Apparatus and Method for Vehicle Driver Recognition and Customization Using Onboard Vehicle System Settings

• US 20100087987A1
• Filed: 10/08/2008
• Published: 04/08/2010
• Est. Priority Date: 10/08/2008
• Status: Abandoned Application

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: Huang, Jihua, Chin, Yuen-Kwok, Lin, William C.
• Application Number:
  US12/247,349
• Publication Number:
  US 20100087987A1
• Time in Patent Office: Days
• US Class Current: 701/36
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: G05B 2219/25056 Automatic configuration of monitoring, control system as function of operator input, events
• CPC Class Codes: G05B 2219/25084 Select configuration as function of operator

Abstract

A vehicle includes vehicle systems each having driver-selectable vehicle system settings (VSS), and a control system for statistically modeling the VSS to determine an identity of a driver. The control system automatically controls a setting of at least one of the vehicle systems using or based on the identity. The control system statistically models the VSS for the driver over time to produce a historical driver profile (HDP) for the driver, and can automatically update the HDP when said driver manually changes any one of the VSS. An optional driver identification device can verify the identity. A method for controlling a predetermined onboard system of a vehicle includes collecting a set of VSS for a plurality of onboard systems, processing the VSS through a statistical modeling algorithm to determine an identity of a driver of the vehicle, and automatically controlling a predetermined onboard system using the identity of the driver.

Claims

1. A vehicle comprising:

a plurality of vehicle systems each having a corresponding set of vehicle system settings (VSS), said set of VSS being one of a driver-selectable set of VSS and a driver-adjustable set of VSS; and

a control system operable for statistically modeling said set of VSS to thereby generate a historical driver profile (HDP), and for processing said HDP to thereby determine an identify a driver of the vehicle;

wherein said control system is operable for automatically controlling a setting of at least one of said plurality of vehicle systems using said identity.

2. The vehicle of claim 1, wherein said control system is adapted to statistically model a first predetermined subset of said set of VSS for said driver over time to thereby modify said HDP for said driver.

3. The vehicle of claim 2, wherein said control system is adapted to record a variance and a mean of a second predetermined subset of said set of driver-selectable VSS to thereby modify said HDP for said driver.

4. The vehicle of claim 2, wherein said control system is adapted to automatically update said HDP for said driver when said driver manually changes one of said set of VSS.

5. The vehicle of claim 1, further comprising a driver identification device, wherein said control system is operable for verifying said identity of said one driver using a signal from said driver identification device.

6. The vehicle of claim 5, wherein said driver identification device is selected from the group consisting essentially of:

a radio frequency identification (RFID) tag, a key fob, a speech recognition device, and a biometric identification device.

7. The vehicle of claim 1, wherein said control system includes an algorithm having each of a feature extraction subprocess, a feature selection subprocess, and a feature classification subprocess.

8. The vehicle of claim 7, wherein said feature extraction subprocess is a Linear Discriminant Analysis (LDA) subprocess, and wherein said feature classification process is a Gaussian Mixture Model (GMM) subprocess.

9. A method for controlling a predetermined onboard system of a vehicle, the method comprising:

collecting a set of vehicle system settings (VSS) for a plurality of different onboard systems of the vehicle, said set of VSS being one of a driver-selectable set of VSS and a driver-adjustable set of VSS;

processing the set of driver-selectable VSS through a statistical modeling algorithm to thereby determine an identity of a driver of the vehicle; and

automatically controlling the predetermined onboard system using the identity of the driver.

10. The method of claim 9, wherein collecting the set of VSS includes detecting a VSS for at least a pair of said different onboard systems selected from the group consisting of:

mirrors, seats, pedals, steering wheel, radio, and an HVAC system.

11. The method of claim 10, wherein processing the set of VSS through a statistical modeling algorithm includes generating an original feature vector collectively describing said set of VSS.

12. The method of claim 11, wherein processing the set of VSS includes transforming said original feature vector using a feature extraction subprocess to thereby generate a new feature vector.

13. The method of claim 12, wherein processing the set of VSS includes processing said new feature vector through a feature selection subprocess to thereby generate a final feature vector.

14. The method of claim 13, wherein processing the set of VSS includes processing said final feature vector through a classification subprocess to thereby determine the identity of the driver.

15. A method for controlling a predetermined onboard system of a vehicle, the method comprising:

collecting a set of driver-selectable vehicle system settings (VSS);

processing the set of driver-selectable VSS through a statistical modeling algorithm utilizing a Gaussian Mixture Model (GMM) to thereby determine an identity of a driver of the vehicle; and

automatically adjusting a setting of the predetermined onboard system using said identity.

16. The method of claim 15, further comprising statistically modeling a plurality of sets of driver-selectable VSS for the driver over time to thereby produce a historical driver profile (HDP).

17. The method of claim 15, wherein processing the set of driver-selectable VSS includes processing the set of driver-selectable VSS through a feature extraction subprocess selected from the group consisting of:

Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Kernel PCA, and Generalized Discriminant Analysis (GDA).

18. The method of claim 15, wherein processing the set of driver-selectable VSS includes processing the set of driver-selectable VSS through a feature selection subprocess selected from the group consisting of:

Exhaustive Search, Branch- and Bound Search, Sequential Forward/Backward Selection, and Sequential Forward/Backward Floating Search.