Passenger Flow Assignment Method for Urban Rail Transit Networks Based on Inference of Spatiotemporal Path

To calculate passenger flow distribution in urban rail transits, a passenger flow assignment method based on inference of passenger spatiotemporal path is proposed with the data collected from the automatic fare collection (AFC) and train timetables. Firstly, the passenger travel time parameters are estimated with the above two types of data. The feasible path set of each origin–destination (OD) in the whole network is then obtained by using the feasible path search algorithm based on the node-inserting method. Subsequently, according to the inbound and outbound information from passenger smart cards, train timetable and matched feasible path set, an inference model of passenger effective travel path and train set is built to obtain the effective travel result set. Finally, a train operation is developed with the obtained effective result set, train load capacity, and train timetable to determine the sole effective travel path and riding train. A calculation system for the passenger flow in urban rail transit networks is designed and developed, and a case study is conducted on weekday passenger flow data of urban rail transit. The results show that the average difference of section passenger flow between the calculated results and operation reference data of upstream and downstream is 2.03% and 3.90%, respectively, and the trend of train load rate confirms to the line routing. Moreover, the source of transfer passenger flow at transfer station is stable in the morning and evening peaks, but the proportion of sources in the morning peak is more stable that in the evening peak.