为定量化分析地铁站台客流组织方案的应用效果，实地收集乘客候车分布数据，统计分析候车位置选择的特性，研究发现乘客的候车位置选择具有集中性，并受行走距离、排队长度和候车区域容量影响。基于细菌趋药性(BC)算法原理，结合站台乘客候车位置选择特性，建立了站台乘客分布仿真模型，并利用实测数据对模型进行了标定和验证。从实例站台的限流栏杆长度方面提出了优化方案，利用所建模型再现了实例站台的候车场景及优化方案，对优化效果进行验证。结果显示：优化的限流栏杆设置方案实施后，站台候车区域客流平均密度在各客流条件下分别下降了0.02、0.07和0.09，可上车的人数分别增加了10、8及11人次，因此所提优化方案具备有效性，得到的模型及应用成果能为地铁车站运营管理方在站台客流控制策略的制定方面提供理论支持和依据。

For quantitative analysis of the application effect of a subway platform passenger flow organization scheme, the data on the passenger waiting distribution were collected on-site, and the characteristics of the waiting position selection were statistically analyzed. Finally, it was found that the waiting position selection of the passengers was centralized and affected by the walking distance, queue length, and waiting area capacity. Based on the principle of the bacterial chemotaxis (BC) algorithm and the characteristics of platform passenger waiting position selection, a platform passenger distribution simulation model was established, and the model was calibrated and validated using the measured data. An optimization scheme has been proposed based on the length of the current-limiting railing of the platform, the waiting scene and optimization scheme of the platform are reproduced using the model, and the optimization effect is verified. The results show that after the implementation of the optimized scheme of limiting the railing, the average density of passenger flow in the waiting area of the platform decreased by 0.02, 0.07, and 0.09, respectively, and the number of people who could get on the bus increased by 10, 8, and 11; this scheme was therefore considered to be effective. The model and its application results can provide the theoretical support and basis for subway station operation management to determine a passenger flow control strategy.

U121

国家重点研发计划(2017YFB1201104); 朝阳区博士后科研活动经费资助项目(Q1038001201901)