The invention discloses an intelligent network connection vehicle non-signal-control intersection passing optimization method based on a coupling algorithm, and the acceleration of a vehicle is adjusted and controlled based on a mode of coupling a deep reinforcement learning algorithm and a microscopic traffic flow model. Constructing a maximum acceleration passing strategy, a minimum acceleration passing strategy and a dynamic adjustment acceleration passing strategy; and selecting a corresponding passing strategy according to the actual scene to control the intelligent network connection vehicle to pass at the signal-control-free intersection. The traffic efficiency can be effectively improved and the safety can be considered in a complex traffic scene without a signal control intersection.
本发明公开了一种基于耦合算法的智能网联车辆无信控交叉口通行优化方法,基于耦合深度强化学习算法和微观交通流模型的方式对车辆的加速度进行调整控制,并以此构建最大加速度通行策略、最小加速度通行策略和动态调整加速度通行策略;根据实际场景选择相应的通行策略控制智能网联车辆在无信控交叉口通行。本发明在无信控交叉口的复杂交通场景,不仅可以有效提升通行效率,还可以兼顾安全性。
Intelligent network connection vehicle no-signal-control intersection passing optimization method based on coupling algorithm
基于耦合算法的智能网联车辆无信控交叉口通行优化方法
2025-01-24
Patent
Electronic Resource
Chinese
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