基于WIFI数据的城市轨道交通乘客出行时空轨迹推定

Travel Time-space Trajectory Characterization of Urban Rail Transit Network Based on WIFI Data

针对复杂轨道交通网络环境中乘客出行路径选择与站内走行行为的问题,传统方法由于缺乏时空维度的详细数据,所得结果与实际情况易存在偏差。城市轨道交通网络WIFI信号的逐渐覆盖和移动终端数量的持续增长,提供了大量无线定位信息资源。为实现乘客出行时空轨迹的精准化识别,利用轨道交通网络范围内的WIFI信号数据,建立基于乘客完整出行链的轨道交通超级网络,提出基于改进的接收信号强度指示(RSSI)定位算法的乘客出行轨迹推断模型。通过实验测试验证了该方法的可靠性,结果表明:该方法能更为准确地推断乘客在城市轨道交通网络及车站内的综合出行过程,可为城市轨道交通客流分析、票务清算等提供理论与技术支持。

For the problem of passenger travel route choice and walking within stations in complex urban rail transit（URT） network environment, there are errors with traditional method for the lack of detailed data of timespace dimension. The gradual covering of WIFI and continuous growth of mobile terminal provide a lot of information resources of wireless location. In order to characterize passengers＇ time-space trajectories precisely, this study, according to WIFI signal data in URT network environment, established a super network based on passenger trip-chain and proposed an inference model based on modified Received Signal Strength Indicator（RSSI）positioning algorithm for passenger travel space-time trajectory. Initial experiments are conducted to test the reliability of the proposed methodology. The results showed that it can accurately infer passengers＇ comprehensive travel process both in network and stations, providing a basis for URT passenger flow analysis and fare clearing,etc.