Driving workload estimation

• US 6,995,663 B2
• Filed: 09/15/2003
• Issued: 02/07/2006
• Est. Priority Date: 10/31/2002
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: General Motors Corporation (Motors Liquidation Co. GUC Trust)
• Inventors: Geisler, Scott P., Nardi, Flavio, Creech, Thomas William, Marica, Stefano, Schreiner, Lisa
• Primary Examiner(s): Swarthout, Brent A.
• Assistant Examiner(s): LAI, ANNE VIET NGA
• Application Number:
  US10/662,957
• Publication Number:
  US 20040113799A1
• Time in Patent Office: 876 Days
• Field of Search: 340/438, 340/439, 340/576, 180/272, 701/1, 701/35
• US Class Current: 340/439
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

A method for estimating workload placed on the driver of a vehicle. The method comprises receiving workload estimation data. Driving conditions responsive to the workload estimation data are detected. An impact value of at least one of the driving conditions is calibrated. The impact values are combined to determine a current driving workload estimate. The current driving workload estimate is output.

Claims

1. A method for estimating workload placed on the driver of a vehicle, the method comprising:

receiving workload estimation data;

detecting driving conditions responsive to said workload estimation data;

calibrating an impact value of at least one of said driving conditions;

combining each said impact value to determine a current driving workload estimate; and

outputting said current-driving workload estimate after the passage of a pre-selected period of time from the outputting of a previous driving workload estimate, wherein said pre-selected period of time varies based on the value of the previous driving workload estimate.

2. The method of claim 1 wherein said workload estimation data includes internally generated vehicle data.

3. The method of claim 1 wherein said workload estimation data includes environment data.

4. The method of claim 1 wherein said workload estimation data includes current task data.

5. The method of claim 1 wherein said calibrating includes applying a weighting algorithm to at least one of said driving conditions.

6. The method of claim 1 wherein said calibrating is performed within one second of said receiving workload estimation data.

7. The method of claim 1 wherein said combining includes a multiplicative operation.

8. The method of claim 1 wherein said combining includes an additive operation.

9. The method of claim 1 wherein said outputting said current driver workload estimate is performed after the passage of the pre-selected period of time from the outputting of a previous if the value of said current driving workload estimate is less than the value of the previous driving workload estimate.

10. The method of claim 1 wherein said current driving workload estimate is expressed as a number ranging from one to five.

11. The method of claim 1 wherein said current driving workload estimate is expressed as a number ranging from one to one-hundred.

12. The method of claim 1 wherein said outputting includes transmitting said current driving workload estimate to a specified location.

13. The method of claim 12 wherein said specified location is a vehicle information management system.

14. The method of claim 1 wherein said outputting includes writing said current driving workload estimate to a log file.

15. The method of claim 1 wherein said workload estimation data includes at least one of vehicle speed, turn signal status, anti-lock brake status, traction control system status, vehicle stability data, steering wheel angle data, brake position data, throttle position data, engine revolutions per minute, spark data and fuel data.

16. The method of claim 1 wherein said workload estimation data includes at least one of headlamp status, wiper status, defroster status, outside air temperature data, global positioning data and time of day.

17. The method of claim 1 wherein said workload estimation data includes at least one of radio information and phone status.

18. The method of claim 1 wherein said workload estimation data includes adaptive cruise control data.

19. The method of claim 1 wherein said workload estimation data includes at least one of forward collision warning data, side object detection data and rear collision warning data.

20. The method of claim 1 wherein said workload estimation data includes lane departure warning data.

21. The method of claim 1 wherein said workload estimation data includes driver identification data.

22. A system for estimating workload placed on the driver of a vehicle, the system comprising:

a network; and

a microprocessor in communication with said network, said microprocessor including instructions to implement the method comprising;

receiving workload estimation data via said network;

detecting driving conditions responsive to said workload estimation data;

calibrating an impact value of at least one of said driving conditions;

combining each said impact value to determine a current driving workload estimate; and

outputting said current driving workload estimate after the passage of a pre-selected peroid of time from the outputting of a previous driving workload estimate, wherein said pre-selected period of time varies based on the value of the previous driving workload estimate.

23. The system of claim 22 further comprising a vehicle sensor in communication with said network for creating said workload estimation data.

24. The system of claim 22 wherein said network is the Internet.

25. The system of claim 22 wherein said network is a wireless network.

26. The system of claim 22 wherein said outputting said current driving workload estimate includes transmitting said driving workload estimate to a receiving location over said network.

27. A computer program product for estimating workload placed on the driver of a vehicle, the product comprising:

a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising;

receiving workload estimation data;

detecting driving conditions responsive to said workload estimation data;

calibrating an impact value of at least one of said driving conditions;

combining each said impact value to determine a current driving workload estimate; and

outputting said current driving workload estimate after the passage of a pre-selected period or time from the outputting of a previous driving workload estimate, wherein said pre-selected period of time varies based on the value of the previous driving workload estimate.