E-Mail: christopher.diehl@tu-dortmund.de

Research focus:

• Learning-based decision making and situation prediction for automated driving
• Keywords: reinforcement learning, inverse reinforcement learning, imitation learning, game theory, optimal control

Further activities

• WiSe: Supervision of the lecture Automated Driving
• Summer semester: Supervision of the lecture Learning in Robotics, Multivariable Systems and Optimal Control

Journal and book contributions:

2023

• Diehl, C., T. Sievernich, M. Krüger, F. Hoffmann, T. Bertram: "Uncertainty-Aware Model-Based Offline Reinforcement Learning for Automated Driving", IEEE Robotics and Automation Letters (RA-L), 2023

2022

• Krüger, M., P. Palmer, C. Diehl, T. Osterburg, T. Bertram: "Recognition Beyond Perception: Environmental Model Completion by Reasoning for Occluded Vehicles", IEEE Robotics and Automation Letters (RA-L), 2022.

2021

• Diehl, C., N.Stannartz, T. Bertram : Navigation with Uncertain Map Data for Automated Vehicles
  Springer Fachmedien Wiesbaden

Conference contributions:

2023

• Diehl, C., J. Adamek, M. Krueger, F. Hoffmann and T. Bertram: "Differentiable Constrained Imitation Learning for Robot Motion Planning and Control", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Workshop on Traffic Agent Modeling for Autonomous Driving Simulation, Detroit, USA, October 2023
• Diehl, C., T. Klosek, M. Krueger, N. Murzyn, T. Osterburg, T. Bertram: "Energy-based Potential Games for Joint Motion Forecasting and Control", Conference on Robot Learning (CoRL), Atlanta, USA, November 2023
• Osterburg, T., C. Diehl, T. Bertram : "Social Behavior Prediction for Automated Vehicles Using Contrastive Learning", IFToMM D-A-CH, 2023 (Accepted)

2022

• Stockem Novo, A.S., Marco Stolpe, Christopher Diehl, Timo Osterburg, Torsten Bertram, Vijay Parsi,Nils Murzyne, Mualla, Georg,Schneider, and Philipp Töws:"Mid-term status report on KISSaF: AI-based situation interpretation for automated driving" AmE 2022 - Automotive meets Electronics, 13th GMM-Symposium September 2022
• Diehl, C., A. Makarow, C. Rösmann, T. Bertram: "Time-Optimal Nonlinear Model Predictive Control for Radar-based Automated Parking", IFAC Symposium on Intelligent Autonomous Vehicles, 2022.
• Diehl, C., T. Osterburg, N. Murzyn, G. Schneider, F. Hoffmann, T. Bertram : "Conditional Behavior Prediction for Automated Driving on Highways", Proc. 32nd Workshop Computational Intelligence (CIW), 2022.
• Novo, A.S., M. Stolpe, C. Diehl, T. Osterburg, T. Bertram, V. Parsi, N. Murzyn, F. Mualla, G. Schneider, P. Töws : "Mid-term status report on KISSaF: AI-based Situation Interpretation for Automated Driving", Automotive meets Electronics (AME), 2022

2021

• Diehl, C., T. Waldeyer, F. Hoffmann, T. Bertram: VectorRL: Interpretable Graph-based Reinforcement Learning for Automated Driving, Proc. 31st Workshop Computational Intelligence
  Berlin, 25-26.11.2021
• Diehl, C., T. Sievernich, M. Krüger, F. Hoffmann, T. Bertam: UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning, Advances in Neural Information Processing Systems - Machine Learning for Autonomous Driving Workshop (NeuRIPS 2021 ML4AD)
  2021

2020

• Diehl, C., E. Feicho, A. Schwambach, T. Dammeier, T. Bertram: Radar-based Dynamic Occupancy Grid Mapping, 23nd IEEE International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece, 20-23.09.2020 (accepted)
  September 2020

Diploma/bachelor/master theses:

2020

• C. Wunsch
  Path planning based on imprecise external map information and local sensor data
  Supervision: C. Diehl, N. Stannartz, T. Bertram