A single vision-based reinforcement learning policy can steer an autonomous vehicle in simulation with different driving styles by feeding it a user preference vector, without retraining.
Toward adaptive driving styles for automated driving with users’ trust and preferences,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving
A single vision-based reinforcement learning policy can steer an autonomous vehicle in simulation with different driving styles by feeding it a user preference vector, without retraining.