Human driving behavior modeling system using machine learning

A method comprising:

• using a data processor to obtain training image data from a plurality of real world image sources and using the data processor to perform object extraction on the training image data to detect a plurality of vehicle objects in the training image data;
• using the data processor to categorize the detected plurality of vehicle objects into behavior categories based on vehicle objects performing similar maneuvers at similar locations of interest;
• training a machine learning module to model particular human driving behaviors based on use of the training image data from one or more corresponding behavior categories;
• and
• using the data processor to generate a plurality of simulated dynamic vehicles that each model one or more of the particular human driving behaviors trained into the machine learning module based on the training image data.

A non-transitory machine-useable storage medium embodying instructions which, when executed by a machine, cause the machine to:

• a vehicle object extraction module, executable by the data processor, to obtain training image data from a plurality of real world image sources and to perform object extraction on the training image data to detect a plurality of vehicle objects in the training image data;
• a vehicle behavior classification module, executable by the data processor, to categorize the detected plurality of vehicle objects into behavior categories based on vehicle objects performing similar maneuvers at similar locations of interest;
• a machine learning module, executable by the data processor, trained to model particular human driving behaviors based on use of the training image data from one or more corresponding behavior categories;
• and
• a simulated vehicle generation module, executable by the data processor, to generate a plurality of simulated dynamic vehicles that each model one or more of the particular human driving behaviors trained into the machine learning module based on the training image data.