METHODS FOR MOTOR VEHICLE DRIVER RISK REDUCTION AND DEVICES THEREOF

• US 20150064659A1
• Filed: 09/03/2013
• Published: 03/05/2015
• Est. Priority Date: 09/03/2013
• Status: Abandoned Application

• Current Assignee: Edriving Fleet LLC (Solera Holdings Incorporated)
• Original Assignee: Interactive Driving Systems Inc. (Solera Holdings Incorporated)
• Inventors: Dubens, Edmund S.
• Application Number:
  US14/017,015
• Publication Number:
  US 20150064659A1
• Time in Patent Office: Days
• US Class Current: 434/65
• CPC Class Codes: G09B 19/167 Control of land vehicles
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F

Abstract

A method, non-transitory computer readable medium, and a driver intervention device that obtains an indication of a risk event associated with a motor vehicle driver. At least one human factor of the motor vehicle driver that contributed to the risk event is retrieved based on a correlation with the indicated risk event. At least one recommended intervention is determined for the motor vehicle driver based on a match of the at least one human factor of the motor vehicle driver. The determined at least one recommended intervention is output to a computing device associated with the motor vehicle driver.

Claims

1. A method for motor vehicle driver risk reduction, the method comprising:

obtaining, by a driver intervention device, an indication of each of a plurality of risk events associated with a motor vehicle driver for a historical period of time;

retrieving, by the driver intervention device, a plurality of human factors of the motor vehicle driver based on a correlation of the human factors with one or more of the risk event indications in a human factor mapping table;

determining, by the driver intervention device, a risk reduction plan comprising a plurality of recommended interventions for the motor vehicle driver based on a correlation of each of the recommended interventions with one or more of the human factors, the human factors each comprising an indication of an attribute of the motor vehicle driver that contributed to one or more of the risk events;

determining, by the driver intervention device, a plurality of risk levels each associated with one of the human factors based on a number of correlations of each of the human factors with one of the risk events, wherein the risk levels each reflect a likelihood that the associated one of the human factors will contribute to a future risk event associated with the motor vehicle driver; and

outputting, by the driver intervention device, the risk reduction plan and one or more of the risk levels in response to one or more received requests.

2. The method of claim 1, wherein:

the recommended interventions of the risk reduction plan are selected based on a correlation of the recommended interventions with one or more of the human factors having a higher associated risk level than one or more other of the human factors; and

the outputting further comprises outputting the determined risk reduction plan to a computing device associated with the motor vehicle driver.

3. The method of claim 1, further comprising:

outputting, by the driver intervention device, the risk levels in response to a request received from a fleet vehicle operator associated with the motor vehicle driver.

4. The method of claim 3, further comprising:

retrieving, by the driver intervention device, a risk level for one or more human factors for each of one or more other motor vehicle drivers sharing a characteristic with the motor vehicle driver; and

outputting, by the driver intervention device, one or more of the determined plurality of risk levels and the retrieved risk level for the one or more human factors for each of the one or more other motor vehicle drivers in response to a received request for a comparison of the motor vehicle driver to the one or more other motor vehicle drivers.

5. The method of claim 1, wherein the risk event is an incident, a collision, or a violation and the obtaining further comprises:

obtaining performance data associated with the motor vehicle driver from one or more performance data source devices; and

identifying the risk event based on the performance data.

6. The method of claim 5, wherein the performance data comprises at least one or more motor vehicle records for the motor vehicle driver, road side inspection data for the motor vehicle driver, telematics data retrieved from a motor vehicle associated with the motor vehicle driver, or one or more insurance claim records associated with the motor vehicle driver.

7. The method of claim 1, wherein the at least one recommended intervention comprises educational, informational, or training material comprising written, audio, or video content or a link to the educational, informational, or training material.

8. A non-transitory computer readable medium having stored thereon instructions for motor vehicle driver risk reduction comprising machine executable code which when executed by a processor, causes the processor to perform steps comprising:

obtaining an indication of each of a plurality of risk events associated with a motor vehicle driver for a historical period of time;

retrieving a plurality of human factors of the motor vehicle driver based on a correlation of the human factors with one or more of the risk event indications in a human factor mapping table;

determining a risk reduction plan comprising a plurality of recommended interventions for the motor vehicle driver based on a correlation of each of the recommended interventions with one or more of the human factors, the human factors each comprising an indication of an attribute of the motor vehicle driver that contributed to one or more of the risk events;

determining a plurality of risk levels each associated with one of the human factors based on a number of correlations of each of the human factors with one of the risk events, wherein the risk levels each reflect a likelihood that the associated one of the human factors will contribute to a future risk event associated with the motor vehicle driver; and

outputting the risk reduction plan and one or more of the risk levels in response to one or more received requests.

