The invention discloses an intersection entrance lane manual driving and automatic driving hybrid fleet queuing configuration optimization method. The method comprises the following steps: S1, constructing an SAC model overall framework; s2, designing an intelligent agent, and setting a state S (t), an action A (t) and a reward R (t); s3, urban traffic simulation software SUMO is utilized to construct an analogue simulation environment, automatic driving vehicles in simulation adopt a CACC model to simulate vehicle following behaviors, and manual driving vehicles adopt a Krauss following model to simulate behavior characteristics; and S4, training the SAC model, and outputting an optimized Actor network for adjusting the queuing configuration of the hybrid motorcade in an actual guidance embodiment after a training stopping condition is reached. The method can effectively improve the traffic efficiency and stability of the hybrid motorcade passing through the intersection, and is suitable for optimal control of a dynamic hybrid traffic environment.
本发明公开了一种交叉口进口道人工驾驶与自动驾驶混合车队排队构型优化方法,包括步骤如下:S1,构建SAC模型整体框架;S2,设计智能体,对状态S(t)、动作A(t)和奖励R(t)进行设置;S3,利用城市交通仿真软件SUMO构建仿真模拟环境,仿真中的自动驾驶车辆均采用CACC模型模拟车辆跟驰行为,人工驾驶车辆均采用Krauss跟驰模型模拟其行为特征;S4,对SAC模型进行训练,达到停止训练条件后,输出优化后的Actor网络,用于实际指导实施例中的混合车队排队构型调整。本发明能有效提升混合车队通过交叉口的通行效率和稳定性,适用于动态混合交通环境的优化控制。
Intersection entrance lane manual driving and automatic driving hybrid fleet queuing configuration optimization method
一种交叉口进口道人工驾驶与自动驾驶混合车队排队构型优化方法
23.05.2025
Patent
Elektronische Ressource
Chinesisch
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