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Optimization of Bottleneck Facilities in Subway Stations Based on WiFi Data

机译:基于WiFi数据的地铁站优化瓶颈设施

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With the rapid development of subway network, crowding has become a common problem for both the passengers and the management departments. To study this problem, data like MAC address and their arrival time were obtained through WiFi probes in three subway stations in Beijing in 2018. The credibility of WiFi data was verified by the sample consistency, the measurement accuracy and WiFi usage ratio. The passing time in bottleneck areas was considered to be a key indicator for facility evaluation in Anylogic-based simulation. The security inspection and the fare gate were shown as the bottleneck areas. The schemes were put forward to optimize the layout. The results show that if the passengers with small luggage were guided to use portable detectors, the total average passing time will drop from 48.4 to 44.8 s. In a subway station, 8-10 fare gates are basically enough to save the passing time for the crowds.
机译:随着地铁网络的快速发展,拥挤已成为乘客和管理部门的常见问题。为研究这个问题,通过2018年北京三个地铁站的WiFi探测来获得MAC地址及其到达时间的数据。通过样品一致性,测量精度和WiFi使用率验证了WiFi数据的可信度。瓶颈区域中的传递时间被认为是基于AnyLogic的仿真中的设施评估的关键指标。安全检查和票价门被显示为瓶颈区域。提出了这些方案以优化布局。结果表明,如果带有小行李箱的乘客被引导使用便携式探测器,则总平均通过的时间将从48.4降至44.8秒。在地铁站,8-10票价基本上足以挽救人群的传递时间。

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