Using Taxi GPS Trajectory Data to Optimize the Spatial Layout of Urban Taxi Stands

The unreasonable layout of taxi stands (TS) in urban areas not only fails to provide bidirectional guidance for drivers and passengers but also wastes spatial resources and aggravates the surrounding traffic. This paper compares the performance of three classical location models in optimizing TS spatial layout, and develops an extended model integrating the p-median and distance factor to support TS site selection in urban planning from multiple perspectives. To this end, taxi demand with spatial–temporal dynamics is extracted from taxi global positioning system (GPS) data to uncover the restrictive distribution characteristics of the setting areas and specific locations of TS with GIS platform. Taxi demand is then subdivided, and potential service points are set up on the road network. With the constraints of the supply and demand environment, we design the TS location models (TSLM) based on the set covering problem (SCP), the maximal covering location problem (MCLP), and the p-median problem (PMP), respectively. Furthermore, the TSLM based on PMP is extended to consider the maximum acceptable distance for passengers. A genetic algorithm-based procedure is introduced for solving the extended TSLM. An experiment conducted in China compares the facility coverage capacity, taxi demand allocation, and passenger access willingness of the optimal layout schemes obtained from four TSLMs. The number of parking spaces at TS is also evaluated. The result demonstrates that extended TSLM outperforms the other three models in the validity of locating TS.

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    • The authors confirm contribution to the paper as follows: study conception and design: Zhaowei Qu, Xin Wang; data collection: Xianmin Song; analysis and interpretation of results: Xin Wang, Haitao Li, Zhaotian Pan; draft manuscript preparation: Xianmin Song, Xin Wang. All authors reviewed the results and approved the final version of the manuscript. © National Academy of Sciences: Transportation Research Board 2020.
  • Authors:
    • Wang, Xin
    • Qu, Zhaowei
    • Song, Xianmin
    • Li, Haitao
    • Pan, Zhaotian
  • Publication Date: 2021-3


  • English

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  • Accession Number: 01762299
  • Record Type: Publication
  • Files: TRIS, TRB, ATRI
  • Created Date: Jan 2 2021 3:05PM