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- Publisher Website: 10.1109/TITS.2019.2920674
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Article: Dynamic Lane Reversal Routing and Scheduling for Connected and Autonomous Vehicles: Formulation and Distributed Algorithm
Title | Dynamic Lane Reversal Routing and Scheduling for Connected and Autonomous Vehicles: Formulation and Distributed Algorithm |
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Authors | |
Keywords | Roads Routing Dynamic scheduling Vehicle dynamics Autonomous vehicles |
Issue Date | 2020 |
Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979 |
Citation | IEEE Transactions on Intelligent Transportation Systems, 2020, v. 21 n. 6, p. 2557-2570 How to Cite? |
Abstract | An effective intelligent transportation system is a core part of modern smart city. The Internet of Things and vehicular communication technologies facilitate rapid development of connected and autonomous vehicles (CAVs). While most studies focus on standalone CAV technologies, collective CAV control has much potential. With the connectivity and automation of CAVs, we can employ dynamic lane reversal (DLR) to optimize the travel schedules of CAVs for performance enhancement. In this paper, we propose the dynamic lane reversal-traffic scheduling management (DLR-TSM) scheme for CAVs. The system collects the travel requests from CAVs and determines their optimal schedules and routes over dynamically reversible lanes. We formulate the routing and scheduling problem on DLR as an integer linear program. To address the scaling effect, an algorithm based on alternating direction method of multipliers is designed to solve the problem in a distributed manner. We extensively evaluate the DLR-TSM and the distributed algorithm with real-world transportation data. The simulation results show that the DLR-TSM can significantly improve the travel times of CAVs and the distributed algorithm can dramatically reduce the required computational time. |
Persistent Identifier | http://hdl.handle.net/10722/288071 |
ISSN | 2023 Impact Factor: 7.9 2023 SCImago Journal Rankings: 2.580 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | CHU, KF | - |
dc.contributor.author | Lam, AYS | - |
dc.contributor.author | Li, VOK | - |
dc.date.accessioned | 2020-10-05T12:07:27Z | - |
dc.date.available | 2020-10-05T12:07:27Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | IEEE Transactions on Intelligent Transportation Systems, 2020, v. 21 n. 6, p. 2557-2570 | - |
dc.identifier.issn | 1524-9050 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288071 | - |
dc.description.abstract | An effective intelligent transportation system is a core part of modern smart city. The Internet of Things and vehicular communication technologies facilitate rapid development of connected and autonomous vehicles (CAVs). While most studies focus on standalone CAV technologies, collective CAV control has much potential. With the connectivity and automation of CAVs, we can employ dynamic lane reversal (DLR) to optimize the travel schedules of CAVs for performance enhancement. In this paper, we propose the dynamic lane reversal-traffic scheduling management (DLR-TSM) scheme for CAVs. The system collects the travel requests from CAVs and determines their optimal schedules and routes over dynamically reversible lanes. We formulate the routing and scheduling problem on DLR as an integer linear program. To address the scaling effect, an algorithm based on alternating direction method of multipliers is designed to solve the problem in a distributed manner. We extensively evaluate the DLR-TSM and the distributed algorithm with real-world transportation data. The simulation results show that the DLR-TSM can significantly improve the travel times of CAVs and the distributed algorithm can dramatically reduce the required computational time. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979 | - |
dc.relation.ispartof | IEEE Transactions on Intelligent Transportation Systems | - |
dc.rights | IEEE Transactions on Intelligent Transportation Systems. Copyright © Institute of Electrical and Electronics Engineers. | - |
dc.rights | ©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Roads | - |
dc.subject | Routing | - |
dc.subject | Dynamic scheduling | - |
dc.subject | Vehicle dynamics | - |
dc.subject | Autonomous vehicles | - |
dc.title | Dynamic Lane Reversal Routing and Scheduling for Connected and Autonomous Vehicles: Formulation and Distributed Algorithm | - |
dc.type | Article | - |
dc.identifier.email | Lam, AYS: ayslam@eee.hku.hk | - |
dc.identifier.email | Li, VOK: vli@eee.hku.hk | - |
dc.identifier.authority | Lam, AYS=rp02083 | - |
dc.identifier.authority | Li, VOK=rp00150 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TITS.2019.2920674 | - |
dc.identifier.scopus | eid_2-s2.0-85085945626 | - |
dc.identifier.hkuros | 315121 | - |
dc.identifier.volume | 21 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 2557 | - |
dc.identifier.epage | 2570 | - |
dc.identifier.isi | WOS:000545427200028 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1524-9050 | - |