数据驱动的城市轨道交通网络优化策略

The Optimization Strategy of Data Driven Urban Rail Transit Network

摘要: 城市轨道交通已成为大城市居民出行的主要载体，也是城市发展的重要支撑。为了提供合理的限流意见，建立了城轨交通单一线路乘客限流模型。首先，建立乘客出行OD概率矩阵，以便观察乘客出行的分布状况。其次，通过设定乘客总出行等待时间指标、乘客总在车旅行时间指标、乘客出行延误时间惩罚系数三个指标，建立了单一线路乘客限流模型目标函数。最后，以北京地铁八通线的客流数据为实验数据，基于MATLAB平台运用设计的改进模拟退火算法对模型进行求解，得到八通线早高峰时段最优单线协同限流策略，并提出相对应的限流意见。

Abstract: Urban rail transit has become the main carrier of urban residents’ travel and the important support of urban development. In order to provide reasonable opinions on current limiting, a single line passenger current limiting model of urban rail transit is established. Firstly, od probability matrix of passenger trip is established to observe the distribution of passenger trip. Secondly, the objective function of single line passenger current limiting model is established by setting three indexes: total travel waiting time index, total in vehicle travel time index and penalty coefficient of travel delay time. Finally, the passenger flow data of Beijing Metro Batong line is taken as the experimental data, the model is solved by using the improved simulated annealing algorithm based on MATLAB platform. The optimal single line collaborative current limiting strategy in the early peak period of Batong line is obtained and the corresponding current limiting opinions are put forward.