2 citations · 4 across the 5 of their papers we have counts for
5 papers
Data-driven Diffusion Models for Enhancing Safety in Autonomous Vehicle Traffic Simulations
Jinxiong Lu, Shoaib Azam, Gokhan Alcan +1
Safety-critical traffic scenarios are integral to the development and validation of autonomous driving systems. These scenarios provide crucial insights into vehicle responses unde…
Automated Feature Selection for Inverse Reinforcement Learning
Daulet Baimukashev, Gokhan Alcan, Ville Kyrki
Inverse reinforcement learning (IRL) is an imitation learning approach to learning reward functions from expert demonstrations. Its use avoids the difficult and tedious procedure o…
The Role of Higher-Order Cognitive Models in Active Learning
Oskar Keurulainen, Gokhan Alcan, Ville Kyrki
Building machines capable of efficiently collaborating with humans has been a longstanding goal in artificial intelligence. Especially in the presence of uncertainties, optimal coo…
Challenges of Data-Driven Simulation of Diverse and Consistent Human Driving Behaviors
Kalle Kujanpää, Daulet Baimukashev, Shibei Zhu +4
Building simulation environments for developing and testing autonomous vehicles necessitates that the simulators accurately model the statistical realism of the real-world environm…
Integrating Expert Guidance for Efficient Learning of Safe Overtaking in Autonomous Driving Using Deep Reinforcement Learning
Jinxiong Lu, Gokhan Alcan, Ville Kyrki
Overtaking on two-lane roads is a great challenge for autonomous vehicles, as oncoming traffic appearing on the opposite lane may require the vehicle to change its decision and abo…