9. The medium of claim 8, wherein:

the recommended interventions of the risk reduction plan are selected based on a correlation of the recommended interventions with one or more of the human factors having a higher associated risk level than one or more other of the human factors; and

the outputting further comprises outputting the determined risk reduction plan to a computing device associated with the motor vehicle driver.

10. The medium of claim 8, further having stored thereon instructions that when executed by the processor cause the processor to perform steps further comprising:

outputting the risk levels in response to a request received from a fleet vehicle operator associated with the motor vehicle driver.

11. The medium of claim 10, further having stored thereon instructions that when executed by the processor cause the processor to perform steps further comprising:

retrieving a risk level for one or more human factors for each of one or more other motor vehicle drivers sharing a characteristic with the motor vehicle driver; and

outputting one or more of the determined plurality of risk levels and the retrieved risk level for the one or more human factors for each of the one or more other motor vehicle drivers in response to a received request for a comparison of the motor vehicle driver to the one or more other motor vehicle drivers.

12. The medium of claim 8, wherein the risk event is an incident, a collision, or a violation and the obtaining further comprises:

obtaining performance data associated with the motor vehicle driver from one or more performance data source devices; and

identifying the risk event based on the performance data.

13. The medium of claim 12, wherein the performance data comprises at least one or more motor vehicle records for the motor vehicle driver, road side inspection data for the motor vehicle driver, telematics data retrieved from a motor vehicle associated with the motor vehicle driver, or one or more insurance claim records associated with the motor vehicle driver.

14. The medium of claim 8, wherein the at least one recommended intervention comprises educational, informational, or training material comprising written, audio, or video content or a link to the educational, informational, or training material.

15. A driver intervention device, comprising:

a processor coupled to a memory and configured to execute programmed instructions stored in the memory comprising;

obtaining an indication of each of a plurality of risk events associated with a motor vehicle driver for a historical period of time;

retrieving a plurality of human factors of the motor vehicle driver based on a correlation of the human factors with one or more of the risk event indications in a human factor mapping table;

determining a risk reduction plan comprising a plurality of recommended interventions for the motor vehicle driver based on a correlation of each of the recommended interventions with one or more of the human factors, the human factors each comprising an indication of an attribute of the motor vehicle driver that contributed to one or more of the risk events;

determining a plurality of risk levels each associated with one of the human factors based on a number of correlations of each of the human factors with one of the risk events, wherein the risk levels each reflect a likelihood that the associated one of the human factors will contribute to a future risk event associated with the motor vehicle driver; and

outputting the risk reduction plan and one or more of the risk levels in response to one or more received requests.

16. The device of claim 15, wherein:

the recommended interventions of the risk reduction plan are selected based on a correlation of the recommended interventions with one or more of the human factors having a higher associated risk level than one or more other of the human factors; and

the outputting further comprises outputting the determined risk reduction plan to a computing device associated with the motor vehicle driver.

17. The device of claim 15, wherein the processor is further configured to execute programmed instructions stored in the memory further comprising:

outputting the risk levels in response to a request received from a fleet vehicle operator associated with the motor vehicle driver.

18. The device of claim 17, wherein the processor is further configured to execute programmed instructions stored in the memory further comprising:

retrieving a risk level for one or more human factors for each of one or more other motor vehicle drivers sharing a characteristic with the motor vehicle driver; and

outputting one or more of the determined plurality of risk levels and the retrieved risk level for the one or more human factors for each of the one or more other motor vehicle drivers in response to a received request for a comparison of the motor vehicle driver to the one or more other motor vehicle drivers.

19. The device of claim 15, wherein the risk event is an incident, a collision, or a violation and the obtaining further comprises:

obtaining performance data associated with the motor vehicle driver from one or more performance data source devices; and

identifying the risk event based on the performance data.

20. The device of claim 19, wherein the performance data comprises at least one or more motor vehicle records for the motor vehicle driver, road side inspection data for the motor vehicle driver, telematics data retrieved from a motor vehicle associated with the motor vehicle driver, or one or more insurance claim records associated with the motor vehicle driver.

21. The device of claim 15, wherein the at least one recommended intervention comprises educational, informational, or training material comprising written, audio, or video content or a link to the educational, informational, or training material.