基于手机信令数据的旅客联程出行时空特征分析方法

Spatial and Temporal Characteristics of Intermodal Passenger Transportation Based on Mobile Signaling Data

为高效准确地识别旅客联程出行方式,基于旅客联程出行行为特征,引入不同运输方式场站地理位置、场站数据取样最佳半径、旅客行驶速度等关键参数,对旅客手机信令数据进行筛选、校核和计算,提出了基于手机信令数据的旅客联程出行方式识别方法,同时测算了不同运输方式场站数据取样最佳半径。以2018年国庆假期广东省内旅客出行为例进行分析,剔除了约98%的无关信令数据。分析结果显示,广东省内公铁联运出行比例最高,广州、深圳两大枢纽城市的客流集疏运效应突出,广佛城际出行联系较为密切,佛山机场的潜力较大。研究表明,识别方法大幅降低了信令数据分析量和运算成本,方法原理和技术路线清晰,分析结果准确、符合实际。

To accurately and efficiently identify passengers′travel modes in intermodal transportation,based on the behavior characteristics of intermodal passenger transportation,the geographical location of stations in different transportation modes,the best radius of station data sampling and passengers′travel speed were introduced as key parameters.Through filtering,utilizing and calculating the mobile signaling data,an identification method to passengers′travel modes in intermodal transportation was put forward taking advantage of mobile signaling data.The best radiuses of station data sampling of different transportation modes were measured simultaneously.A case study of passenger transportation in Guangdong Province during 2018 National Day holiday was conducted and about 98%irrelevant signaling data were removed.The analysis results showed that the highway-railway travel had the highest proportion within Guangdong province;Guangzhou and Shenzhen were the top two cities which had a prominent effect on passenger collection and distribution;the intercity travels between Guangzhou and Foshan were frequent and Foshan airport had great potential of passenger transportation.The identification method could greatly reduce the signaling data analysis volume and operation cost.Its principle and technical route are clear,which leads to accurate and practical analysis results.