Research on Urban Taxi Allocation Optimization Based on Dynamic Change of Travel Demand

Taxis can satisfy the high-level travel demands in urban areas, and the rational layout of urban taxis will affect both taxi passengers’ travel experience and taxi drivers’ income. Too many taxis in some regions with few travel demands will cause a waste of resources, while too few in other regions with lots of travel demands will affect the quality of service. Using minimum waiting time as the objective, this paper establishes an optimization model considering the dynamic change of taxi travel demand with time, and genetic algorithm is used to solve the problem. The feasibility of the model is verified by a simulation example. The effects of taxi scale and travel time on the layout and average waiting time are discussed. The method of determining the reasonable scale of taxi is given. The research results can provide theoretical support for the determination of urban taxi scale and reasonable spatial layout.

• Record URL:
  • https://doi.org/10.1061/9780784483053.229
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784483053
• Supplemental Notes:
  • © 2020 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Liang, Keke
  • Li, Tao
  • Liu, Zhen-Guo
• Conference:
  • 20th COTA International Conference of Transportation Professionals
  • Location: Xi’an , China
  • Date: 2020-8-14 to 2020-8-16
• Publication Date: 2020

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 2715-2725
• Monograph Title: CICTP 2020: Transportation Evolution Impacting Future Mobility

Subject/Index Terms

• TRT Terms: Optimization; Passengers; Quality of service; Resource allocation; Taxicabs; Travel demand; Travel time; Waiting time
• Subject Areas: Operations and Traffic Management; Passenger Transportation; Public Transportation;

Filing Info

• Accession Number: 01768183
• Record Type: Publication
• ISBN: 9780784483053
• Files: TRIS, ASCE
• Created Date: Mar 25 2021 9:35AM