Fan-Shaped Model for Generating the Anisotropic Catchment Area of Subway Stations based on Feeder Taxi Trips
The catchment areas of subway stations have always been considered as a circular shape in previous research. Although some studies show the catchment area may be affected by road conditions, public transportation, land use, and other factors, few studies have discussed the shape of the catchment area. This study focuses on analyzing the anisotropy of catchment areas and developing a sound methodology to generate them. Based on taxi global positioning system (GPS) data, this paper first proposes a data mining method to identify feeder taxi trips around subway stations. Then, a fan-shaped model is proposed and applied to Xi'an Metro Line 1 to generate catchment areas. The number and angle of fan areas are determined according to the spatial distribution characteristics of GPS points. Results show that the acceptable distance of the catchment area has significant differences in different directions. The average maximum acceptable distance of one station is 2.31 times the minimum. Furthermore, for feeder taxis, the overlap ratio of the catchment area is very high. Travelers in several places could choose several different stations during the travel. A multiple linear regression model was introduced to find the influencing factors, and the result shows the anisotropy of the catchment area is affected not only by neighboring subway stations, but also by the road network, distance from the city center, and so on.
S. Liu et al., "Fan-Shaped Model for Generating the Anisotropic Catchment Area of Subway Stations based on Feeder Taxi Trips," Transportation Research Record, SAGE Publications, Jan 2022.
The definitive version is available at https://doi.org/10.1177/03611981221124594
Civil, Architectural and Environmental Engineering
Keywords and Phrases
anisotropy; catchment area; fan-shaped model; feeder taxi; subway station
International Standard Serial Number (ISSN)
Article - Journal
© 2023 SAGE Publications, All rights reserved.
01 Jan 2022
Chang'an University, Grant 300102342204