Autonomous feature use monitoring and insurance pricing

• US 10,354,330 B1
• Filed: 05/15/2015
• Issued: 07/16/2019
• Est. Priority Date: 05/20/2014
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Konrardy, Blake, Christensen, Scott T., Hayward, Gregory, Farris, Scott
• Primary Examiner(s): Fu, Hao
• Application Number:
  US14/713,188
• Time in Patent Office: 1,523 Days
• Field of Search: 705 4
• CPC Class Codes: B60Q 11/005 for lighting devices, e.g. indicating if lamps are burning or not
• CPC Class Codes: B60Q 9/00 Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 , e.g. haptic signalling
• CPC Class Codes: B60R 2021/0027 Post collision measures, e.g. notifying emergency services
• CPC Class Codes: B60R 21/00 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; devices, apparatus or methods for life-saving in general A62B; safety devices for propulsion unit control specially adapted for, or arranged in, vehicles B60K28/00; 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; harnessing in aircraft B64D25/00
• CPC Class Codes: B60W 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2050/0095 Automatic control mode change
• CPC Class Codes: B60W 2050/0096 Control during transition between modes
• CPC Class Codes: B60W 30/16 Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 15/931 of land vehicles
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 19/13 Receivers
• CPC Class Codes: G01S 19/48 by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
• CPC Class Codes: G01S 2013/9318 Controlling the steering
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 20/0855 involving a third party
• CPC Class Codes: G06Q 40/04 : Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/08 : Insurance
• CPC Class Codes: G06Q 50/40 : Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G06V 20/597 : Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G07C 5/008 : communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/08 : Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
• CPC Class Codes: G07C 5/0808 : Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/0816 : Indicating performance data, e.g. occurrence of a malfunction
• CPC Class Codes: G07C 5/085 : using electronic data carriers
• CPC Class Codes: G08B 21/06 : indicating a condition of sleep, e.g. anti-dozing alarms
• CPC Class Codes: G08B 25/08 : using communication transmission lines G08B13/19658, G08B21/0286, G08B25/016 take precedence
• CPC Class Codes: G08G 1/005 : including pedestrian guidance indicator
• CPC Class Codes: G08G 1/096725 : where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 : where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/09675 : where a selection from the received information takes place in the vehicle
• CPC Class Codes: G08G 1/096758 : where no selection takes place on the transmitted or the received information
• CPC Class Codes: G08G 1/096775 : where the origin of the information is a central station
• CPC Class Codes: G08G 1/096783 : where the origin of the information is a roadside individual element
• CPC Class Codes: G08G 1/096791 : where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/143 : inside the vehicles
• CPC Class Codes: G08G 1/147 : where the parking area is within an open public zone, e.g. city centre
• CPC Class Codes: G08G 1/164 : Centralised systems, e.g. external to vehicles
• CPC Class Codes: G08G 1/165 : for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 : for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: G08G 1/205 : Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
• CPC Class Codes: H04L 67/12 : specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 4/44 : for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
• CPC Class Codes: H04W 4/46 : for vehicle-to-vehicle communication [V2V]
• CPC Class Codes: H04W 4/90 : Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]

Abstract

Methods and systems for monitoring use and determining risk associated with operation of autonomous vehicles are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, and operating data regarding vehicle operation may be obtained. The operating data may include information regarding use levels or settings associated with use of the autonomous operation features. Risk levels associated with the features may be determined from test data or actual loss data. The risk levels and operating data may be used to determine a total risk level associated with operation of the vehicle with expected use levels of the autonomous operation features. The total risk level may further be used to determine or adjust aspects of an insurance policy associated with the vehicle.

Claims

1. A computer-implemented method for monitoring use and evaluating effectiveness of a vehicle having one or more autonomous operation features, comprising:

generating, by one or more test units configured to simultaneously test a plurality of autonomous operation features, test results for the plurality of autonomous operation features including a plurality of versions of computer-readable instructions of at least one of the one or more autonomous operation features of the vehicle, wherein the test units generate the test results as control commands generated by the one or more autonomous operation features of the test units in response to test sensor data that simulates sensor data for an autonomous vehicle operating under a plurality of operating conditions within a virtual test environment;

receiving, at one or more processors, information regarding the one or more autonomous operation features of the vehicle, the information identifying the one or more autonomous operation features of the vehicle, including an indication of a current version of the plurality of versions of the at least one of the one or more autonomous operation features;

