The invention discloses a block chain-based cooperative path planning and scheduling method in a cognitive Internet of Vehicles scene, which considers the scene of hybrid driving of a networked automatic driving vehicle and a networked manned vehicle, jointly optimizes the load balance of a vehicle traffic road network and an edge computing node, proposes a block chain-based cooperative framework, and improves the cooperative path planning and scheduling efficiency. Therefore, path planning and scheduling of vehicle cooperation are supported. In addition, a task processing model is established, and influence factors of time delay calculation of the proposed collaboration framework are analyzed. A traffic condition and load distribution model is established on the basis of sensed traffic and network states, a joint optimization problem is modeled, a distributed reinforcement learning algorithm based on Q-Learning is proposed to perform cooperative path planning and scheduling, and active load balance of road infrastructures and mobile edge computing nodes is realized to minimize driving time and computing time delay. According to the invention, different service requirements of different types of vehicles are met, and the calculation complexity is reduced.
本发明公开了一种认知车联网场景下基于区块链的协作路径规划和调度方法,考虑了网联自动驾驶汽车和网联有人驾驶汽车混合驾驶的场景,并联合优化车辆交通道路网络以及边缘计算节点的负载均衡,提出基于区块链的协作框架,以支持车辆协作的路径规划和调度。另外本发明建立了任务处理模型,并分析了所提出的协作框架计算时延的影响因素。基于感知的交通和网络状态建立交通状况和负载分布模型,建模联合优化问题,提出基于Q‑Learning的分布式强化学习算法进行协作路径规划与调度,实现道路基础设施和移动边缘计算节点的主动负载平衡,以最小化行驶时间和计算时延。本发明满足了不同类型车辆的不同服务需求,并降低了计算复杂度。
Cooperative path planning and scheduling method based on block chain in cognitive car networking scene
认知车联网场景下基于区块链的协作路径规划和调度方法
2023-04-28
Patent
Electronic Resource
Chinese
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