Autonomous vehicle operation feature monitoring and evaluation of effectiveness

Patent metadata

Field	Value
Publication number	US-11869092-B2
Application number	US-202217679452-A
Country	US
Kind code	B2
Filing date	Feb 24, 2022
Priority date	May 20, 2014
Publication date	Jan 9, 2024
Grant date	Jan 9, 2024

Abstract

Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

First claim

What is claimed is:

1. A computer-implemented method for monitoring and evaluating a vehicle having one or more autonomous operation features for controlling the vehicle, comprising:
generating, by one or more processors of an on-board computer configured to control operation of the vehicle, operating data regarding operation of the vehicle, wherein the operating data includes (i) information from one or more sensors disposed within the vehicle, (ii) information regarding the one or more autonomous operation features, and (iii) a plurality of control decisions generated by the one or more autonomous operation features in response to sensor data from the one or more sensors, wherein the plurality of control decisions includes, for each of a plurality of times during vehicle operation: (i) an implemented control decision implemented to control the vehicle and (ii) one or more unimplemented control decisions generated by the one or more autonomous operation features but not implemented to control the vehicle, the unimplemented control decisions indicating alternative control actions for controlling the vehicle; and
determining, by the one or more processors, at least one risk level indicative of effectiveness of operation of the one or more autonomous operation features in controlling the vehicle based at least in part upon the operating data, including an indication of operating conditions of the vehicle in the information from the one or more sensors.

2. The computer-implemented method of claim 1 , the method further comprising:
determining, by the one or more processors, responses of the vehicle to the implemented control decision and predicted responses of the vehicle to the one or more unimplemented control decisions; and
adjusting, by the one or more processors, the at least one risk level based upon received actual loss data, the responses of the vehicle to the implemented control decision, and the predicted responses of the vehicle to the one or more unimplemented control decisions.

3. The computer-implemented method of claim 2 , the method further comprising:
receiving, at the one or more processors, a request for a quote of a premium associated with a vehicle insurance policy;
determining, by the one or more processors, the premium associated with the vehicle insurance policy based at least in part upon the adjusted at least one risk level; and
presenting, by the one or more processors, an option to purchase the vehicle insurance policy to a customer associated with the vehicle.

4. The computer-implemented method of claim 1 , wherein the one or more unimplemented control decisions further include at least one control decision not implemented because the autonomous operation feature was disabled.

5. The computer-implemented method of claim 1 , wherein:
each entry in a log of the operating data includes a timestamp associated with the recorded operating data, including information regarding at least one of the following: date, time, location, vehicle environment, vehicle condition, autonomous operation feature settings, or autonomous operation feature configuration information.

6. The computer-implemented method of claim 5 , the method further comprises receiving, at the one or more processors, external data regarding the vehicle environment for each entry in the log of the operating data based upon the timestamp associated with the entry, including information regarding at least one of the following: road conditions, weather conditions, nearby traffic conditions, type of road, construction conditions, presence of pedestrians, presence of other obstacles, or availability of autonomous communications from external sources; and
the at least one risk level is further determined based at least in part upon the external data regarding the vehicle environment.

7. The computer-implemented method of claim 5 , further comprising:
communicating, via a wireless network, the log of the operating data to a server, wherein the server determines and adjusts the at least one risk level.

8. A computer system for monitoring and evaluating a vehicle having one or more autonomous operation features for controlling the vehicle, comprising:
one or more processors; and
a non-transitory program memory coupled to the one or more processors and storing executable instructions that when executed by the one or more processors cause the computer system to:
generate operating data regarding operation of the vehicle by an on-board computer configured to control operation of the vehicle, wherein the operating data includes (i) information from one or more sensors disposed within the vehicle, (ii) information regarding the one or more autonomous operation features, and (iii) a plurality of control decisions generated by the one or more autonomous operation features in response to sensor data from the one or more sensors, wherein the plurality of control decisions includes, for each of a plurality of times during vehicle operation: (i) an implemented control decision implemented to control the vehicle and (ii) one or more unimplemented control decisions generated by the one or more autonomous operation features but not implemented to control the vehicle, the unimplemented control decisions indicating alternative control actions for controlling the vehicle; and
determine at least one risk level indicative of effectiveness of operation of the one or more autonomous operation features in controlling the vehicle based at least in part upon the operating data, including an indication of operating conditions of the vehicle in the information from the one or more sensors.

9. The computer system of claim 8 , wherein the one or more unimplemented control decisions further include at least one control decision not implemented because the autonomous operation feature was disabled.

10. The computer system of claim 8 , wherein the executable instructions further cause the computer system to:
determine responses of the vehicle to the implemented control decision and predicted responses of the vehicle to the one or more unimplemented control decisions; and
adjust the at least one risk level based upon received actual loss data, the responses of the vehicle to the implemented control decision, and the predicted responses of the vehicle to the one or more unimplemented control decisions.

11. The computer system of claim 8 , wherein:
each entry in a log of the operating data includes a timestamp associated with the recorded operating data, including information regarding at least one of the following: date, time, location, vehicle environment, vehicle condition, autonomous operation feature settings, or autonomous operation feature configuration information.

12. The computer system of claim 11 , wherein the executable instructions further cause the computer system to:
receive external data regarding the vehicle environment for each entry in the log of the operating data based upon the timestamp associated with the entry, including information regarding at least one of the following: road conditions, weather conditions, nearby traffic conditions, type of road, construction conditions, presence of pedestrians, presence of other obstacles, or availability of autonomous communications from external sources; and
the at least one risk level is further determined based at least in part upon the external data regarding the vehicle environment.

13. The computer system of claim 8 , further comprising a wireless network, wherein:
at least one of the one or more processors is disposed within a networked server communicatively connected to the vehicle via the wireless network; and
the executable

Assignees

• State Farm Mutual Automobile Insurance Co

Inventors

• Konrardy Blake
• Christensen Scott T
• Hayward Gregory
• Farris Scott

Classifications

• G06Q40/08 Primary

  Insurance · CPC title

• B60Q9/00

  Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 {, e.g. haptic signalling} · CPC title

• B60R21/00

  Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks (safety belts or body harnesses in vehicles B60R22/00; seats constructed to protect the occupant from the effect of abnormal g-forces, e.g. crash or safety seats, B60N2/42; energy-absorbing arrangements for hand wheels for steering vehicles B62D1/11; energy-absorbing arrangements for vehicle steering columns B62D1/19) · CPC title

• B60W30/16

  Control of distance between vehicles, e.g. keeping a distance to preceding vehicle · CPC title

• B60W40/09

  Driving style or behaviour · CPC title