Optimal online dispatch for high-capacity shared autonomous mobility-on-demand systems

Cheng Li, David Parker, Qi Hao

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

167 Downloads (Pure)

Abstract

Shared autonomous mobility-on-demand systems hold great promise for improving the efficiency of urban transportation, but are challenging to implement due to the huge scheduling search space and highly dynamic nature of requests. This paper presents a novel optimal schedule pool (OSP) assignment approach to optimally dispatch high-capacity ride-sharing vehicles in real time, including: (1) an incremental search algorithm that can efficiently compute the exact lowest-cost schedule of a ride-sharing trip with a reduced search space; (2) an iterative online re-optimization strategy to dynamically alter the assignment policy for new incoming requests, in order to maximize the service rate. Experimental results based on New York City taxi data show that our proposed approach outperforms the state-of-the-art in terms of service rate and system scalability.
Original languageEnglish
Title of host publication2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Number of pages7
ISBN (Electronic)978-1-7281-9077-8
ISBN (Print)978-1-7281-9078-5
DOIs
Publication statusPublished - 18 Oct 2021
Event2021 IEEE International Conference on Robotics and Automation (ICRA) - International Convention and Exhibition Center, Xi’an , China
Duration: 30 May 20215 Jun 2021

Publication series

NameIEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE

Conference

Conference2021 IEEE International Conference on Robotics and Automation (ICRA)
Abbreviated titleICRA 2021
Country/TerritoryChina
CityXi’an
Period30/05/215/06/21

Keywords

  • space vehicles
  • shedules
  • scalability
  • urban areas
  • optimal scheduling
  • dynamic scheduling
  • real time systems

Fingerprint

Dive into the research topics of 'Optimal online dispatch for high-capacity shared autonomous mobility-on-demand systems'. Together they form a unique fingerprint.

Cite this