1 citations · 1 across the 3 of their papers we have counts for
3 papers
Interactive Trajectory Planning with Learning-based Distributionally Robust Model Predictive Control and Markov Systems
Erik Börve, Nikolce Murgovski, Morteza Haghir Chehreghani +1
We investigate interactive trajectory planning subject to uncertainty in the decisions of surrounding agents. To control the ego-agent, we aim to first learn the decision distribut…
Preference-Conditioned Multi-Objective Reinforcement Learning for Tactical Decision Making in Heavy-Duty Vehicles
Deepthi Pathare, Leo Laine, Morteza Haghir Chehreghani
A central difficulty in applying reinforcement learning to real-world applications such as autonomous driving is that conventional scalar reward formulations obtained by aggregatin…
Tactical Decision Making for Autonomous Trucks by Deep Reinforcement Learning with Total Cost of Operation Based Reward
Deepthi Pathare, Leo Laine, Morteza Haghir Chehreghani
We develop a deep reinforcement learning framework for tactical decision making in an autonomous truck, specifically for Adaptive Cruise Control (ACC) and lane change maneuvers in…