Deviation of Peak Hours for Urban Rail Transit Stations: A Case Study in Xi’an, China

Lijie Yu, Quan Chen and Kuanmin Chen
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Lijie Yu: Department of Traffic Engineering, Highway School, Chang’an University, Xi’an 710064, China
Quan Chen: Department of Traffic Engineering, Highway School, Chang’an University, Xi’an 710064, China
Kuanmin Chen: Department of Traffic Engineering, Highway School, Chang’an University, Xi’an 710064, China

Sustainability, 2019, vol. 11, issue 10, 1-21

Abstract: The inconsistencies of passenger flow volume between stations’ peak hours and cities’ peak hours have emerged as a phenomenon in various cities worldwide. Passenger flow forecasting at planning stages can only predict passenger flow volume in city peak hours and for the whole day. For some stations, the highest flow does not occur in the city peak hours, and station scale design is often too small. 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. 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 was done by analyzing the inconsistencies of passenger flow volume between the station’s peak hours and the city’s peak hours. Morning peak deviation coefficient (PDC) and evening PDC were selected as datasets, and stations were classified accordingly. 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. More than 90.00% of stations with a proportion of commuter travel land that was more than 0.50 had PDCs under 1.10. All stations with a proportion of commuter travel land that was less than 0.50 had morning PDCs over 1.10. 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.

Keywords: transport planning; urban rail transit stations; peak deviation coefficient; clustering methods (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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