Research

• Learning Path Tracking from Simulation
• Scalable Reinforcement Learning for Automated Driving at Occluded Intersections

Open Theses

• Learning Data Efficient Policies for Human-like Automated Driving at Intersections
• Combining Demonstrations with Reinforcement Learning for Intelligent Policies in Automated Driving

Publications

Danial Kamran, Carlos Fernandez Lopez, Martin Lauer, Christoph Stiller. Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning. In IEEE Intelligent Vehicles Symposium, Las Vegas, USA, 2020. accepted. [ http ]

Danial Kamran, Martin Lauer, Christoph Stiller. Learning Realistic High Level Decisions for Autonomous Driving at Complex Intersections. In 13. Uni-DAS e.V. Workshop Fahrerassistenz und automatisiertes Fahren, Walting, Germany, 2020. [ .pdf ]

Danial Kamran, Marvin Busch, Tizian Engelgeh. On the Challenges of Safe and Scalable Reinforcement Learning for Automated Driving at Intersections. In Proceedings of Robotics: Science and Systems (RSS) Workshops, Oregon State University at Corvallis, United States, 2020. [ http ]

Danial Kamran, Junyi Zhu, Martin Lauer. Learning Path Tracking for Real Car-like Mobile Robots From Simulation. In IEEE European Conference on Mobile Robots (ECMR), 2019. [ .pdf ]