The invention discloses a vehicle cooperative collision avoidance method in automatic driving trajectory planning, and the method comprises the steps: collecting the trajectory data and environment information of a vehicle through a vehicle-mounted sensor, and uploading the trajectory data and environment information to a distributed block chain network for verification and sharing; dynamic environment data are collected and fused through the V2X communication technology, and future tracks of surrounding vehicles are predicted through a deep learning algorithm; based on the vehicle data, the dynamic environment data and the future trajectory prediction data shared by the block chain, trajectory planning and collision avoidance decisions are collaboratively optimized through a multi-agent system, and optimized trajectory planning data are generated; further optimizing the optimized trajectory planning data through quantum computing to generate final optimized trajectory planning data; the high-precision GNSS and the GIS are used for real-time navigation and driving control, actual driving data are fed back to the block chain network, high-precision real-time sensing, accurate track prediction and global optimal track planning are achieved, and the safety and efficiency of an automatic driving system are improved.
本发明公开了自动驾驶轨迹规划中车辆协同避撞方法,通过车载传感器采集车辆的轨迹数据和环境信息,并上传至分布式区块链网络进行验证与共享;通过V2X通信技术采集并融合动态环境数据,利用深度学习算法预测周围车辆的未来轨迹;基于区块链共享的车辆数据、动态环境数据和未来轨迹预测数据,通过多智能体系统协同优化轨迹规划和避撞决策,生成优化的轨迹规划数据;通过量子计算对优化的轨迹规划数据进行进一步优化,生成最终优化的轨迹规划数据;利用高精度GNSS和GIS进行实时导航与行驶控制,并反馈实际行驶数据至区块链网络,本发明实现了高精度的实时感知、精准的轨迹预测和全局最优的轨迹规划,提高了自动驾驶系统的安全性和效率。
Vehicle cooperative collision avoidance method in automatic driving trajectory planning
自动驾驶轨迹规划中车辆协同避撞方法
2024-09-27
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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