Systems and methods for associating vehicle operators with driving misses indicated in vehicle operation data

• US 9,886,638 B1
• Filed: 04/14/2017
• Issued: 02/06/2018
• Est. Priority Date: 01/06/2016
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Chan, Aaron Scott, Sanchez, Kenneth Jason
• Primary Examiner(s): Sherali, Ishrat I
• Application Number:
  US15/488,094
• Time in Patent Office: 298 Days
• Field of Search: 382104
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/02 Registering or indicating driving, working, idle, or waiting time only apparatus forming part of taximeters G07B13/00
• CPC Class Codes: G07C 5/085 using electronic data carriers
• CPC Class Codes: G07C 9/257 electronically G07C9/26 takes precedence

Abstract

Systems and methods for assessing vehicle operation are provided. According to certain aspects, an electronic device may receive and analyze image data depicting an individual located within a vehicle. The electronic device may also access and compile vehicle operation data and operator data corresponding to a state or condition of the vehicle operator. The electronic device may identify, from the vehicle operator data, a set of close misses experienced by the vehicle, correlate the set of close misses with a state or condition of the vehicle operator, and attribute at least some of the close misses to the vehicle operator. A remote server may aggregate and compile corresponding data from a plurality of vehicles.

Claims

1. A computer-implemented method in an electronic device of assessing operation of a vehicle by an operator, the method comprising:

accessing (i) vehicle operation data associated with operation of the vehicle, and (ii) operator data associated with at least one condition of the operator and including image data indicating a movement or a position of the operator;

analyzing, by a computer processor, the vehicle operation data and the operator data, including;

identifying, from the vehicle operation data, a set of close misses experienced by the vehicle during the operation of the vehicle,

correlating the set of close misses to the operator data, and

based on the correlating, attributing at least a portion of the set of close misses to the operator; and

recording an indication of at least the portion of the set of close misses and an identification of the operator of the vehicle.

2. The computer-implemented method of claim 1, wherein accessing the vehicle operation data associated with the operation of the vehicle comprises:

retrieving sensor data from at least one of;

a yaw rate sensor, a tilt sensor, a steering angle sensor, a location module, and a brake sensor.

3. The computer-implemented method of claim 1, wherein the operator data further includes biometric data associated with the operator.

4. The computer-implemented method of claim 1, wherein accessing the operator data comprises:

accessing the image data included in the operator data from the at least one image sensor.

5. The computer-implemented method of claim 1, further comprising:

transmitting, to a remote server, the indication of at least the portion of the set of close misses and the identification of the operator of the vehicle.

6. The computer-implemented method of claim 1, wherein correlating the set of close misses to the operator data comprises:

identifying, for each of the set of close misses, an occurrence time; and

determining a state or condition of the operator immediately prior to each of the occurrence times.

7. The computer-implemented method of claim 6, wherein attributing at least the portion of the set of close misses to the operator comprises:

for each of the portion of the set of close misses, determining that the respective state or condition of the operator contributed to the respective close miss.

8. The computer-implemented method of claim 1, wherein identifying the set of close misses experienced by the vehicle during the operation of the vehicle comprises:

analyzing the vehicle operation data to identify a set of instances in which the vehicle operation data exceeds a predetermined threshold, the set of instances corresponding to the set of close misses.

9. The computer-implemented method of claim 8, further comprising:

accessing the predetermined threshold from a remote server.

10. The computer-implemented method of claim 1, further comprising:

analyzing the image data included in the operator data to identify the operator of the vehicle.

11. A system in an electronic device for assessing operation of a vehicle by an operator, comprising:

a memory configured to store non-transitory computer executable instructions; and

a processor configured to interface with the memory, wherein the processor is configured to execute the non-transitory computer executable instructions to cause the processor to;

access (i) vehicle operation data associated with operation of the vehicle, and (ii) operator data associated with at least one condition of the operator and including image data indicating a movement or a position of the operator,

analyze the vehicle operation data and the operator data, including;

identify, from the vehicle operation data, a set of close misses experienced by the vehicle during the operation of the vehicle,

correlate the set of close misses to the operator data, and

based on the correlating, attribute at least a portion of the set of close misses to the operator, and

record an indication of at least the portion of the set of close misses and an identification of the operator of the vehicle.

12. The system of claim 11, wherein to access the vehicle operation data associated with the operation of the vehicle, the processor is configured to:

retrieve sensor data from at least one of;

a yaw rate sensor, a tilt sensor, a steering angle sensor, a location module, and a brake sensor.

13. The system of claim 11, wherein the operator data further includes biometric data associated with the operator.

14. The system of claim 11, wherein to access the operator data, the processor is configured to:

access the image data included in the operator data from the at least one image sensor.

15. The system of claim 11, wherein the processor is further configured to:

transmit, to a remote server, the indication of at least the portion of the set of close misses and the identification of the operator of the vehicle.

16. The system of claim 11, wherein to correlate the set of close misses to the operator data, the processor is configured to:

identify, for each of the set of close misses, an occurrence time, and

determine a state or condition of the operator immediately prior to each of the occurrence times.

17. The system of claim 16, wherein to attribute at least the portion of the set of close misses to the operator, the processor is configured to:

for each of the portion of the set of close misses, determine that the respective state or condition of the operator contributed to the respective close miss.

18. The system of claim 11, wherein to identify the set of close misses experienced by the vehicle during the operation of the vehicle, the processor is configured to:

analyze the vehicle operation data to identify a set of instances in which the vehicle operation data exceeds a predetermined threshold, the set of instances corresponding to the set of close misses.

19. The system of claim 18, wherein the processor is further configured to:

access the predetermined threshold from a remote server.

20. The system of claim 11, wherein the processor is further configured to:

analyze the image data included in the operator data to identify the operator of the vehicle.