Driver risk assessment system and method having calibrating automatic event scoring

• US 8,508,353 B2
• Filed: 06/11/2010
• Issued: 08/13/2013
• Est. Priority Date: 01/26/2009
• Status: Active Grant

• Current Assignee: Lytx, Inc.
• Original Assignee: Lytx, Inc.
• Inventors: Cook, Bryon, Gilles, Louis
• Primary Examiner(s): Lieu, Julie
• Application Number:
  US12/814,117
• Publication Number:
  US 20100250021A1
• Time in Patent Office: 1,159 Days
• Field of Search: None
• US Class Current: 340/439
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/085 using electronic data carriers

Abstract

A Driver Risk Assessment System and Method Having Calibrating Automatic Event Scoring is disclosed. The system and method provide robust and reliable event scoring and reporting, while also optimizing data transmission bandwidth. The system includes onboard vehicular driving event detectors that record data related to detected driving events and selectively store or transfer data related to said detected driving events. If elected, the onboard vehicular system will score a detected driving event, compare the local score to historical values previously stored within the onboard system, and upload selective data or data types to a remote server or user if the system concludes that a serious driving event has occurred. Importantly, the onboard event scoring system, if enabled, will continuously evolve and improve in its reliability by being periodically re-calibrated with the ongoing reliability results of manual human review of automated predictive event reports. The system may further respond to independent user requests by transferring select data to said user at a variety of locations and formats.

Claims

1. A system for reducing risk in driving, comprising:

at least one event capture device associated with a vehicle, said event capture device or devices detecting data related to a physical condition of said vehicle;

at least one event detector device coupled with the vehicle and configured to;

communicate with said event capture device or devices;

predict, responsive to analysis of a group of data captured by said event capture device or devices, whether or not the group of data captured by said event capture device or devices represents a driving event; and

assign a unique risk identifier selected from a group of risk identities to said driving event;

an event scoring module attached to or otherwise associated to communicate with said event detector for generating an event score based upon the unique risk identifier and for applying risk confidence data related to the unique risk identifier;

an event data management module attached to or otherwise associated to communicate with said event detector for uploading data from said event capture devices to a remote computing device, with said uploading being responsive to said event score; and

a risk confidence data repository configured to communicate with said event scoring module to periodically update said risk confidence data.

2. The system of claim 1, wherein said risk confidence data is updated regularly after human review of captured event data.

3. The system of claim 2, wherein said human review of captured event data results in the assignment of a manual score to a specific driving event and the unique risk identifier assigned thereto by said event detector or event detectors.

4. The system of claim 3, wherein said human review of captured event data results in the assignment of a severity score related to a riskiness of the driving observed by the human reviewer in the data of the captured event.

5. The system of claim 4, wherein said risk confidence data comprises a confidence factor for each said risk identifier in said group of risk identities, said confidence factor being a fractional value representing the statistical likelihood that each said unique risk identifier in said group of risk identities is representative of a risky driving event.

6. The system of claim 5, wherein said risk confidence data for each unique risk identifier includes a percentage of times that human review concurred that the driving event to which the unique risk identifier was assigned was correct.

7. The system of claim 6, wherein said risk confidence data for each unique risk identifier includes a number representing a severity of risk of the driving event to which the unique risk identifier was assigned.

8. The system of claim 1, wherein at least one said event capture device generating a selectively uploaded data associated with the physical condition;

and at least another said event capture device generating a regularly uploaded data associated with the physical condition.

9. The system of claim 8, wherein said event data management module uploads said selectively uploaded data responsive to a comparison between said generated event score and a set of representative event scores stored in a local data repository associated with said comparison subsystem.

10. The system of claim 8, wherein said event score is based only upon said regularly uploaded data.

11. The system of claim 8, wherein said selectively uploaded data is selected from a group of audio data, video data, and telemetry data.

12. The system of claim 8, wherein said regularly uploaded data comprises vehicle velocity, vehicle acceleration, vehicle spatial orientation, vehicle metadata, and vehicle location.

13. 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 a 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 a result of actual human review of said driving event data associated with said predicted driving event identifier, or a historical confidence that prior human review of driving event data leading to the predicted driving event identifier was confirmed; and

selectively uploading all or part of said driving event data to a remote computing device, said selective uploading being responsive to said event score, wherein said selective uploading is further responsive to a data request by said event detector.

14. The method of claim 13, wherein said data request received by said event detector is sent from the remote computing device that is remote to said vehicle.

15. The method of claim 14, wherein an event score calculation excludes said selectively uploaded data.

16. The method of claim 15, wherein said selectively uploaded captured data comprises audio or video data.

17. The method of claim 13, wherein said selective uploading is further responsive to user request.