An algorithm for integrating peer-to-peer ridesharing and schedule-based transit system for first mile/last mile access

Pramesh Kumar, Alireza Khani

Research output: Contribution to journalArticlepeer-review

Abstract

Due to limited transit network coverage and infrequent service, suburban commuters often face the transit first mile/last mile (FMLM) problem. To deal with this, they either drive to a park-and-ride location to take transit, use carpooling, or drive directly to their destination to avoid inconvenience. Ridesharing, an emerging mode of transportation, can solve the transit first mile/last mile problem. In this setup, a driver can drive a ride-seeker to a transit station, from where the rider can take transit to her respective destination. The problem requires solving a ridesharing matching problem with the routing of riders in a multimodal transportation network. We develop a transit-based ridesharing matching algorithm to solve this problem. The method leverages the schedule-based transit shortest path to generate feasible matches and then solves a matching optimization program to find an optimal match between riders and drivers. The proposed method not only assigns an optimal driver to the rider but also assigns an optimal transit stop and a transit vehicle trip departing from that stop for the rest of the rider's itinerary. We also introduce the application of space-time prism (STP) (the geographical area which can be reached by a traveler given the time constraints) in the context of ridesharing to reduce the computational time by reducing the network search. An algorithm to solve this problem dynamically using a rolling horizon approach is also presented. We use simulated data obtained from the activity-based travel demand model of Twin Cities, MN to show that the transit-based ridesharing can solve the FMLM problem and save a significant number of vehicle-hours spent in the system.

Original languageEnglish (US)
Article number102891
JournalTransportation Research Part C: Emerging Technologies
Volume122
DOIs
StatePublished - Jan 2021

Bibliographical note

Funding Information:
This research is conducted at the University of Minnesota Transit Lab, currently supported by the following, but not limited to, projects:, ? National Science Foundation, awards CMMI-1637548 and CMMI-1831140 ? Freight Mobility Research Institute (FMRI), Tier 1 Transportation Center, U.S. Department of Transportation: award RR-K78/FAU SP#16-532 AM2 and AM3 ? Minnesota Department of Transportation, Contract No. 1003325 Work Order No. 44 and 111 ? University of Minnesota Office of Vice President for Research, COVID-19 Rapid Response Grants, The authors are grateful to Metropolitan Council for sharing the data. We are also grateful to the anonymous referees for their constructive input to improve the quality of this article. Any limitation of this study remains the responsibility of the authors.

Publisher Copyright:
© 2020 Elsevier Ltd

Keywords

  • Matching optimization
  • Ridesharing
  • Rolling horizon
  • Schedule-based transit shortest path
  • Space-time prism (STP)
  • Transit
  • Transit first mile last mile

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