高技术通讯2026，Vol.36Issue(1)：89-100,12.DOI:10.3772/j.issn.1002-0470.2026.01.008
基于A3C算法的无人车智能博弈估计与控制
Intelligent game estimation and control of unmanned vehicles based on A3C algorithm
摘要
Abstract
Vehicular traffic systems have complex road conditions and frequent network disturbances.The traditional model predictive control(MPC)method degrades its control performance due to the influence of disturbances.To solve this problem,a three-degree-of-freedom kinematic model of the vehicle is firstly established.The model pre-dictive control algorithm is proposed to achieve trajectory tracking under the ideal state.Secondly,considering the influence of external interference on trajectory tracking accuracy,a game model based on attack and defence con-frontation is constructed.That is,the game relationship between network interference and vehicle defence system is established through the idea of attack and defence.Stackelberg's equilibrium solution is solved by asynchronous advantage actor-critic(A3 C)algorithm.Due to the possible loss of measurement information under complex network interference,a Kalman filter based on attack and defence information is designed to achieve the state estimation of the vehicle.On the basis of obtaining the state estimation,the trajectory tracking of the unmanned vehicle under complex disturbance interference is achieved by using the MPC method.Finally,the effectiveness of the proposed method is verified by simulation.关键词
干扰/卡尔曼滤波器/斯塔克尔伯格博弈论/模型预测控制/强化学习Key words
jamming/Kalman filters/Stackelberg game/model predictive control/reinforcement learning引用本文复制引用
刘青林,叶泽华,张丹..基于A3C算法的无人车智能博弈估计与控制[J].高技术通讯,2026,36(1):89-100,12.基金项目
国家自然科学基金(61873237,62322315,62503420)和浙江省自然科学基金(LR22F030003,LMS25F030006)资助项目. （61873237,62322315,62503420）
