Transit Planning Optimization Under Ride-Hailing Competition and Traffic Congestion
With the soaring popularity of ride-hailing, the interdependence between transit ridership, ride-hailing ridership, and urban congestion motivates the following question: can public transit and ride-hailing coexist and thrive in a way that enhances the urban transportation ecosystem as a whole? To answer this question, the authors develop a mathematical and computational framework that optimizes transit schedules while explicitly accounting for their impacts on road congestion and passengers' mode choice between transit and ride-hailing. The problem is formulated as a mixed integer nonlinear program and solved using a bilevel decomposition algorithm. Based on computational case study experiments in New York City, the authors' optimized transit schedules consistently lead to 0.4%-3% system-wide cost reduction. This amounts to rush-hour savings of millions of dollars per day while simultaneously reducing the costs to passengers and transportation service providers. These benefits are driven by a better alignment of available transportation options with passengers' preferences - by redistributing public transit resources to where they provide the strongest societal benefits. These results are robust to underlying assumptions about passenger demand, transit level of service, the dynamics of ride-hailing operations, and transit fare structures. Ultimately, by explicitly accounting for ride-hailing competition, passenger preferences, and traffic congestion, transit agencies can develop schedules that lower costs for passengers, operators, and the system as a whole: a rare win-win-win outcome.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/1767714
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Supplemental Notes:
- Abstracts reprinted with permission of INFORMS (Institute for Operations Research and the Management Sciences, http://www.informs.org).
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Authors:
- Wei, Keji
- Vaze, Vikrant
- Jacquillat, Alexandre
- Publication Date: 2022-5
Language
- English
Media Info
- Media Type: Digital/other
- Features: References;
- Pagination: pp 725-749
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Serial:
- Transportation Science
- Volume: 56
- Issue Number: 3
- Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
- ISSN: 0041-1655
- Serial URL: http://transci.journal.informs.org/
Subject/Index Terms
- TRT Terms: Competition; Optimization; Public transit; Ridership; Ridesourcing; Schedules; Traffic congestion
- Geographic Terms: New York (New York)
- Subject Areas: Operations and Traffic Management; Passenger Transportation; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01849400
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 24 2022 10:54AM