控制(管理)
业务
环境科学
航空学
计算机科学
工程类
人工智能
作者
Yi Ran,Yifan Yao,Pu Fan,Yang Zhou,Xin Wang
标识
DOI:10.1016/j.commtr.2024.100126
摘要
This paper presents a spatially formulated cooperative dynamic mandatory connected automated vehicle (CAV) lane-changing and car-following approach on curved highways with the assistance of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. This work proposes mandatory lane-changing control in a spatial domain to accomplish car-following and lane-changing efficiency in a systematic manner. This control technique initially creates a virtual CAV car-following lane by assigning CAVs sequential numbers based on their spatial position. On this basis, a multi-objective model predictive control (MPC) strategy in the spatial domain is designed to optimize the trajectories in a rolling horizon fashion in order to maintain the inter-vehicle spacing and speed difference while simultaneously satisfying collision avoidances, traffic regulations, and vehicle kinematics constraints. Multi-scenario numerical simulations are conducted to validate the control efficacy of our technique.
科研通智能强力驱动
Strongly Powered by AbleSci AI