Intelligent Driving

Intelligent driving research aims to develop systems capable of safe and efficient autonomous navigation, focusing on robust perception, decision-making, and control in complex environments. Current efforts concentrate on improving object detection and trajectory prediction accuracy using deep learning models like attention-based LSTMs and mixtures of experts, alongside developing more interpretable and reliable algorithms through techniques such as entropy loss and counterfactual reasoning. This field is crucial for enhancing road safety, optimizing traffic flow, and creating more human-centered driving experiences, impacting both the transportation sector and the broader AI community.