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A Priority-Based Autonomous Intersection Management (AIM) Scheme for Connected Automated Vehicles (CAVs)
Hui Zhang (Peking University, State Key Laboratory of Advanced Optical Communication Systems and Networks), Rongqing Zhang (Tongji University), Chen Chen (Peking University, State Key Laboratory of Advanced Optical Communication Systems and Networks), Dongliang Duan (University of Wyoming), Xiang Cheng (Peking University, State Key Laboratory of Advanced Optical Communication Systems and Networks), Liuqing Yang (University of Minnesota)
Abstract: In this paper, we investigate the intersection traffic management for connected automated vehicles (CAVs). In particular, a decentralized autonomous intersection management scheme that takes into account both the traffic efficiency and scheduling flexibility is proposed, which adopts a novel intersection–vehicle model to check conflicts among CAVs in the entire intersection area. In addition, a priority-based collision-avoidance rule is set to improve the performance of traffic efficiency and shorten the delays of emergency CAVs. Moreover, a multi-objective function is designed to obtain the optimal trajectories of CAVs, which considers ride comfort, velocities of CAVs, fuel consumption, and the constraints of safety, velocity, and acceleration. Simulation results demonstrate that our proposed scheme can achieve good performance in terms of traffic efficiency and shortening the delays of emergency CAVs.