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