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

doi:10.1109/TSMC.2022.3225250

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse
	Li, Bai 1,2; Cao, Dongpu 3; Tang, Shiqi 2; Zhang, Tantan 2; Dong, Hairong 4; Wang, Yaonan 5,6; Wang, Fei-Yue7
发表期刊	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
ISSN	2168-2216
	2022-12-13
页码	12
通讯作者	Cao, Dongpu(dongpu.cao@uwaterloo.ca)
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.
关键词	Autonomous intersection management (AIM) cyber-physical-social intelligence metaverse numerical optimal control
DOI	10.1109/TSMC.2022.3225250
关键词[WOS]	SIGNAL-FREE ; AUTOMATED VEHICLES ; SYSTEMS ; IMPLEMENTATION ; FORMULATION ; CONGESTION ; STRATEGIES ; CONSENSUS
收录类别	SCI
语种	英语
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]
项目资助者	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
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Cybernetics
WOS记录号	WOS:000899976200001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50995
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Cao, Dongpu
作者单位	1.Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Peoples R China 2.Hunan Univ, Coll Mech & Vehicle Engn, Changsha 410082, Peoples R China 3.Tsinghua Univ, Sch Vehicle & Mobil, Beijing 100084, Peoples R China 4.Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China 5.Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China 6.Hunan Univ, Natl Engn Lab Robot Visual Percept & Control, Changsha 410082, Peoples R China 7.Chinese Acad Sci, Inst Automation, State Key Lab Management & Control Complex Syst, Beijing 100190, 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.