Context-based grading

• US 10,633,002 B1
• Filed: 06/21/2018
• Issued: 04/28/2020
• Est. Priority Date: 03/25/2016
• Status: Active Grant

• Current Assignee: Allstate Insurance Company (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Ferguson, Dana
• Primary Examiner(s): Wong, Yuen
• Application Number:
  US16/014,417
• Time in Patent Office: 677 Days
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention

Abstract

A driving analysis server may be configured to receive vehicle operation data from mobile devices respectively disposed within the vehicles, and may use the data to group the vehicles into multiple groups. A driving pattern for each vehicle may be established and compared against a group driving pattern of its corresponding group to identify outliers. A driver score the outliers may be adjusted positively or negatively based on whether the outlier behaved in a manner more or less safe than its group. Further, unsafe driving events performed by the outlier that were the result of another vehicle'"'"'s unsafe driving event may be ignored or positively accounted for in determining or adjusting the outlier'"'"'s driver score.

Claims

1. A driving analysis server comprising:

a processing unit comprising a processor; and

a memory unit storing computer-readable instructions that, when executed by the processing unit, cause the driving analysis server to;

receive telematics data associated with a plurality of vehicles;

determine a group of vehicles, wherein a geographic location of each vehicle in the group of vehicles is within a first distance from each other vehicle in the group of vehicles;

determine a driving pattern for a first vehicle in the group of vehicles, wherein the driving pattern for the first vehicle is a second vector comprising a plurality of elements representative of telematics data of the first vehicle;

determine a normalized group driving pattern representative of driving behavior of the group of vehicles, wherein the normalized group driving pattern of the group of vehicles is a first vector comprising a plurality of elements, wherein each element of the first vector is an average of values of each vector associated with each vehicle of the group of vehicles;

identify that the first vector is different than the second vector;

compare, based on the identification, a number of one or more unsafe driving events performed by the first vehicle to an average number of unsafe driving events performed by the group of vehicles;

adjust, based on the comparison, a driver score of the first vehicle, wherein the driver score is an indication of the driving pattern of the first vehicle compared to the normalized group driving pattern representative of driving behavior of the group of vehicles; and

output the driver score for display to a graphical user interface to a driver of the first vehicle.

2. The driving analysis server of claim 1, wherein adjusting the driver score of the first vehicle comprises positively adjusting the driver score of the first vehicle.

3. The driving analysis server of claim 1, wherein the computer-readable instructions, when executed by the processing unit, further cause the driving analysis server to:

in response to determining that the number of one or more unsafe driving events performed by the first vehicle is greater than the average number of unsafe driving events performed by the group of vehicles, negatively adjust the driver score of the first vehicle.

4. The driving analysis server of claim 1, wherein the computer-readable instructions, when executed by the processing unit, further cause the driving analysis server to:

in response to determining that a second vehicle of the group of vehicles caused the first vehicle to perform at least one unsafe driving event of the one or more unsafe driving events, ignore, in a calculation of the driver score for the first vehicle, the at least one unsafe driving event.

5. The driving analysis server of claim 1, wherein the computer-readable instructions, when executed by the processing unit, further cause the driving analysis server to:

in response to determining that a second vehicle of the group of vehicles caused the first vehicle to perform at least one unsafe driving event of the one or more unsafe driving events, positively account for the at least one unsafe driving event in a calculation of the driver score for the first vehicle.

6. The driving analysis server of claim 5, wherein the computer-readable instructions, when executed by the processing unit, further cause the driving analysis server to:

determine that the second vehicle caused the first vehicle to perform the unsafe driving event based, at least in part, on the second vehicle being within a second distance of the first vehicle and performing another unsafe driving event within a time frame prior to a time at which the first vehicle performed the at least one unsafe driving event.

7. The driving analysis server of claim 1, wherein an unsafe driving event is one of a hard-braking event, a swerving event, an excessive-speed event, or a hard-acceleration event.

8. The driving analysis server of claim 1, wherein each vehicle in the group of vehicles traversed the same driving route on a same date.

9. The driving analysis server of claim 1, wherein the telematics data is received from a plurality of mobile devices respectively disposed within the plurality of vehicles.

