Micro Transit Simulation of On-Demand Shuttles Based on Transit Data for First- and Last-Mile Connection

The authors simulate the introduction of shared, automated, and electric vehicles (SAEVs) providing on-demand shuttles service in a large-scale transport digital twin of the San Francisco Bay Area region (California, USA) based on transit supply and demand data, and using the mesoscopic agent-based Behavior, Energy, Autonomy, and Mobility beta software (BEAM) developed at the Lawrence Berkeley National Laboratory (LBNL). The main goal of this study is to test the operations of this novel mobility service integrated with existing fixed-route public transportation service in a mesoscopic simulation of a real case scenario, while testing the BEAM beta software capabilities. In particular, the authors test the introduction of fleets of on-demand vehicles bound to operate within circular catchment areas centered on high-frequency transit stops, with the purpose of extending the reach of fixed-route transit by providing an alternative first- and last-mile connection at high-frequency public transport stations. Results show that on-demand automated shuttles represent the best solution for some users, increasing the overall transit ridership by 3%, and replacing mostly ride-hail trips, especially those connecting to transit stops, but also some walking trips. This type of service has the potential to reduce overall vehicle miles traveled (VMT), increase transit accessibility, and save energy, but future research is needed to optimize this type of service and make it more attractive to travelers.

• Record URL:
  • https://doi.org/10.3390/ijgi12040177
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22209964
• Supplemental Notes:
  • Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
• Authors:
  • Poliziani, Cristian
  • 0000-0002-7646-1394
  • Hsueh, Gary
  • 0000-0002-5753-7365
  • Czerwinski, David
  • 0000-0002-6344-6304
  • Wenzel, Tom
  • 0000-0001-5522-9687
  • Needell, Zachary
  • 0000-0001-6190-5186
  • Laarabi, Haitam
  • 0000-0002-0375-7266
  • Schweizer, Joerg
  • 0000-0003-2289-6111
  • Rupi, Federico
  • 0000-0001-8404-5684
• Publication Date: 2023-4

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: 177
• Serial:
  • ISPRS International Journal of Geo-Information
  • Volume: 12
  • Issue Number: 4
  • Publisher: MDPI AG
  • ISSN: 2220-9964
  • Serial URL: https://www.mdpi.com/journal/ijgi
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Demand responsive transportation; Electric vehicles; Public transit; Shuttle service; Simulation
• Geographic Terms: San Francisco Bay Area
• Subject Areas: Passenger Transportation; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01908465
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 20 2024 9:14AM