Neural network approach for parameter learning to speed up planning for complex driving scenarios

A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations, the operations comprising:

• perceiving a driving environment surrounding the ADV based on sensor data obtained from one or more sensors mounted on the ADV;
• determining a driving scenario, in response to a driving decision based on the driving environment;
• applying a predetermined machine-learning model to data representing the driving environment and the driving scenario to generate a set of one or more driving parameters;
• and
• planning a trajectory to navigate the ADV using the set of the driving parameters according to the driving scenario through the driving environment.

A data processing system, comprising:

• a processor;
• and
• a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations, the operations including:
• perceiving a driving environment surrounding the ADV based on sensor data obtained from one or more sensors mounted on the ADV,
• determining a driving scenario, in response to a driving decision based on the driving environment,
• applying a predetermined machine-learning model to data representing the driving environment and the driving scenario to generate a set of one or more driving parameters, and
• planning a trajectory to navigate the ADV using the set of the driving parameters according to the driving scenario through the driving environment.