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An Adaptive Control Framework for Mixed Autonomy Traffic Platoon
Tang, Ruru1; Li, Zhenning1; Xu, Chengzhong2
2024-01-24
Source PublicationArabian Journal for Science and Engineering
ISSN2193-567X
Abstract

As autonomous vehicles (AVs) and human-driven vehicles (HVs) are expected to share the road for the foreseeable future, understanding how to improve the stability of mixed-autonomy platoons is crucial. This paper introduces a novel adaptive control strategy tailored for a specific platoon configuration termed as “ 1 + n+ 1 ”, consisting of a leading AV, n intervening vehicles, and a trailing AV. Utilizing vehicle-to-vehicle communication, the trailing AV adapts to real-time traffic states, thereby promoting overall platoon stability. Our analysis, grounded in Lyapunov theory, demonstrates that stabilizing only the trailing vehicle is sufficient to ensure the entire system reaches a stable state. To mitigate the negative effects of sensor and actuator uncertainties, we also introduce a corrective signal framework capable of nullifying adverse inputs. Numerical experiments validate the effectiveness of the proposed strategy in platoon control, which can also be adapted to other platoon configurations. Additionally, the performance of this strategy on macroscopic traffic flow is explored, suggesting substantial potential throughput increases compared with the benchmark strategy of Cooperative Adaptive Cruise Control (CACC).

KeywordAdaptive Control Autonomous Vehicle Mixed Autonomy Traffic Platoon
DOI10.1007/s13369-023-08625-8
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:001149176400003
PublisherSPRINGER HEIDELBERG, TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
Scopus ID2-s2.0-85183013824
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Document TypeJournal article
CollectionDEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Faculty of Science and Technology
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
INSTITUTE OF COLLABORATIVE INNOVATION
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorTang, Ruru; Li, Zhenning; Xu, Chengzhong
Affiliation1.State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Taipa, SAR, 999078, Macao
2.State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science, University of Macau, Taipa, SAR, 999078, Macao
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Tang, Ruru,Li, Zhenning,Xu, Chengzhong. An Adaptive Control Framework for Mixed Autonomy Traffic Platoon[J]. Arabian Journal for Science and Engineering, 2024.
APA Tang, Ruru., Li, Zhenning., & Xu, Chengzhong (2024). An Adaptive Control Framework for Mixed Autonomy Traffic Platoon. Arabian Journal for Science and Engineering.
MLA Tang, Ruru,et al."An Adaptive Control Framework for Mixed Autonomy Traffic Platoon".Arabian Journal for Science and Engineering (2024).
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