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.
FORMATS 2022
This work introduces an active preference learning method that ensures adherence to traffic rules for autonomous vehicles by decreasing the number of question asked to the user.