Papers
2
Total Citations
11
H-Index
2
About
Kenan Ahmic is a researcher at the German Aerospace Center (DLR) whose work sits at the intersection of artificial intelligence, vehicle system dynamics, and autonomous driving. His primary research focuses on developing robust, AI-based control methods for safety-critical automotive applications, with a particular emphasis on reinforcement learning (RL) for path following and vehicle motion control. Ahmic’s major contribution lies in addressing a fundamental challenge in autonomous driving: the gap between simulation and real-world performance. In his most cited work (2023, 7 citations), he pioneered the use of dynamics randomization within RL training to make controllers resilient to parametric uncertainties in vehicle models—a key step toward deploying learned policies on actual hardware without costly retraining. He also led the development of the AI-For-Mobility (AFM) research platform at DLR (2023, 4 citations), a production hybrid vehicle retrofitted to serve as a testbed for novel AI-based control strategies. This platform bridges simulation and reality, enabling rigorous validation of algorithms under real driving conditions. With his work gaining traction in the autonomous driving community, Ahmic is establishing himself as a key figure in making RL-based control safe, practical, and transferable to real-world vehicles.
Research Focus
Key Achievements
Top Papers
- 1
- 2AI-For-Mobility—A New Research Platform for AI-Based Control Methods4 citations · 2023