基于时空路径匹配的城市轨道交通新型清分算法

New Clearing Algorithm for Urban Rail Transit Based on Temporal-Spatial Path Matching

大多城市选择传统的“分配型”模型对轨道客流进行清分,即按照既定固化比例进行清分,未充分考虑乘客和列车的实际运行状态,导致清分结果存在一定偏差。为进一步研究解决传统清分算法导致的偏差问题,提出基于时空路径匹配的客流清分模型,基于乘客刷卡数据和列车实际运行ATS数据,对乘客个体OD出行过程进行全方案搜索,同时融合手机信令等多元大数据,实现乘客-列车的精准匹配。通过路网建模、乘车方案搜索与匹配,得出的客流清分结果,经采集手机信令数据进行分析验证,证明基于时空路径匹配的清分算法适用于轨道交通客流清分要求,可为轨道交通运营组织、客流调度、应急指挥等提供决策支持。

Most cities select the traditional“distribution”model for rail passenger clearing,i.e.clearing is carried out according to the established fixed proportion,and the actual situation of passengers and operating status of trains are not fully considered,resulting in certain deviations in the allocating results.In order to further study and solve the deviation problem caused by the traditional clearing algorithm,this paper proposes a passenger clearing model based on temporal-spatial path matching.Based on the card swiping data of passengers and ATS data of actual train operation,the whole scheme search is carried out for the individual OD travel process of passengers.At the same time,multi-dimensional big data such as mobile phone signaling are integrated to realize accurate matching between passengers and trains.The passenger clearing results obtained through railway network modeling,traveling scheme search and matching are analyzed and verified by collecting mobile phone signaling data,which proves that the clearing algorithm based on temporal-spatial path matching is suitable for the passenger clearing requirements of rail transit,and can provide decision support for rail transit operation organization,passenger flow dispatching,emergency command,etc.