Mixed Traffic

Mixed traffic research focuses on improving the safety and efficiency of road systems where autonomous vehicles (AVs) and human-driven vehicles (HVs) coexist. Current research emphasizes developing robust control strategies for AVs navigating unpredictable HV behavior, often employing reinforcement learning (RL) algorithms, physics-enhanced models, and multi-agent pathfinding techniques to optimize trajectory planning and conflict resolution. This field is crucial for the safe and efficient integration of AVs into existing infrastructure, impacting both the design of autonomous driving systems and the development of intelligent transportation systems.