Determination of the Peak Hour Ridership of Metro Stations in Xi’an, China Using Geographically-Weighted Regression
Lijie Yu,
Yarong Cong and
Kuanmin Chen
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Lijie Yu: Department of Traffic Engineering, College of Transportation Engineering, Chang’an University, Xi’an 710064, China
Yarong Cong: Department of Traffic Engineering, College of Transportation Engineering, Chang’an University, Xi’an 710064, China
Kuanmin Chen: Department of Traffic Engineering, College of Transportation Engineering, Chang’an University, Xi’an 710064, China
Sustainability, 2020, vol. 12, issue 6, 1-22
Abstract:
The ridership of a metro station during a city’s peak hour is not always the same as that during the station’s own peak hour. To investigate this inconsistency, this study introduces the peak deviation coefficient to describe this phenomenon. Data from 88 metro stations in Xi’an, China, are used to analyze the peak deviation coefficient based on the geographically weighted regression model. The results demonstrate that when the land around a metro station is mainly land for work, primary and middle schools, and residences, its station’s peak hour is consistent with the city’s peak hour. Additionally, the station’s peak hour is more likely to deviate from the city’s peak hour for suburban stations. There are two ridership options when designing stations, namely the extra peak hour ridership during a city’s peak hour and that during a station’s peak hour, and the larger of the two is used to design metro stations. The mixed land use ratio must be considered in urban land use planning, because although non-commuting land can mitigate the traffic pressure of a city’s peak hour, it may cause the deviation of the station’s peak hours from that of the city.
Keywords: urban rail transit station; peak deviation coefficient; transportation and land use; geographically weighted regression; station design (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:6:p:2255-:d:332123
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