Several Problems Of Urball Rail Transit Hub Emergency Evacuation Based On ACP Approach

Recently, with the advantages of safety and high efficiency, convenience and reliability, low energy consumption and light environmental pollution, urban rail transit has become one of the important means for urban public transport. With the growth of the urban population in China, traffic demand has gradually increased and urban rail transit has been rapidly developed. Due to large passenger flow, complex structure and unreasonable emergency strategies, rail transit hub stations which are important nodes of urban rail transit network are easy to form safety hazards. And fire and other emergency incidents at hub stations can cause huge casualties and property losses. In recent years, emergency evacuation of urban rail transit hub has drawn more and more attention of scholars and research institutions at home and abroad.As an important research tool for complex system, Parallel control method which is referred as ACP approach includes the following three steps:artificial system, computational experiments and parallel execution. Through the establishment of artificial system and interact in parallel with the actual system, the control and management of complex systems can be realized by ACP approach. Several issues of emergency evacuation for urban rail transit hub are discussed in this paper based on ACP approach. The main work is as follows:Firstly, the behavioral characteristics of passengers at waiting area and bottleneck area of the station platform are researched based on ACP approach. The waiting area selection behavior of passengers is studied. Passengers’distribution model at waiting area and the artificial system of some urban rail transit hub are established. Computational experiments are conducted to analyze the effect of inbound traffic rate and dynamic signs; Bottleneck "zipper effect" model is built and the maximum capacity of the typical bottleneck areas are calculated. Then emergency evacuation capability of station platform is analyzed and computational experiments are done to verify the feasibility of the "zipper effect" model.Secondly, based on adaptive ant colony algorithm, the artificial emergency evacuation strategies for passengers at urban rail transit hub platform are studied. Adaptive ant colony evacuation model is built and it is applied to the artificial system of urban rail transit hub to dynamically adjust the impact weight of evacuation guide; According to the behavioral characteristics of evacuees at the platform, three evacuation strategies are developed which are adaptive ant colony algorithm, proximity principle and the combination of the proximity principle and adaptive ant colony algorithm. Then the effects of traffic distribution on passenger evacuation time are analyzed through computational experiments, and reasonable evacuation strategies for passengers are proposed under different passenger flow distributions.Finally, the emergency evacuation capability of urban rail transit hub is studied based on ACP approach. The assessment model for emergency evacuation capability is built, and emergency strategies for typical evacuation scenarios that improve evacuation capability are proposed. The emergency evacuation artificial system of some urban rail transit hub is established based on ACP approach and emergency evacuation capacity of the subway station is analyzed through computational experiments. By comparing the results with the assessment model for the same evacuation scenario, the performance of artificial system is tested and the feasibility of the assessment model is verified.