Interactive Driving

Interactive driving research focuses on enabling safe and efficient interaction between autonomous vehicles (AVs) and human drivers, aiming to improve the safety and efficiency of mixed traffic scenarios. Current research heavily utilizes deep reinforcement learning, graph neural networks, and model predictive control, often incorporating trajectory prediction models and risk assessment frameworks to account for the uncertainty and diverse behaviors of human drivers. These advancements are crucial for developing reliable and trustworthy AV systems, contributing significantly to the safety and efficiency of future transportation systems.