In this project, we aim to capture user preferences for driving task to generate personalized and safe behaviors. We use temporal logic formalism to specify the safety. To capture the user preferences, we utilize preference learning methods. Specifically, we ask pairwise questions that compare two behaviors.

In this project, we utilize temporal logic formalism to classify driving behaviors. The goal is to infer an STL formula that can distinguish two classes of behaviors. By using this formula, we can synthesize new behaviors that belong to the desired class.