Zhao, W orcid.org/0000-0002-5481-8700, Liu, R and Ngoduy, D (2018) A bilevel programming model for autonomous intersection control and trajectory planning. Transportmetrica A: Transport Science. ISSN 2324-9943
Abstract
Advances in autonomous and connected vehicles bring new opportunities for intelligent intersection control strategies. In this paper, we propose a centralised way to jointly integrate an intersection control problem with vehicle trajectory planning. It is formulated as a bilevel optimisation problem in which the upper level is designed to minimise the total travel time by a mixed integer linear programming (MILP) model. In contrast, the lower level is a linear programming (LP) model with an objective function to maximise the total speed entering the intersection. The two levels are coupled by the arrival time and terminal speed. By using the relationship between the safe time headway and the process time, a novel platoon-based method is developed to reduce the computational burden. Finally, simulation tests are carried out to investigate the control performance under different demands, intersection lengths, communication ranges and traffic compositions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Hong Kong Society for Transportation Studies Limited. This is an author produced version of a paper published in Transportmetrica A: Transport Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Autonomous vehicle, intersection control, trajectory planning, bilevel programming |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Jan 2019 12:19 |
Last Modified: | 24 Dec 2019 01:39 |
Status: | Published online |
Publisher: | Taylor and Francis |
Identification Number: | 10.1080/23249935.2018.1563921 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:140880 |