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Dynamic shared autonomous taxi system considering on-time arrival reliability
Abstract
Abstract Dynamic shared autonomous taxi (SAT) systems are regarded as a promising means of improving travel flexibility. With no human drivers, SATs urgently require precise traffic information in order to plan accurate paths independently; in addition, on-time arrival is an essential service quality in SAT systems. In this study, taxis are assumed to be replaced with ride-sharing autonomous vehicles. To improve the probability of on-time arrival, the reliable path concept and collected travel time information are used to facilitate path finding for SATs, and the potential benefits are examined. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—are executed to evaluate the information’s usefulness in reliable path finding. In simulation results, reliable path scenarios showed a higher on-time arrival ratio than shortest path scenarios, in which the shortest path algorithm is used in path finding for SATs, and the historical information-based scenarios showed a higher on-time arrival ratio than the real-time information-based scenarios. A system-beneficial path finding method is proposed and is verified to be effective for mitigating road network congestion.
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In the citing paper
“Similarly, historical traffic information based scenario results in a higher on-time arrival ratio than real-time traffic information based scenario.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Liu et al. (2019)
In the citing paper
“Results from the study shows that the reliable path algorithm results in a higher on-time arrival ratio than the shortest path algorithm.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Liu et al. (2019)
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Cited by
Shared autonomous vehicle services: A comprehensive review
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Metadata
- Authors
- Liu, Z., Miwa, T., Zeng, W., Bell, M. G. H., & Morikawa, T.
- Affiliations
- Nagoya University (JP)
- Institute of Materials and Systems for Sustainability, Nagoya University (JP)
- Guangdong University of Technology (CN)
- The University of Sydney (AU)
- Institutes of Innovation for Future Society, Nagoya University (JP)
- Corresponding author
- Liu, Zhiguang
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 103
- Pages
- 281-297
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2941854170
- Cited by
- 48
- References
- 60
- Citations by year
- 2026: 5 · 2025: 1 · 2024: 5 · 2023: 11 · 2022: 5 · 2021: 13 · 2020: 6 · 2019: 2
- FWCI
- 2.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Locations
- Transportation Research Part C Emerging Technologies (publishedVersion)
- Funders
- JSPS KAKENHI (16H02367, 16K12825)
- National Natural Science Foundation of China (61803100)
- China Scholarship Council
- Topics
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- autonomous vehicles, ride-sharing, travel time information, real-time traffic information, shortest path, road network congestion, path planning
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