Automatic identification of a vehicle driver based on driving behavior

• US 8,938,227 B2
• Filed: 12/25/2013
• Issued: 01/20/2015
• Est. Priority Date: 06/24/2012
• Status: Active Grant

• Current Assignee: Tango Networks Incorporated
• Original Assignee: Tango Networks Incorporated
• Inventors: Silver, Andrew, Lewis, Lathan
• Primary Examiner(s): Brandt, Christopher M
• Application Number:
  US14/140,492
• Publication Number:
  US 20140106732A1
• Time in Patent Office: 391 Days
• Field of Search: 455/569.2, 701/36, 340/438, 340/439, 340/440
• US Class Current: 455/420
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/90 Details of database functions independent of the retrieved data types
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04M 1/724098 Interfacing with an on-board device of a vehicle for hands-free speaking in vehicles H04M1/6075
• CPC Class Codes: H04M 1/72463 to restrict the functionality of the device
• CPC Class Codes: H04W 4/16 Communication-related supplementary services, e.g. call-transfer or call-hold
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 4/46 for vehicle-to-vehicle communication [V2V]

Abstract

A method and apparatus are disclosed that identify a motor vehicle operation and whether a driver is operating a mobile device. One example of operation may include a method that includes receiving vehicle data based on active operation of a vehicle and compiling a candidate driver identification profile (DIP) based on the received vehicle data. The method may also include comparing the candidate DIP to a pre-stored DIP and determining a match between the candidate DIP and the pre-stored DIP. The method may also include applying a restriction to a mobile station operated by a driver of the vehicle responsive to the match determination.

Claims

1. A method, comprising:

receiving vehicle data;

compiling a candidate driver identification profile (DIP) based on the received vehicle data;

comparing the candidate DIP to at least one pre-stored DIP;

determining a match between the candidate DIP and the at least one pre-stored DIP;

incrementing a DIP credibility score based on the DIP match to increase a DIP credibility threshold value for subsequent comparison operations; and

if the DIP credibility threshold values falls below a predetermined threshold value then deleting the at least one pre-stored DIP from memory.

2. The method of claim 1, wherein the vehicle data comprises at least one of a vehicle acceleration rate, pedal position, vehicle route information, time between driver operated events, and one or more vehicle peripheral activities.

3. The method of claim 2, wherein the vehicle peripheral activities comprise entertainment system preferences, vehicle seat settings, vehicle mirror settings, vehicle steering wheel settings, and vehicle climate control.

4. The method of claim 1 comprising applying at least one restriction to a mobile station operated by a driver of the vehicle responsive to the match determination.

5. The method of claim 4, wherein the at least one restriction is related to the match determination.

6. The method of claim 1, wherein the determining the match between the candidate DIP and the at least one pre-stored DIP further comprises declaring a match when the candidate DIP matches the at least one pre-stored DIP having a predetermined credibility threshold.

7. The method of claim 1, further comprising declaring the candidate DIP a new DIP and storing the new DIP in memory for subsequent DIP comparison operations.

8. An apparatus, comprising:

a receiver configured to receive vehicle data;

a processor configured to;

compile a candidate driver identification profile (DIP) based on the received vehicle data;

compare the candidate DIP to at least one pre-stored DIP; and

determine a match between the candidate DIP and the at least one pre-stored DIP;

wherein the processor is further configured to increment a DIP credibility score based on the DIP match to increase a DIP credibility threshold value for subsequent comparison operations;

wherein if the DIP credibility threshold values falls below a predetermined threshold value then the at least one pre-stored DIP is deleted from memory.

9. The apparatus of claim 8, wherein the vehicle data comprises at least one of a vehicle acceleration rate, pedal position, time between driver operated events, vehicle route information, and one or more vehicle peripheral activities.

10. The apparatus of claim 9, wherein the vehicle peripheral activities comprise entertainment equipment preferences, vehicle seat settings, vehicle mirror settings, vehicle steering wheel settings, and vehicle climate control.

11. The apparatus of claim 8 comprising a transmitter configured to transmit at least one restriction to a mobile station operated by a driver of the vehicle.

12. The apparatus of claim 11, wherein the at least one restriction is related to the match determination.

13. The apparatus of claim 8, wherein the processor determines the match between the candidate DIP and the at least one pre-stored DIP by matching the candidate DIP to the one pre-stored DIP having a predetermined credibility threshold.

14. The apparatus of claim 8, wherein the candidate DIP is declared a new DIP and stored in memory for subsequent DIP comparison operations.

15. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform:

receiving vehicle data;

compiling a candidate driver identification profile (DIP) based on the received vehicle data;

comparing the candidate DIP to at least one pre-stored DIP;

determining a match between the candidate DIP and the at least one pre-stored DIP;

incrementing a DIP credibility score based on the DIP match to increase a DIP credibility threshold value for subsequent comparison operations; and

if the DIP credibility threshold values falls below a predetermined threshold value then deleting the at least one pre-stored DIP from memory.

16. The non-transitory computer readable storage medium of claim 15, wherein the vehicle data comprises at least one of a vehicle acceleration rate, pedal position, time between driver operated events, vehicle route information, and one or more vehicle peripheral activities.

17. The non-transitory computer readable storage medium of claim 16, wherein the vehicle peripheral activities comprise entertainment equipment preferences, vehicle seat settings, vehicle mirror settings, vehicle steering wheel settings, and vehicle climate control.

18. The non-transitory computer readable storage medium of claim 15 comprising applying at least one restriction to a mobile station operated by a driver of the vehicle responsive to the match determination.

19. The non-transitory computer readable storage medium of claim 18 wherein the at least one restriction is related to the match determination.

20. The non-transitory computer readable storage medium of claim 15, wherein the determining the match between the candidate DIP and the at least one pre-stored DIP further comprises declaring a match when the candidate DIP matches the at least one pre-stored DIP having a predetermined credibility threshold, and declaring the candidate DIP a new DIP and storing the new DIP in memory for subsequent DIP comparison operations.