CONTEXTUAL SCORING OF AUTOMOBILE DRIVERS

• US 20170088142A1
• Filed: 09/25/2015
• Published: 03/30/2017
• Est. Priority Date: 09/25/2015
• Status: Active Grant

• Current Assignee: McAfee, LLC
• Original Assignee: McAfee, Inc. (McAfee, LLC)
• Inventors: Hunt, Simon, Sambandam, Venkata Ramanan, Venkateswaran, Prasanna
• Granted Patent: US 9,914,460 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2040/0809 Driver authorisation; Driver identity check
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/406 Traffic density
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 40/09 Driving style or behaviour

Abstract

In an example, there is disclosed a computing apparatus, including: a driver identity detector to detect the identity of a driver; and one or more logic elements providing a driver competency engine, operable to: detect the identity of the driver; evaluate the driver'"'"'s operation of a vehicle; and build a driver competency profile based at least in part on the evaluating. The driver competency engine may further be operable to detect a context of the operation, such as environmental factors. There is also described a method of providing a driver competency engine, and one or more computer readable mediums having stored thereon executable instructions for providing a driver competency engine.

Claims

1. A computing apparatus, comprising:

a driver identity detector to detect the identity of a driver;

an operational sensor interface; and

one or more logic elements comprising a driver competency engine, configured to;

detect the identity of the driver via the identity detector;

evaluate the driver'"'"'s operation of a vehicle according to operational inputs received via the operational sensor interface;

build a driver competency profile based at least in part on the evaluating; and

compute a current risk factor of the form RF=avg(DS,DG)/K, wherein RF is the risk factor, DS is a normalized speed deviation, DG is a normalized g-force deviation, and K is a constant.

2. The computing apparatus of claim 1, wherein building the driver competency profile comprises tracking the driver'"'"'s overall experience with operating the vehicle.

3. The computing apparatus of claim 1, further comprising a context interface, wherein the driver competency engine is further configured to track the driver'"'"'s operation of the vehicle relative to a context detected via the context interface.

4. The computing apparatus of claim 3, wherein the detected context comprises a factor selected from the group consisting of weather, visibility, temperature, time of day, road conditions, traffic, road type, road shape, road size, terrain type, construction, vehicle type, vehicle capabilities, vehicle safety features, vehicle condition, vehicle maintenance state, presence of passengers, number of passengers, identity of passengers, noise level, and driver'"'"'s stress level.

5. The computing apparatus of claim 1, wherein the driver competency engine is further configured to load a saved driver competency profile, and wherein building the driver competency profile comprises updating the saved driver competency profile.

6. The computing apparatus of claim 5, wherein loading the saved driver competency profile comprises retrieving the driver competency profile from a network location.

7. The computing apparatus of claim 1, wherein evaluating the driver'"'"'s operation of the vehicle comprises retrieving from a storage a composite profile of a plurality of other drivers.

8. The computing apparatus of claim 7, wherein the composite profile is crowd-sourced to a network location.

10. The computing apparatus of claim 1, wherein the driver competency engine is further configured to act on computing the risk factor.

11. The computing apparatus of claim 10, wherein acting on the risk factor comprises providing advice for the driver.

12. The computing apparatus of claim 10, wherein acting on the risk factor comprises determining that the risk factor exceeds a risk threshold and operating an actuator to take at least partial control of the vehicle.

13. The computing apparatus of claim 10, wherein acting on the risk factor comprises providing data to a third party.

9. (canceled)

14. One or more tangible, non-transitory computer-readable storage mediums having stored thereon executable instructions for providing a driver competency engine for a driver of a vehicle, the driver competency engine configured to:

detect the identity of the driver via a detector;

evaluate the driver'"'"'s operation of the vehicle, comprising receiving operational inputs from one or more operational sensors;

build a driver competency profile based at least in part on the evaluating; and

compute a current risk factor of the form RF=avg(DS,DG)/K, wherein RF is the risk factor, DS is a normalized speed deviation, DG is a normalized g-force deviation, and K is a constant.

15. The one or more tangible, non-transitory computer-readable mediums of claim 14, wherein building the driver competency profile comprises tracking the driver'"'"'s overall experience with operating the vehicle.

16. The one or more tangible, non-transitory computer-readable mediums of claim 14, wherein the driver competency engine is further configured to track the driver'"'"'s operation of the vehicle relative to a detected context, comprising receiving contextual inputs from one or more contextual sensors.

17. The one or more tangible, non-transitory computer-readable mediums of claim 16, wherein the detected context comprises a factor selected from the group consisting of weather, visibility, temperature, time of day, road conditions, traffic, road type, road shape, road size, terrain type, construction, vehicle type, vehicle capabilities, vehicle safety features, vehicle condition, vehicle maintenance state, presence of passengers, number of passengers, identity of passengers, noise level, and driver'"'"'s stress level.

18. The one or more tangible, non-transitory computer-readable mediums of claim 14, wherein the driver competency engine is further configured to load a saved driver competency profile from a storage, and wherein building the driver competency profile comprises updating the saved driver competency profile to the storage.

19. The one or more tangible, non-transitory computer-readable mediums of claim 18, wherein loading the saved driver competency profile comprises retrieving the driver competency profile from a network location.

20. The one or more tangible, non-transitory computer-readable mediums of claim 14, wherein evaluating the driver'"'"'s operation of the vehicle comprises retrieving a composite profile of a plurality of other drivers.

21. The one or more tangible, non-transitory computer-readable mediums of claim 20, wherein the composite profile is crowd-sourced to a network location.

23. The one or more tangible, non-transitory computer-readable mediums of claim 14, wherein the driver competency engine is further configured to act on computing the risk factor, wherein acting on the risk factor comprises an action selected from the group consisting of providing advice for the driver, determining that the risk factor exceeds a risk threshold and operating an actuator to take at least partial control, and providing data to a third party.

22. (canceled)

24. A method of providing a driver competency engine for a driver of a vehicle, comprising:

detecting the identity of the driver via an identity sensor;

evaluating the driver'"'"'s operation of the vehicle comprising receiving operational inputs from one or more operational sensors;

building a driver competency profile based at least in part on the evaluating; and

computing a current risk factor of the form RF=avg(DS,DG)/K, wherein RF is the risk factor, DS is a normalized speed deviation, DG is a normalized g-force deviation, and K is a constant.

25. The method of claim 24, further comprising tracking the driver'"'"'s operation of the vehicle relative to a detected context, comprising receiving contextual inputs via one or more contextual sensors.