2018
DOI: 10.1109/tits.2017.2735628
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Cooperative Intersection Control Based on Virtual Platooning

Abstract: DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal… Show more

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Cited by 103 publications
(23 citation statements)
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“…7 [99]. Medina et al further developed an automated intersection system for CAVs using a similar approach, which consists of a bi-level architecture: a supervisory level with subsystems target vehicle assignment and control reconfiguration; and an execution level with cooperative vehicle motion control design [100]. Xu et al also adopted the virtual platoon methodology to project vehicles approaching from different directions of an intersection into a virtual lane [101].…”
Section: ) Theoretical Research and Simulationmentioning
confidence: 99%
“…7 [99]. Medina et al further developed an automated intersection system for CAVs using a similar approach, which consists of a bi-level architecture: a supervisory level with subsystems target vehicle assignment and control reconfiguration; and an execution level with cooperative vehicle motion control design [100]. Xu et al also adopted the virtual platoon methodology to project vehicles approaching from different directions of an intersection into a virtual lane [101].…”
Section: ) Theoretical Research and Simulationmentioning
confidence: 99%
“…The former focuses on scheduling space tiles and time slots requested by vehicles intending to cross the intersection. In contrast, the latter focuses on the relative motion between vehicles to determine a safe crossing sequence [103].…”
Section: On the Roadmentioning
confidence: 99%
“…If the intent of all vehicles is known, the global solution is known to be NP-hard and quickly becomes intractable with large numbers of vehicles. Thus, many approaches look to find locally-optimal solutions, using control policies that guarantee safe passage [2], [3], [4], [5], [6], game theoretic approaches [7], learning-based control methods [8], [9], and decentralized algorithms [10], [11]. In this paper, we use a central coordinator to manage human and autonomous vehicles using intersection reservations.…”
Section: A Related Workmentioning
confidence: 99%