monitoring, at one or more processors, operation of the vehicle by collecting operating data regarding operation of the vehicle during vehicle operation, wherein the operating data includes (i) information from one or more sensors disposed within the vehicle to generate sensor data regarding movement of the vehicle and objects within an operating environment of the vehicle and (ii) information regarding the operation of the one or more autonomous operation features, including an indication of a current version of the plurality of versions of computer-readable instructions of the at least one of the one or more autonomous operation features;

determining, by one or more processors, one or more autonomous operation risk levels associated with operation of the vehicle in each of the plurality of operating conditions based upon the information regarding the one or more autonomous operation features and the test results generated by the one or more test units;

determining, by one or more processors, one or more use levels indicating extent of actual use of each of the one or more autonomous operation features associated with each of the plurality of operating conditions, and further indicating extent of use of a user-adjustable setting for at least one of the one or more autonomous operation features; and

generating, by one or more processors, a total quality metric indicating effectiveness of control logic implemented by the one or more autonomous operation features under the plurality of operating conditions based at least in part upon the determined one or more autonomous operation risk levels, the determined one or more use levels, and the operating data.

2. The method of claim 1, wherein receiving information regarding the one or more autonomous operation features of the vehicle further comprises:

receiving, at one or more processors, information regarding baseline risk levels corresponding to the test results for the one or more autonomous operation features regarding operation of the one or more autonomous operation features in a simulated test environment.

3. The method of claim 2, wherein determining the one or more autonomous operation risk levels further comprises:

receiving, at one or more processors, loss data regarding a plurality of vehicles having at least one of the one or more autonomous operation features, wherein the loss data includes one or more of the following;

claims for payments under a plurality of vehicle insurance policies related to the plurality of vehicles, actual payments under the plurality of vehicle insurance policies related to the plurality of vehicles, or indications of collisions from sensor data for the plurality of vehicles; and

determining, by one or more processors, the one or more autonomous operation risk levels based upon a correlation between the baseline risk levels and the loss data.

4. The method of claim 3, wherein determining the one or more use levels includes:

determining, by one or more processors, the use levels of the autonomous operation features based upon the operating data, wherein the use levels include separate levels for at least two alternative values of an adjustable setting of the at least one of the autonomous operation features.

5. The method of claim 1, wherein monitoring operation of the vehicle by collecting operating data of the vehicle further comprises:

receiving, at one or more processors, an indication of operation of the vehicle, including one or more times and one or more locations corresponding to an occurrence of operation of the vehicle; and

receiving, at one or more processors, information regarding settings of the one or more autonomous operation features during operation.

6. The method of claim 5, wherein monitoring operation of the vehicle by collecting operating data of the vehicle further comprises:

monitoring, at one or more processors, information regarding the vehicle'"'"'s environment during operation, wherein the information regarding the vehicle'"'"'s environment includes one or more of the following;

road conditions, weather conditions, nearby traffic conditions, type of road, construction conditions, location of pedestrians, movement of pedestrians, movement of other obstacles, signs, traffic signals, or availability of autonomous communications from external sources.

7. The method of claim 1, further comprising:

receiving, at one or more processors, a request for a quote of a premium associated with a vehicle insurance policy;

determining, by one or more processors, a premium associated with the vehicle insurance policy based at least in part upon a total risk level associated with the total quality metric; and

presenting, by one or more processors, an option to purchase the vehicle insurance policy to a customer associated with the vehicle.

8. The method of claim 1, wherein the information from one or more sensors comprises autonomous communications from other vehicles having autonomous operation features.

9. The method of claim 1, wherein the information regarding the one or more autonomous operation features comprises one or more of the following:

a type and version of the autonomous operation feature, an operation of the autonomous operation feature, a type and version of autonomous operation feature control software, or settings of the autonomous operation feature.

