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cs.LG2026
Multi-Objective Reinforcement Learning for Tactical Decision Making for Trucks in Highway Traffic
Deepthi Pathare, Leo Laine, Morteza Haghir Chehreghani
Balancing safety, efficiency, and operational costs in highway driving poses a challenging decision-making problem for heavy-duty vehicles. A central difficulty is that conventiona…
cs.LG2025
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…