Formation control of Connected and Autonomous Vehicles (CAVs) has shown significant potential for improving traffic safety and efficiency in multi-lane traffic. However, previous work has primarily focused on spatial coordination while neglecting temporal optimization, which significantly limits their cooperation capability and practical applicability in real-world traffic. In this study, we propose a Spatio-Temporal Formation Control (STFC) method that integrates centralized formation generation with distributed trajectory planning. Precisely, we propose a graph-based formation maintenance representation, and show that the interlaced geometric structure is optimal for multi-lane formation. Then, we develop a distributed spatio-temporal joint formation trajectory planning method that simultaneously optimizes spatial positions and temporal duration, with consideration of multiple objectives such as formation maintenance and obstacle avoidance. Further, we design a polynomial vehicle-to-target assignment algorithm that inherently resolves conflicts. Simulation experiments demonstrate the superiority of our method over baselines in terms of formation maintenance and transition, achieving a 53% and 58% reduction in transition time and distance, respectively.

The rapid development of intelligent and connected vehicles (ICV) in recent years promotes theoretical research in related fields from driving assistance to automated driving, from single-vehicle intelligent driving to multi-vehicle cooperative driving.ICV systems are expected to improve traffic safety and efficiency, but they face complex challenges in real traffic environment. This paper presents a survey of ICV technologies relating to 3 aspects: system architecture design, functional technology and application. This survey first introduces typical architectures of ICV, and then the development and challenges of three key functional technologies: perception, decision making and control, in consideration of driver-vehicle-road interactions in real traffic environment. Finally, this paper analyzes ICV applications in typical scenarios and the future development of related technologies.