This invention discloses a
machine learning-based intelligent driving behavior method. It acquires basic data, including driving behavior data from real-world road scenarios. Based on this data, it calculates feature vectors for each driving
scenario. Then, based on these feature vectors, it uses a
reinforcement learning algorithm to select driving scenarios. Finally, it generates driving behaviors within these scenarios using the same
reinforcement learning algorithm. Finally, it updates the strategy to obtain the optimal model. This method aims to optimize the
environmental perception and decision-making capabilities of the intelligent driving
system, thereby improving its adaptability and reliability in real-world driving scenarios.