System and method for determining probability that a vehicle driver is associated with a driver identifier
A method for driver identification including recording a first image of a vehicle driver; extracting a set of values for a set of facial features of the vehicle driver from the first image; determining a filtering parameter; selecting a cluster of driver identifiers from a set of clusters, based on the filtering parameter; computing a probability that the set of values is associated with each driver identifier of the cluster; determining, at the vehicle sensor system, driving characterization data for the driving session; and in response to the computed probability exceeding a first threshold probability: determining that the new set of values corresponds to one driver identifier within the selected cluster, and associating the driving characterization data with the one driver identifier.
1. A method involving driver identification comprising:
recording an image sequence of a vehicle driver at an interior-facing camera of a vehicle system during a driving session;
determining a presence of a face in each of a number of images in the image sequence at a face detection module of the vehicle system to generate an image sequence subset;
extracting a feature vector from the image sequence subset at a feature extraction module;
determining a set of auxiliary sensor signals;
associating the vehicle driver with a driver identifier based on the feature vector in combination with the set of auxiliary sensor signals; and
associating the auxiliary sensor signals associated with the driving session and/or characterizations derived from the auxiliary sensor signals with a driving history associated with the driver identifier to determine insurance information.
2. The method of claim 1 , further comprising: using the driver identifier to identify the vehicle driver in a vehicle accident.
3. The method of claim 1 , further comprising: using said auxiliary sensor signals to detect an accident and/or to determine fault in the accident.
4. The method of claim 1 , wherein said auxiliary sensor signals comprise any of audio measurements and secondary camera streams.
5. The method of claim 1 , wherein the characterizations derived from the auxiliary sensor signals comprise any of driver sobriety and cautiousness.
6. The method of claim 1 , further comprising: transmitting the image sequence subset after a total number of images in the image sequence subset exceeds a threshold number.
7. The method of claim 1 , further comprising: determining an image quality associated with each of the number of images in the image sequence, wherein recording of each of the number of images in the image sequence is performed based on the image quality of a preceding image in the sequence exceeding a threshold quality.
8. The method of claim 1 , wherein the set of auxiliary sensor signals comprises a non-visual identification signal.
9. The method of claim 8 , wherein the non-visual identification signal comprises driver login information received at a client application executing on a mobile device associated with the vehicle driver.
10. The method of claim 1 , further comprising detecting a start time point of the driving session.
11. The method of claim 1 , wherein the set of auxiliary sensor signals comprises a set of historical data associated with past driving sessions.
12. The method of claim 11 , wherein the set of auxiliary sensor signals comprises a beacon signal received at the vehicle system from a mobile device associated with the vehicle driver.
13. The method of claim 1 , wherein said driver identifier comprises driver behavior data; and
wherein the method further comprises using said driver behavior data to determine driver actions and/or behaviors.
14. The method of claim 13 , wherein said driver behavior data comprises imagery data recorded by a vehicle sensor system of the vehicle driver of the vehicle during vehicle operation.
15. The method of claim 13 , wherein said driver behavior data comprises data indicative of a driver distraction level or driving tendencies.
16. A method involving driver identification comprising:
recording an image sequence of a vehicle driver at an interior-facing camera of a vehicle system during a driving session;
determining a presence of a face in each of a number of images in the image sequence at a face detection module of the vehicle system to generate an image sequence subset;
extracting a feature vector from the image sequence subset at a feature extraction module;
determining a set of auxiliary sensor signals;
associating the vehicle driver with a driver identifier based on the feature vector in combination with the set of auxiliary sensor signals;
associating the user identifier with a timestamp for the driving session or a driving event;
using the driver identifier associated with the timestamp for any one or more of: determining a payroll for the vehicle driver based upon whether and how long the vehicle driver was driving; determining liability when vehicle damage or a vehicle accident occurs during the driving session; tracking items or objects; and determining a driving profile, wherein the user identifier is associated with characterizations or sensor signals recorded during the driving session for the vehicle.
17. The method of claim 16 , further comprising: dispatching a slower driver to a passenger with a health problem, or dispatching a faster driver to another passenger that is historically in a rush.
18. The method of claim 16 , further comprising: associating the user identifier with a set of locations.
19. The method of claim 18 , wherein the set of locations comprises any of a pickup location, route, and end location.
20. The method of claim 18 , further comprising: using the set of locations to verify driver reports.
21. The method of claim 18 , further comprising: using the set of locations as a filtering parameter.
22. The method of claim 18 , further comprising: associating the driver identifier with a vehicle identifier uniquely identifying an individual vehicle.
23. The method of claim 18 , further comprising: using the set of locations to confirm scheduled use of the vehicle.
24. The method of claim 18 , further comprising: using the set of locations to determine which driver to assign liability to when vehicle damage is discovered.
25. The method of claim 16 , further comprising: using the driver identifier for fleet management purposes.
26. The method of claim 16 , further comprising: transmitting the image sequence subset after a total number of images in the image sequence subset exceeds a threshold number.
27. The method of claim 16 , further comprising: determining an image quality associated with each of the number of images in the image sequence, wherein recording of each of the number of images in the image sequence is performed based on the image quality of a preceding image in the sequence exceeding a threshold quality.
28. The method of claim 16 , wherein the set of auxiliary sensor signals comprises a non-visual identification signal.
29. The method of claim 28 , wherein the non-visual identification signal comprises driver login information received at a client application executing on a mobile device associated with the vehicle driver.
30. The method of claim 16 , further comprising detecting a start time point of the driving session.
31. The method of claim 16 , wherein the set of auxiliary sensor signals comprises a set of historical data associated with past driving sessions.
32. The method of claim 31 , wherein the set of auxiliary sensor signals comprises a beacon signal received at the vehicle system from a mobile device associated with the vehicle driver.
33. The method of claim 1 , wherein the insurance information comprises insurance premium or insurability.