Simulating the effect of strategies to increase transit ridership by reallocating bus service: Two case studies

Gregory D. Erhardt, Vedant S. Goyal, Josephine Kressner, Simon J. Berrebi, Candace Brakewood, Kari E. Watkins

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We evaluate three strategies that transit operators might consider to increase ridership: a) increasing service on bus routes serving the highest share of low-income riders, b) increasing service on those bus routes with the highest ridership, and c) further providing the high-ridership routes identified in strategy (b) with exclusive bus lanes. In each scenario, we double the service frequency of buses on the focus routes and reduce the frequency on all other routes to maintain the total vehicle revenue miles, making the changes roughly cost-neutral. We tested these scenarios for Oshkosh, Wisconsin, and Atlanta, Georgia, using a modeling framework that combines CityCast, a commercially available data-driven planning tool to replicate observed travel patterns, and MATSim to simulate how travelers would change the route, mode, and time-of-day of the trips they make in response to the service changes. The results show substantial ridership gains for all but one scenario, suggesting that these strategies may provide a promising, low-cost means of increasing transit ridership in some contexts. However, impacts varied across the two case studies, indicating that local conditions play a role.

Original languageEnglish
Article number100080
JournalJournal of Public Transportation
Volume26
DOIs
StatePublished - Jan 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Keywords

  • CityCast
  • MATSim
  • Transit ridership
  • Transport modeling
  • Transport simulation

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Urban Studies

Fingerprint

Dive into the research topics of 'Simulating the effect of strategies to increase transit ridership by reallocating bus service: Two case studies'. Together they form a unique fingerprint.

Cite this