![]() Researchers initially studied the four-stage method, and have gradually developed more advanced passenger flow forecasting methods which include total control, and the distribution of passenger flow on the rail transit network. As urban rail transit develops, research into passenger flow forecasting also continues to expand. ![]() ![]() Finally, data from 52 stations in Chongqing, China were used to verify the findings, with the results in Chongqing predominantly corresponding to those in Xi’an.ĭue to the long service life of urban rail, it is necessary to build rail transit according to passenger flow forecast results to adapt the rail for future travel traffic. All stations with a proportion of commuter travel land that was less than 0.50 had morning PDCs over 1.10. More than 90.00% of stations with a proportion of commuter travel land that was more than 0.50 had PDCs under 1.10. Statistics of land usage for every type of station showed that when the stations were surrounded by developed land, the relationship between the PDC and the commuter travel land proportion was to some extent orderly. Morning peak deviation coefficient (PDC) and evening PDC were selected as datasets, and stations were classified accordingly. This was done by analyzing the inconsistencies of passenger flow volume between the station’s peak hours and the city’s peak hours. Data from 63 stations in Xi’an, China, were then used to present an enlargement coefficient which can change the boarding and alighting volume in city peak hours to a station’s own peak hours. This study locates the formation mechanism of station peak in which the temporal distribution of the station is the superposition of different temporal distributions of the purpose determined by land-use attributes. For some stations, the highest flow does not occur in the city peak hours, and station scale design is often too small. Passenger flow forecasting at planning stages can only predict passenger flow volume in city peak hours and for the whole day. The inconsistencies of passenger flow volume between stations’ peak hours and cities’ peak hours have emerged as a phenomenon in various cities worldwide.
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