Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving

Understand

With the development of state-of-art deep reinforcement learning, we can efficiently tackle continuous control problems.

• But the deep reinforcement learning method for continuous control is based on historical data, which would make unpredicted decisions in unfamiliar scenarios.
• Combining deep reinforcement learning and safety based control can get good performance for self-driving and collision avoidance.
• In this passage, we use the Deep Deterministic Policy Gradient algorithm to implement autonomous driving without vehicles around.