Optimal Driving

Optimal driving research aims to develop autonomous driving systems that are not only safe but also efficient, comfortable, and compliant with regulations. Current efforts focus on developing robust models, often employing reinforcement learning and hidden Markov models, to learn optimal driving behaviors from diverse data sources, including sensor inputs and naturalistic driving data. These models are evaluated using comprehensive frameworks that assess various aspects of driving performance beyond collision avoidance, such as adherence to traffic laws and efficient trajectory planning. This research is crucial for advancing the safety and reliability of autonomous vehicles and informing the development of effective regulatory frameworks.