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In order to solve the problem of unstable cooperative control caused by unsatisfactory Vehicle-to-Vehicle (V2V) communication environment in the process of vehicle formation lane change, a cooperative control method combining Deep Deterministic Policy Gradient (DDPG) and Model Predictive Control (MPC) is proposed. Firstly, a non-ideal V2V communication model including delay, noise interference and random interruption is constructed based on the wireless channel fading theory. Then, the multi-agent DDPG algorithm is optimized, and a multi-dimensional reward function including communication quality index, lateral tracking deviation and other factors is designed to output the future reference trajectory under collaborative decision-making. Finally, smooth steering angle and acceleration control sequences are generated and executed based on MPC. The simulation results show that compared with the traditional method, the formation spacing error and lateral tracking error of the proposed method are reduced by 59.11% and 48.81% respectively in the communication delay environment. In the scenario of communication interference and interruption, the lane change success rate of this method is increased by 16.73% at most, which can maintain the stability of vehicle formation and realize safe lane change.

, authors=Meiting Hu, Qiang Liu, authorsList=Meiting Hu, Qiang Liu, authorCompany=null, correspAuthors=Qiang Liu, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1309640092734550956, articleId=1309640092050879402, tenantId=1146029695717560320, journalId=1189621681917173762, language=CN, title=非理想通信环境下车辆编队跟驰换道协同控制, columnId=0, journalTitle=汽车技术, columnName=, runingTitle=null, highlight=null, articleAbstract=

为了解决车辆编队换道过程中，因车对车（V2V）通信环境不理想而导致协同控制不稳定的问题，提出一种融合深度确定性策略梯度（DDPG）和模型预测控制（MPC）的协同控制方法。首先，基于无线信道衰落理论构建包含时延、噪声干扰和随机中断的非理想V2V通信模型；随后，优化多智能体DDPG算法，设计包含通信质量指数、横向跟踪偏差等因素的多维奖励函数，输出协同决策下的未来参考轨迹；最后，基于MPC生成并执行平滑的转向角与加速度控制序列。仿真结果表明：相较于传统方法，在通信时延环境下，提出方法的编队间距误差和横向跟踪误差分别降低59.11%、48.81%；在通信干扰和中断场景下，该方法的换道成功率最大提升16.73%，能够维持车辆编队稳定，实现安全换道。

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