网联汽车群体智能协同网络通信的决策理论和方法

With the rapid development of automobile manufacturing and mobile communication technologies, the Internet-connected connected vehicles show new features such as a huge quantity of data, intelligence of communication, and diversification of user's needs, with a result that the information sensing, resource sharing and content distribution become new issue in the reality and reliability. To address these problems, this application studies the intelligent cooperative decision-making theory of network communications for Internet-connected connected vehicles based on vehicles’ network architecture and communication demands. Firstly, the extensible network architecture and communication model is designed to provide the theoretical foundation. Secondly, with the game theory, operational research and optimization mathematical tools, this application studies the collaborative information sensing based on the cooperation game, the collaborative task allocation strategy based on the dynamic programming, and the collaborative content caching strategy based on the edge computing, respectively. The specific objectives and results are to study the new features and requirements in the current networks and the rational allocation of the network resources. The proposal improves the accuracy of information perception, the efficiency of task allocation and content caching, the performance of the network systems and the user quality of experience. Moreover, the new theory presented in the application establishes the theoretical foundation for the intelligent collaborative decision making theory of network communications for Internet-connected connected vehicles.

随着汽车制造和网络通信技术的快速发展和广泛应用，网联汽车呈现出数据海量化、通信智能化和用户需求多样化等新特征，使得传统网络通信架构无法满足网联汽车对信息感知、资源共享和内容分发的实时性和可靠性等新需求。为了克服上述问题，本项目基于网联汽车的网络架构特征和通信性能需求，研究网联汽车群体智能协同网络通信的决策理论和方法。首先，建立可扩展的网络体系架构和通信模型，为智能协同网络通信决策的研究奠定基础。其次，利用博弈论、运筹学、优化算法等数学工具，分别研究基于博弈合作的协同信息感知策略、基于动态规划的协同任务分配策略、基于边缘计算的协同内容缓存策略。通过充分挖掘通信需求特性和网络群体特征，合理分配网络资源，以达到提高信息感知精度、任务分配效果和内容分发效率，提升网络性能和驾驶用户体验的目的。本项目的开展可为基于下一代网络通信架构的网联汽车群体智能协同网络通信的决策理论和方法研究提供指导与技术支撑。

本项目基于网联汽车的网络架构特征和通信性能需求，研究了网联汽车群体智能协同网络通信的决策理论和方法。首先，建立了可扩展的网络体系架构和通信模型，为智能协同网络通信决策的研究奠定基础。其次，利用博弈论、运筹学、优化算法等数学工具，分别研究基于博弈合作的协同信息感知策略、基于动态规划的协同任务分配策略、基于边缘计算的协同内容缓存策略。攻克了网联汽车群体智能协同的可扩展网络通信相关技术瓶颈，为网联汽车安全可靠、高效运行提供了理论方法支撑。相关成果实现了转化，大幅提高了网联汽车性能。

内容获取失败，请点击重试