Rain-Aware Lane Change Decision Model for Autonomous Vehicle Using Deep Reinforcement Learning
This paper proposes a rain-aware LCD model using Deep Q-Networks (DQN), modified to incorporate rain-dependent human-driven vehicle behavior and wet-road friction effects on the ego vehicle and a safety-augmented DQN model was introduced to penalize unsafe close-following behavior before an actual collision occurs.