车、路、云一体化共融是车联网（智能网联汽车）发展必然方向，其对象不再是传统交通工具，而是集散化、分布式的智能终端群。随着自动驾驶控制需求的提高以及多车智能协同的开展，出现了车用信息分配效率有限、诱导决策功能单一、集散控制协同度低等问题。因此，本项目围绕大数据形态下“云+端”理念，重点面向协同服务，以实现网联车辆群组车用信息高效有序分配切换，研究具有高度协同能力的车辆与道路系统为目标，考虑动态多变的交通环境，构建基于“松耦合+软总线”的车用信息服务协同架构模型，设计结合场强和密度分布的车用共享信息功率调控方法，阐明适宜于高度协同驾驶的动态集散决策机理，提出网联车群协同驾驶分布式混成控制方法。研究结果将对具备高级别自动驾驶功能的群体智能网联汽车在特定场景下的规模应用奠定理论方法基础。

The integration of vehicle, road, and cloud is the inevitable development direction for intelligent connected vehicles. It is no longer a traditional vehicle, but a distributed smart terminal group. With the increase in the demand for autonomous driving control and the development of multi-vehicle intelligent collaboration, such problems as limited information distribution efficiency of vehicle networking systems, single information function for inducing decision-making, and low degree of distributed control coordination have emerged. Therefore, based on the “cloud plus end” concept in the form of big data, this research focuses on collaborative services in order to achieve efficient and orderly allocation and switching of vehicle information for intelligent connected vehicle groups. Vehicles and roads with high collaborative capabilities are studied, and a cooperative architecture model of vehicle information services based on “loose coupling plus soft bus” is constructed due to the dynamically changing traffic environment. A method for regulating and controlling the power of vehicle shared information based on field strength and density distribution. Besides, the research clarifies a method of dynamic distributed decision-making which is suitable for highly collaborative driving and proposes a distributed hybrid control method for the cooperative driving of connected vehicle groups. The research results will lay the theoretical foundation for the large-scale application of intelligent connected vehicle groups with high-level autonomous driving functions in specific scenarios.