Unsignalized Intersection

Unsignalized intersections pose a significant challenge for autonomous driving due to the inherent complexity and uncertainty of multi-agent interactions. Current research heavily focuses on developing robust decision-making frameworks for autonomous vehicles (AVs) navigating these intersections, employing reinforcement learning (RL) algorithms, often coupled with game theory or attention mechanisms, to optimize for safety and efficiency in mixed human-AV traffic. These efforts aim to improve traffic flow, reduce emissions, and enhance overall road safety, impacting both the development of autonomous driving technology and the design of future transportation systems. The ultimate goal is to create AVs that can safely and efficiently interact with human drivers in these challenging environments.