Driving Scenario

Driving scenario research focuses on accurately predicting and responding to complex traffic situations for safer and more efficient autonomous vehicles. Current efforts concentrate on developing data-efficient models, often employing deep learning architectures like transformers and hypergraph neural networks, to predict vehicle trajectories and driver behavior, while also addressing challenges like data scarcity in critical scenarios and the need for robust real-time performance. This research is crucial for improving the safety and reliability of autonomous driving systems, impacting both the development of advanced driver-assistance systems and the broader field of robotics and AI.