Passenger Hotspot Mining Based on Taxi GPS Data—Taking Chengdu as an Example

To explore the status of operation and travel demand characteristic, the authors extract the taxi operation and travel demand information based on data mining model. On this basis, the passenger flow volume in each period, travel time distribution, travel distance distribution are discussed. Simultaneously, the spatial distributive characteristic of travel demand is obtained by displaying the location information on Arcgis software. In addition, the authors verified the characteristic through data analysis. Some significant conclusions are drawn through the taxi operation in Chengdu: (1) the travel demand of taxi in Chengdu is stable, and the travel demand on weekends decreased slightly compared with the travel demand on weekdays. (2) The travel demand is concentrated on the district within the third ring road. (3) A significant difference between Chengdu taxi passenger flow and conventional bus flow is that taxi passenger flow does not show obvious peak characteristics in the morning and evening. The proposed approach can obtain taxi operation and travel demand situations, which can provide aid decision making for analysis and evaluation, operation dispatch, and assignment of vehicles.

Language

  • English

Media Info

  • Media Type: Web
  • Pagination: pp 883-892
  • Monograph Title: ICTE 2019

Subject/Index Terms

Filing Info

  • Accession Number: 01731505
  • Record Type: Publication
  • ISBN: 9780784482742
  • Files: TRIS, ASCE
  • Created Date: Feb 21 2020 9:51AM