脆弱感知下队列车辆控制与通信深度融合的协同巡航机制研究

Platoon-based Cooperative Adaptive Cruise Control (CACC) holds great potential for improving the road safety and alleviating traffic congestion. In general, with the characteristics of vulnerable perceptual capability and unidirectional strong coupling among platoon-based vehicles, the relatively low fusion level between the platoon-based vehicular control and communication is the bottleneck for realizing CACC’s advantages. Guided by the inter-vehicle vulnerability perception capability, this paper will explore the cooperative cruise mechanism with deep fusion between inter-vehicular control and communication. The project mainly researches the following elements: (1) From the string stability standpoint, the coupling mechanism between cruise platoon and communication environment will be revealed, and served as quantifying the capability of inter-vehicular vulnerability perception; (2) Focus on the contradiction between the cruise control requirements for high adaptability and strong robustness and the platoon-based vehicular capabilities of vulnerable perception and low level collaboration, the deep integration mechanism between inter-vehicular control and communication will be established based on the platoon-based vehicular cruise behavior decision in the physical plane; thus the inter-vehicular vulnerability perception will be compensated and the communication environment will be optimized; (3) Focus on the contradiction between the cruise control requirements for high frequency information interaction and ultra-short period and the high density communication node in platoon, the deep integration mechanism inter-vehicular control and communication will be established based on the design of beacon broadcast mechanism in the cyber plane; thus the inter-vehicle vulnerability perception capability can be improved; (4) The simulation environment and semi-physical experimental platform will be constructed to validate the feasibility and effectiveness of the proposed theories and techniques. This project aims to provide an important theoretical basis and a key technical support foundation for the further advancement and application of the CACC systems.

队列车辆协同自适应巡航系统（CACC）对提高驾驶安全、缓解交通拥堵意义重大。时变通信环境下队列车间往往呈现感知脆弱、单向强耦合等特性，巡航控制与车间通信的低效协同严重制约了CACC潜能的发挥。项目以应对-改善车间脆弱感知能力为导向，研究巡航控制与通信深度融合的协同巡航机制：①揭示队列稳定性约束下巡航控制与通信之间的耦合机理，为量化评估车间感知能力、探寻巡航控制与通信融合途径提供理论依据；②物理域内基于协同巡航行为决策建立巡航控制与通信深度融合机制，有效应对车间脆弱感知并局部优化通信环境，解决巡航控制高适用、强鲁棒性需求与车间感知脆弱、低效协作间的矛盾；③网络域内基于协作通信协议设计建立巡航控制与通信深度融合机制，提升车间彼此感知的可靠性，解决巡航控制高频信息交互、超短控制周期需求与队列高密度节点通信间的矛盾；④搭建仿真环境验证协同巡航机制的有效性。为提升CACC整体性能提供理论和技术支撑。

队列车辆协同自适应巡航系统（Cooperative Adaptive Cruise Control, CACC）是智能网联汽车的核心功能之一，是自动驾驶和车联网通信技术的结合体。本项目从物理域和网络域不同角度出发，研究了队列车辆控制与通信深度融合的协同自适应巡航机制，并构建了相应控制策略和优化算法。物理域内，建立了基于车间通信质量的分布式CACC控制策略：基于Lyapunov函数和线性矩阵不等式获取得到确保队列稳定的通信时延上界，建立了模糊系统描述纵向队列被控车辆与其他车辆之间关联有效性关系，根据行驶状态变化设计了CACC模糊PID控制策略。网络域内，建立了高可靠性、低时延和丢包率的分布式车联网MAC层通信协议：针对非均衡交通流场景下固定划分时隙导致时隙资源耗尽或时隙浪费问题，基于合并碰撞预测改进了MAC层通信协议，设计了自适应时隙接入MAC层通信协议。本项目扩展研究了多时间尺度下面向动态交通路网的车流量深度学习预测模型，可为分布式CACC控制和车间通信协议优化提供环境预测感知信息。基于所取得相关成果，在国内外期刊和学术会议上公开发表学术论文13篇，申请发明专利4项，丰富了CACC在车辆控制与车间通信之间协同的基本理论和研究方法。