【摘要】 近年来地铁客运量不断上涨,列车故障却频频发生,当列车发生故障时,客流拥挤现象也因为行车延误变的更为严重,如何对故障状态下的行车组织进行调整显得愈发重要。在减少故障点前方客流积压的基础上,以晚点列车尽快恢复列车计划运行图为目的制定列车行车方案。首先通过延长故障前方列车的停站时间,使列车尽可能带走产生积压风险的潜在客流为目的制定前车运行调整方案;在此基础上以故障点后方列车的总延误时间最少为优化目标建立后车运行调整模型,并采用粒子群算法对行车调整模型进行求解。仿真结果表明,该方法可以使乘客等待时间和列车的总延误时间分别减少38.9%和58.2%,可以有效提高乘客服务水平。更多还原

【Abstract】 In recent years,subway passenger traffic has continued to rise,but train failures have occurred frequently. When trains fail,passenger congestion has become more serious due to train delays. Therefore,how to adjust the organization of train operations under failure conditions becomes more and more important.On the basis of reducing the backlog of passenger flow in front of the fault point,this paper formulated a train operation plan with the purpose of restoring the train plan as soon as possible. First,we formulated the operation adjustment plan of the preceding train by extending the stop time of the train in front of the failure,so that the train can take away the potential passenger flow that generates the backlog risk as much as possible. On this basis,the total delay time of the train behind the failure point is at least as the optimization goal. The following vehicle run the adjustment model,and the particle swarm algorithm was used to solve the vehicle adjustment model. Simulation results show that this method can reduce passengers’ waiting time and total train delay time by 38. 9% and 58. 2%,respectively,which proves that this method can effectively improve the level of passenger service.更多还原