Driver Risk Assessment System and Method Having Calibrating Automatic Event Scoring

A method for evaluating risk in driving, comprising the steps of:

• capturing driving event data at one or more event capture devices coupled with said vehicle;
• analyzing the driving event data with at least one event detector device to assign a predicted driving event identifier selected from a pre-determined group of driving event identifiers;
• assigning an event score to said predicted driving event identifier, said event score being either the result of actual human review of said driving event data associated with said predicted driving event identifier, or the historical confidence that prior human review of driving event data leading to the same predicted driving event identifier was confirmed;
• and
• selectively uploading all or part of said captured data to a remote computing device, said selective uploading being responsive to said assigned event score.

A method for reducing risk in driving, comprising:

• obtaining a plurality of driving event data for the individual driver, said event data comprising selectively uploadable video or audio data and regularly uploaded velocity, acceleration, vehicle spatial orientation and heading, vehicle metadata and vehicle location data, the driving event data obtained from a data storage area comprising a plurality of captured driving event data for a plurality of drivers;
• analyzing the plurality of regularly uploadable driving event data;
• analyzing demographic data for the individual driver, said demographic data obtained from a data storage area comprising a plurality of driver records, said records comprising demographic data;
• and scoring the individual driver based on the analysis of the plurality of driving event data and the analysis of the demographic data;
• and uploading relevant portions of said selectively uploadable video and audio data to a remote computing device responsive to a two-stage analysis of said driving event data, said first stage being the numerical analysis of the driving event data in order to generate a predicted event identifier selected from a group of potential event identities, and the second stage being the assignment of a confidence score to the generated predicted event identifier, with said confidence score being responsive to intermittent human review of predicted driving events.