Methods and systems for learning safe driving paths

A system comprising:

• at least one processor;
• and
• a non-transitory computer readable medium storing computer, which when executed cause the system to:
• acquire vehicle sensor data for a plurality of driving events associated with autonomous driving adversity conditions, the vehicle sensor data including, for each driving event, corresponding image data depicting surroundings of the vehicle and corresponding inertial measurement data;
• acquire, for each driving event of the plurality of driving events, corresponding vehicle positioning data indicative of a corresponding trajectory followed by the vehicle;
• and
• train, using the vehicle sensor data and the vehicle positioning data, a machine learning model to predict navigation trajectories during the autonomous driving adversity conditions.

A non-transitory computer-readable medium comprising computer instruction, the computer instructions when executed by one or more processors cause the one or more processors to:

• acquire vehicle sensor data for a plurality of driving events associated with autonomous driving adversity conditions, the vehicle sensor data including, for each driving event, corresponding image data depicting surroundings of the vehicle and corresponding inertial measurement data;
• acquire, for each driving event of the plurality of driving events, corresponding vehicle positioning data indicative of a corresponding trajectory followed by the vehicle;
• and
• train, using the vehicle sensor data and the vehicle positioning data, a machine learning model to predict navigation trajectories during the autonomous driving adversity conditions.