The evolutionary interaction between taxi-sharing behaviours and social networks
Mobility services increasingly consider the sharing of vehicles to reduce resource use and congestion. People are, however, reluctant to sharing vehicles with strangers. Therefore, this paper investigates the dynamic co-evolution of taxi-sharing behaviours and the taxi-sharing-oriented social network structure. A social network based taxi-sharing method is introduced that is able to prioritise taxi-sharing with acquaintances over strangers while capping the detour cost to reasonable and varied limits. Furthermore, the social network structure evolves and is updated based on shared trips. An empirical simulation demonstrates the advantages of social network based taxi-sharing, i.e., an increased match rate and a comparable satisfaction level to trip-based methods. The spatial aggregation of the emerging social network not only suggests a space-time searching heuristic for taxi-sharing, but also indicates how social factors conquer space while space constrains social interactions.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
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Supplemental Notes:
- © 2018 Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
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Authors:
- Wang, Yaoli
- Kutadinata, Ronny
- Winter, Stephan
- Publication Date: 2019-1
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 170-180
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Serial:
- Transportation Research Part A: Policy and Practice
- Volume: 119
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0965-8564
- Serial URL: http://www.sciencedirect.com/science/journal/09658564
Subject/Index Terms
- TRT Terms: Intelligent agents; Networks; Simulation; Social factors; Taxicabs; Travel behavior; Vehicle sharing
- Candidate Terms: Social networking
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01687937
- Record Type: Publication
- Files: TRIS
- Created Date: Dec 11 2018 9:22AM