Model development using parallel driving data collected from multiple computing systems

A vehicle comprising:

• a cabin configured to receive at least one entity chosen from an operator, a passenger, and cargo;
• a drive system configured to motivate, accelerate, decelerate, stop, and steer the vehicle;
• an operator control system configured to allow the operator to direct operations of the vehicle;
• an operator assist system configured to perform at least one function chosen from:
• autonomously controlling the vehicle without assistance of the operator;
• and
• assisting the operator in controlling the vehicle;
• and
• a vehicle data system operably coupled with at least one sensor aboard a vehicle and configured to collect vehicle driving data representing driving conduct of the operator in operating the vehicle during at least one trip and provide the vehicle driving data to an evaluation system, wherein the vehicle driving data is configured to be:
• assigned a risk level for at least one event included in the vehicle driving data based on data provided by the at least one sensor;
• and
• correlated with portable driving data collected by a portable computing system aboard the vehicle to enable a pattern to be identified in the portable driving data that is associable with the risk level.

A computer-implemented method comprising:

• receiving vehicle driving data collected by a vehicle data system operably coupled with at least one sensor aboard a vehicle and configured to collect data representing driving conduct of the operator in operating the vehicle during at least one trip;
• receiving portable driving data collected by a portable data system transportable aboard the vehicle to collect representing the driving conduct of the operator in operating the vehicle during the at least one trip;
• and
• evaluating the vehicle driving data and the portable driving data, including:
• assigning a risk level to at least one event included in the vehicle driving data based on data provided by the at least one sensor;
• and
• correlating the vehicle driving data with the portable driving data to identify a pattern in the portable driving data that is associable with the risk level.