Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse

doi:10.1109/TSMC.2022.3225250

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进控制与自动化团队

	Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse
	Li, Bai 6,7; Cao, Dongpu 5; Tang, Shiqi 6; Zhang, Tantan 6; Dong, Hairong 4; Wang, Yaonan 2,3; Wang, Fei-Yue 1
刊名	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
	2022-12-13
页码	12
关键词	Autonomous intersection management (AIM) cyber-physical-social intelligence metaverse numerical optimal control
ISSN号	2168-2216
DOI	10.1109/TSMC.2022.3225250
通讯作者	Cao, Dongpu(dongpu.cao@uwaterloo.ca)
英文摘要	Replacing traffic signals with roadside vehicle-to-infrastructure systems in the era of connected and autonomous vehicles (CAVs) is promising. Managing CAVs in a signal-free intersection, known as autonomous intersection management (AIM), controls the driving behavior of each intersection-traverse CAV to maximize the throughput. Although AIM improves the gross throughput, the fairness of each individual vehicle in its right of way is not seriously considered. This study sets up an AIM system in the cyber-physical-social space to trade traverse priorities quantitatively and fairly. To that end, one needs an AIM method that is optimal and stable, otherwise no convincing trades of traverse priorities could be made. This study proposes a near-optimal lane-free AIM method based on numerical optimal control, wherein log-exp functions are deployed to convexify nondifferentiable collision-avoidance constraints. Besides that, a parameterized social force model (SFM) is proposed to provide a tunable initial guess for numerical optimal control. By tuning the urgency weights in SFM, one may get cooperative trajectories in different homotopy classes, which are further utilized to decide the amount of virtual currency to reward those CAVs who tend to share their traverse priorities. The overall method improves the traverse throughput with individual fairness respected. In experiencing this system, passengers learn how to behave with politeness when they drive manually. Experiments show the efficiency and robustness of the AIM method and also show the efficacy of the overall priority-sharing system.
资助项目	Fundamental Research Funds for the Central Universities[531118010509] ; National Natural Science Foundation of China[62103139] ; Natural Science Foundation of Hunan Province, Chin[2021JJ40114] ; 2022 Opening Foundation of State Key Laboratory of Management and Control for Complex Systems[E2S9021119]
WOS关键词	SIGNAL-FREE ; AUTOMATED VEHICLES ; SYSTEMS ; IMPLEMENTATION ; FORMULATION ; CONGESTION ; STRATEGIES ; CONSENSUS
WOS研究方向	Automation & Control Systems ; Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000899976200001
资助机构	Fundamental Research Funds for the Central Universities ; National Natural Science Foundation of China ; Natural Science Foundation of Hunan Province, Chin ; 2022 Opening Foundation of State Key Laboratory of Management and Control for Complex Systems
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50994]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者	Cao, Dongpu
作者单位	1.Chinese Acad Sci, Inst Automation, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Hunan Univ, Natl Engn Lab Robot Visual Percept & Control, Changsha 410082, Peoples R China 3.Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China 4.Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China 5.Tsinghua Univ, Sch Vehicle & Mobil, Beijing 100084, Peoples R China 6.Hunan Univ, Coll Mech & Vehicle Engn, Changsha 410082, Peoples R China 7.Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Peoples R China
推荐引用方式 GB/T 7714	Li, Bai,Cao, Dongpu,Tang, Shiqi,et al. Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2022:12.
APA	Li, Bai.,Cao, Dongpu.,Tang, Shiqi.,Zhang, Tantan.,Dong, Hairong.,...&Wang, Fei-Yue.(2022).Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,12.
MLA	Li, Bai,et al."Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2022):12.