@article{Dong2025, 
author = {Jianghong Dong and Jiawei Wang and Mengchi Cai and Yibin Yang and Qing Xu and Jianqiang Wang and Keqiang Li},
title = {STFC: Spatio-temporal formation control for connected and autonomous vehicles in multi-lane traffic},
year = {2025},
journal = {Communications in Transportation Research},
volume = {5},
number = {4},
pages = {100219},
keywords = {Multi-vehicle coordination, Formation control, Spatio-temporal joint optimization, Multi-lane traffic},
url = {https://www.sciopen.com/article/10.1016/j.commtr.2025.100219},
doi = {10.1016/j.commtr.2025.100219},
abstract = {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.}
}