Modeling Interactions of Autonomous Vehicles and Pedestrians with Deep Multi-Agent Reinforcement Learning for Collision Avoidance. - Raphael Trumpp; Harald Bayerlein; David Gesbert (IV, 2022)

Efficient Learning of Urban Driving Policies Using Bird'View State Representations. - Raphael Trumpp; Martin Büchner; Abhinav Valada; Marco Caccamo (ITSC, 2023)

Residual Policy Learning for Vehicle Control of Autonomous Racing Cars. - Raphael Trumpp; Denis Hoornaert; Marco Caccamo (IV, 2023)

Efficient Learning of Urban Driving Policies Using Bird's-Eye-View State Representations. - Raphael Trumpp; Martin Büchner; Abhinav Valada; Marco Caccamo (CoRR, 2023)

RaceMOP: Mapless Online Path Planning for Multi-Agent Autonomous Racing using Residual Policy Learning. - Raphael Trumpp; Ehsan Javanmardi; Jin Nakazato; Manabu Tsukada; Marco Caccamo (IROS, 2024)

Learning to Generate All Feasible Actions. - Mirco Theile; Daniele Bernardini 002; Raphael Trumpp; Cristina Piazza; Marco Caccamo; Alberto L. Sangiovanni-Vincentelli (IEEE Access, 2024)

Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks. - Benjamin David Evans; Raphael Trumpp; Marco Caccamo; Hendrik Willem Jordaan; Herman Arnold Engelbrecht (CoRR, 2024)

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints. - Mirco Theile; Lukas Dirnberger; Raphael Trumpp; Marco Caccamo; Alberto L. Sangiovanni-Vincentelli (CoRR, 2024)

Impoola: The Power of Average Pooling for Image-Based Deep Reinforcement Learning. - Raphael Trumpp; Ansgar Schäfftlein; Mirco Theile; Marco Caccamo (CoRR, 2025)

From Marginal to Joint Predictions: Evaluating Scene-Consistent Trajectory Prediction Approaches for Automated Driving. - Fabian Konstantinidis; Ariel Dallari Guerreiro; Raphael Trumpp; Moritz Sackmann; Ulrich Hofmann 002; Marco Caccamo; Christoph Stiller (CoRR, 2025)