Optimal design of autonomous vehicle zones in transportation networks
This paper advocates the need for infrastructure planning to adapt to and further promote the deployment of autonomous vehicle (AV) technology. It is envisioned that in the future government agencies will dedicate certain areas of road networks to AVs only to facilitate the formulation of vehicle platoons to improve throughput and hopefully improve the performance of the whole network. This paper aims to present a mathematical framework for the optimal design of AV zones in a general network. With the presence of AV zones, AVs may apply different routing principles outside of and within the AV zones. A novel network equilibrium model (the authors refer to it as the “mixed routing equilibrium model”) is thus firstly proposed to capture such mixed-routing behaviors. The authors then proceed to formulate a mixed-integer bi-level programming model to optimize the deployment plan of AV zones. Numerical examples are presented to demonstrate the performance of the proposed models.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
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Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
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Authors:
- Chen, Zhibin
- He, Fang
- Yin, Yafeng
- Du, Yuchuan
- Publication Date: 2017-5
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: pp 44-61
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Serial:
- Transportation Research Part B: Methodological
- Volume: 99
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0191-2615
- Serial URL: http://www.sciencedirect.com/science/journal/01912615
Subject/Index Terms
- TRT Terms: Design; Equilibrium (Systems); Intelligent vehicles; Mathematical models; Mixed integer programming; Networks; Optimization
- Uncontrolled Terms: Bilevel programming; Restricted zones
- Subject Areas: Data and Information Technology; Design; Highways; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01635655
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 25 2017 5:00PM