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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.
Dong et al. (Mon,) studied this question.