An analytical framework for modeling ride pooling efficiency and minimum fleet size
Ride pooling (RP) is a transport mode using on-demand buses to combine the trips of multiple users into one vehicle. Its required fleet size and carbon emissions are quantified by the system’s efficiency. Due to the complex interplay between street network, buses, users and dispatch algorithm, efficiency case studies are available but bottom-up predictions are not. Here the authors close this gap using probabilistic and geometric arguments in an analytical model framework. Its modular design allows for adaptation to specific usage scenarios and provides an over-arching view of them. In a showcase on Euclidean spaces, the authors' model quantifies how RP outperforms private cars as user demand increases. Its predicted power-law scaling is verified using a custom simulation framework, which further reveals improved scaling on real street networks and graphs with hierarchical structures. Henceforth, the authors' work may help to identify street networks well-suited for RP, and predict key performance indicators analytically.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/27725863
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Supplemental Notes:
- © 2023 The Author. Published by Elsevier Ltd on behalf of Southeast University. Abstract reprinted with permission of Elsevier.
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Authors:
- Mühle, Steffen
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0000-0002-8675-3091
- Publication Date: 2023-6
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References;
- Pagination: 100080
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Serial:
- Multimodal Transportation
- Volume: 2
- Issue Number: 2
- Publisher: Elsevier
- ISSN: 2772-5863
- Serial URL: https://www.sciencedirect.com/journal/multimodal-transportation
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Demand responsive transportation; Fleet management; Performance measurement; Sustainable transportation; Vanpools
- Subject Areas: Passenger Transportation; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01878880
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 10 2023 11:58AM