动态随机客流下城轨列车运行调整策略

Operation adjustment of urban rail transit trains under dynamic stochastic passengers

针对城市轨道交通中随机到达客流对列车运行造成的延误问题,将动态变化且服从泊松分布的客流到达率拟合为随机分布变量.结合随机规划理论,构建了以列车发车时间偏差及到站列车间隔偏差为最小化目标的期望模型.应用最优化方法中的K-T条件对所建模型进行求解,得出调整相关偏差的控制策略.通过实例仿真模拟列车运行在受到随机客流及外界干扰的影响下产生的延误,比较采取调整策略前后列车在各站的离站时间偏差及其优化水平,结果表明:所设计的列车运行调整策略能够有效减小列车延误约25%,使得在动态客流下的城市轨道交通列车运行更能"按图行车".

This paper aims at reducing the train delay in urban rail transit,which is caused by disturbance from the random passenger arrivals.The dynamic changeable arrival rate of passengers is set as a random variable which follows a Poisson distribution.Appling stochastic programming theory,this paper proposes an expectation model for train operation which tries to minimize the deviations of the departure time of trains and the deviations of the time intervals between successive arriving trains.The control strategy for adjusting the deviations is obtained by solving the model with the Kuhn-Tucker condition from optimal method.In the base of the real survey data,the simulation chapter obtains the delay of trains by simulating trains operate under the influence of random passenger arrivals and external factors.The paper also compares the deviations of departure time and the levels of optimization before and after using the adjustment strategy.In this way,the paper verifies that the designed strategy can effectively reduce the train delay by 25% ,enabling the urban rail transit trains to operate more steadily according to the timetable.