Wang: School of Computer Science and Technology, Hubei University of Technology, Wuhan 430068, P. R. China
Hongwei Chen: School of Computer Science and Technology, Hubei University of Technology, Wuhan 430068, P. R. China

International Journal of Modern Physics C (IJMPC), 2017, vol. 28, issue 12, 1-17

Abstract: 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.

Keywords: Mixed evacuation; pedestrian; particle swarm optimization algorithm; co-evolution; pheromone (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1142/S012918311750142X

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