Simulation of Autonomous Transit On Demand for Fleet Size and Deployment Strategy Optimization

Autonomous transit on demand (ATOD) is a potential future public transit mode, which appeals to a lot of researchers and policymakers. In the project, ATOD is simulated in MATSim to explore the optimal fleet size and deployment strategy to help policymakers to decide how to introduce the new transport system in the future. The simulation enables the system to explore the optimization automatically under specific constraints with the MATSim evolutionary algorithm.

• Record URL:
  • https://doi.org/10.1016/j.procs.2018.04.138
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1877050918305003
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/18770509
• Supplemental Notes:
  • © 2018 Biyu Wang et al. Published by Elsevier B.V. 7th International Workshop on Agent-based Mobility, Traffic and Transportation Models,Methodologies and Applications (ABMTrans 2018).
• Authors:
  • Wang, Biyu
  • Ordonez Medina, Sergio Arturo
  • Fourie, Pieter
• Publication Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 797-802
• Serial:
  • Procedia Computer Science
  • Volume: 130
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1877-0509
  • Serial URL: http://www.sciencedirect.com/science/journal/18770509
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Intelligent vehicles; Optimization; Public transit; Simulation; Vehicle fleets
• Subject Areas: Operations and Traffic Management; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01677242
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 31 2018 5:08PM