System and method for training a machine learning model deployed on a simulation platform

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:

• for each of a plurality of driving scenarios,
• responsive to sensor data from one or more sensors of a vehicle and the driving scenario, collecting driving statistics and environment data of the vehicle while the vehicle is driven by a human driver in accordance with the driving scenario,
• upon completion of the driving scenario, requesting the driver to select a label for the completed driving scenario and storing the selected label responsive to the driver selection, and
• extracting features from the driving statistics and the environment data based on predetermined criteria, the extracted features including some of the driving statistics and some of the environment data collected at the different points in time during the driving scenario, wherein the extracted features are utilized to evaluate behaviors of autonomous driving of a plurality of autonomous driving vehicles subsequently.

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
• for each of a plurality of driving scenarios,
• responsive to sensor data from one or more sensors of a vehicle and the driving scenario, collecting driving statistics and environment data of the vehicle while the vehicle is driven by a human driver in accordance with the driving scenario,
• upon completion of the driving scenario, requesting the driver to select a label for the completed driving scenario and storing the selected label responsive to the driver selection, and
• extracting features from the driving statistics and the environment data based on predetermined criteria, the extracted features including some of the driving statistics and some of the environment data collected at the different points in time during the driving scenario, wherein the extracted features are utilized to evaluate behaviors of autonomous driving of a plurality of autonomous driving vehicles subsequently.