Risk Field

Risk fields are mathematical representations of the potential danger in a given environment, primarily used in autonomous driving research to model and predict the risk associated with various driving maneuvers. Current research focuses on integrating risk field models with trajectory prediction algorithms, often employing deep learning and model predictive control, to enable safer and more efficient autonomous navigation, particularly in complex scenarios involving occlusions and multiple interacting agents. This work aims to improve the safety and reliability of autonomous vehicles by providing a quantitative framework for assessing and mitigating risk, ultimately contributing to the development of more robust and dependable self-driving systems.