Real-time Transfers for Improving Efficiency of Ridesharing Services in the Environment with Connected and Self-driving Vehicles

Yen Long Chen, Kuo Feng Ssu, Yu Jung Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Current ridesharing services typically support one-hop delivery. With potential vehicle transfers, the ridesharing efficiency can be enhanced. This paper develops a real-time transfer approach based on a centralized pubic taxicab scheduling system. The approach can improve the traffic efficiency by leveraging real-time trajectory information of vehicles maintained in the system. The system can search for a suitable location for the passenger who could be transferred, and calculate the subsequent routes for original and transfer taxicabs. The simulation results based on the road networks of Midtown Manhattan demonstrate the effectiveness of the developed scheme compared to the transfer-disallowed scheme. Several passengers can be transferred to other vehicles to save more travel time and travel distance. Taxicabs on the roads can be used more efficiently.

Original languageEnglish
Title of host publicationProceedings - 2020 International Computer Symposium, ICS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages165-170
Number of pages6
ISBN (Electronic)9781728192550
DOIs
Publication statusPublished - 2020 Dec
Event2020 International Computer Symposium, ICS 2020 - Tainan, Taiwan
Duration: 2020 Dec 172020 Dec 19

Publication series

NameProceedings - 2020 International Computer Symposium, ICS 2020

Conference

Conference2020 International Computer Symposium, ICS 2020
Country/TerritoryTaiwan
CityTainan
Period20-12-1720-12-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Computational Mathematics

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