AINeutralarXiv – CS AI · 8h ago6/10
🧠
Multi-Objective Reinforcement Learning for Tactical Decision Making for Trucks in Highway Traffic
Researchers present a multi-objective reinforcement learning framework using Proximal Policy Optimization to optimize tactical decision-making for autonomous trucks on highways. The system learns Pareto-optimal policies that balance competing objectives—safety, energy efficiency, and time efficiency—without requiring retraining when switching between different driving behaviors.