A hybrid PPO state space combining image features, sensor data, and transformer-based trajectory predictions improves lane-change safety in CARLA, raising success from 47.6% to 87.8%.
Motion planning among dynamic, decision -making agents with deep reinforcement learning,
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A Hybrid Input based Deep Reinforcement Learning for Lane Change Decision-Making of Autonomous Vehicle
A hybrid PPO state space combining image features, sensor data, and transformer-based trajectory predictions improves lane-change safety in CARLA, raising success from 47.6% to 87.8%.