10. A method comprising:

receiving, by a computing device, telematics data associated with a plurality of vehicles;

determining a group of vehicles, wherein a geographic location of each vehicle in the group of vehicles is within a first distance from each other vehicle in the group of vehicles;

determining a driving pattern for a first vehicle in the group of vehicles, wherein the driving pattern for the first vehicle is a second vector comprising a plurality of elements representative of telematics data of the first vehicle;

determining a normalized group driving pattern representative of driving behavior of the group of vehicles, wherein the normalized group driving pattern of the group of vehicles is a first vector comprising a plurality of elements, wherein each element of the first vector is an average of values of each vector associated with each vehicle of the group of vehicles;

identifying that the first vector is different than the second vector;

comparing, based on the identifying, a number of one or more unsafe driving events performed by the first vehicle to an average number of unsafe driving events performed by the group of vehicles; and

adjusting, based on the comparison, a driver score of the first vehicle, wherein the driver score is an indication of the driving pattern of the first vehicle compared to the normalized group driving pattern representative of driving behavior of the group of vehicles; and

outputting the driver score for display to a graphical user interface to a driver of the first vehicle.

11. The method of claim 10, further comprising:

in response to determining that the number of unsafe driving events performed by the first vehicle is greater than the average number of unsafe driving events performed by the group of vehicles, negatively adjust the driver score of the first vehicle.

12. The method of claim 10, wherein adjusting the driver score comprises positively adjusting the driver score of the first vehicle.

13. The method of claim 10, further comprising:

in response to determining that a second vehicle of the group of vehicles caused the first vehicle to perform at least one unsafe driving event of the one or more unsafe driving events, ignore, in a calculation of the driver score for the first vehicle, the at least one unsafe driving event.

14. The method of claim 10, further comprising:

in response to determining that a second vehicle of the group of vehicles caused the first vehicle to perform at least one unsafe driving event of the one or more unsafe driving events, positively account for the at least one unsafe driving event in a calculation of the driver score for the first vehicle.

15. A non-transitory computer-readable medium storing instructions that, when executed by a computing device, cause the computing device to:

receive telematics data associated with a plurality of vehicles;

determine a group of vehicles, wherein a geographic location of each vehicle in the group of vehicles is within a first distance from each other vehicle in the group of vehicles;

determine a driving pattern for a first vehicle in the group of vehicles, wherein the driving pattern for the first vehicle is a second vector comprising a plurality of elements representative of telematics data of the first vehicle;

determine a normalized group driving pattern representative of driving behavior of the group of vehicles, wherein the normalized group driving pattern of the group of vehicles is a first vector comprising a plurality of elements, wherein each element of the first vector is an average of values of each vector associated with each vehicle of the group of vehicles;

determine that the first vector is different than the second vector;

identify a number of one or more unsafe driving events performed by the first vehicle to an average number of unsafe driving events performed by the group of vehicles;

adjust, based on the identification, a driver score of the first vehicle, wherein the driver score is an indication of the driving pattern of the first vehicle compared to the normalized group driving pattern representative of driving behavior of the group of vehicles; and

output the driver score for display to a graphical user interface to a driver of the first vehicle.

16. The non-transitory computer-readable medium of claim 15, further storing instructions that, when executed by the computing device, cause the computing device to:

in response to determining that the number of unsafe driving events performed by the first vehicle is greater than the average number of unsafe driving events performed by the group of vehicles, negatively adjust the driver score of the first vehicle.

17. The non-transitory computer-readable medium of claim 15, wherein adjusting the driver score comprises positively adjusting the driver score of the first vehicle.

18. The non-transitory computer-readable medium of claim 15, further storing instructions that, when executed by the computing device, cause the computing device to:

in response to determining that a second vehicle of the group of vehicles caused the first vehicle to perform at least one unsafe driving event of the one or more unsafe driving events, ignore, in a calculation of the driver score for the first vehicle, the at least one unsafe driving event.

19. The non-transitory computer-readable medium of claim 18, further storing instructions that, when executed by the computing device, cause the computing device to:

in response to determining that a second vehicle of the group of vehicles caused the first vehicle to perform at least one unsafe driving event of the one or more unsafe driving events, positively account for the at least one unsafe driving event in a calculation of the driver score for the first vehicle.

20. The non-transitory computer-readable medium of claim 15, wherein an unsafe driving event is one of a hard-braking event, a swerving event, an excessive-speed event, or a hard-acceleration event.