10. A computer system for monitoring use and evaluating effectiveness of a vehicle having one or more autonomous operation features, comprising:

one or more processors;

one or more sensors disposed within the vehicle;

one or more communication modules adapted to communicate data;

one or more test units configured to simultaneously test a plurality of autonomous operation features and to generate test results for the plurality of autonomous operation features including a plurality of versions of computer-readable instructions of at least one of the one or more autonomous operation features of the vehicle, wherein the test units generate the test results as control commands generated by the one or more autonomous operation features of the test units in response to test sensor data that simulates sensor data for an autonomous vehicle operating under a plurality of operating conditions within a virtual test environment, and wherein the test results are communicated to the one or more processors via the one or more communication modules; and

a 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;

receive information regarding the one or more autonomous operation features of the vehicle, the information identifying the one or more autonomous operation features of the vehicle, including an indication of a current version of the plurality of versions of the at least one of the one or more autonomous operation features;

monitor operation of the vehicle by collecting operating data regarding operation of the vehicle from the one or more communication modules during vehicle operation, wherein the operating data includes (i) information from one or more sensors disposed within the vehicle to generate sensor data regarding movement of the vehicle and objects within an operating environment of the vehicle and (ii) information regarding the operation of the one or more autonomous operation features, including an indication of a current version of the plurality of versions of computer-readable instructions of the at least one of the one or more autonomous operation features;

determine one or more autonomous operation risk levels associated with operation of the vehicle in each of the plurality of operating conditions based upon the information regarding the one or more autonomous operation features and the test results generated by the one or more test units;

determine one or more use levels indicating extent of actual use of each of the one or more autonomous operation features associated with each of the plurality of operating conditions, and further indicating extent of use of a user-adjustable setting for at least one of the one or more autonomous operation features; and

generate a total quality metric indicating effectiveness of control logic implemented by the one or more autonomous operation features under the plurality of operating conditions based at least in part upon the determined one or more autonomous operation risk levels, the determined one or more use levels, and the operating data.

11. The computer system of claim 10, wherein the information regarding the one or more autonomous operation features includes information regarding baseline risk levels corresponding to the test results for the one or more autonomous operation features regarding operation of the one or more autonomous operation features in a test environment.

12. The computer system of claim 11, wherein the executable instructions further cause the computer system to:

receive loss data regarding a plurality of vehicles having at least one of the one or more autonomous operation features, wherein the loss data includes one or more of the following;

claims for payments under a plurality of vehicle insurance policies related to the plurality of vehicles, actual payments under the plurality of vehicle insurance policies related to the plurality of vehicles, or indications of collisions from sensor data for the plurality of vehicles; and

determine the one or more autonomous operation risk levels based upon a correlation between the baseline risk levels and the loss data.

13. The computer system of claim 10, wherein the operating data further includes an indication of operation of the vehicle, including one or more times and one or more locations corresponding to an occurrence of operation of the vehicle and information regarding settings of the one or more autonomous operation features during operation.

14. The computer system of claim 10, wherein the one or more communication modules are further adapted to send or receive autonomous communications between the vehicle and one or more of other autonomous vehicles, infrastructure, map databases, weather databases, traffic, or accident databases.

15. A tangible, non-transitory computer-readable medium storing instructions for monitoring use and evaluating effectiveness of a vehicle having one or more autonomous operation features that, when executed by at least one processor of a computer system, cause the computer system to:

generate test results for a plurality of autonomous operation features including a plurality of versions of computer-readable instructions of at least one of the one or more autonomous operation features of the vehicle using one or more test units configured to simultaneously test the plurality of autonomous operation features, wherein the test units generate the test results as control commands generated by the one or more autonomous operation features of the test units in response to test sensor data that simulates sensor data for an autonomous vehicle operating under a plurality of operating conditions within a virtual test environment;

receive information regarding the one or more autonomous operation features of the vehicle, the information identifying the one or more autonomous operation features of the vehicle, including an indication of a current version of the plurality of versions of the at least one of the one or more autonomous operation features;

monitor operation of the vehicle by collecting operating data regarding operation of the vehicle during vehicle operation, wherein the operating data includes (i) information from one or more sensors disposed within the vehicle to generate sensor data regarding movement of the vehicle and objects within an operating environment of the vehicle and (ii) information regarding the operation of the one or more autonomous operation features, including an indication of a current version of the plurality of versions of computer-readable instructions of the at least one of the one or more autonomous operation features;

determine one or more autonomous operation risk levels associated with operation of the vehicle in each of the plurality of operating conditions based upon the information regarding the one or more autonomous operation features and the test results generated by the one or more test units;

determine one or more use levels indicating extent of actual use of each of the one or more autonomous operation features associated with each of the plurality of operating conditions, and further indicating extent of use of a user-adjustable setting for at least one of the one or more autonomous operation features; and

generate a total quality metric indicating effectiveness of control logic implemented by the one or more autonomous operation features under the plurality of operating conditions based at least in part upon the determined one or more autonomous operation risk levels, the determined one or more use levels, and the operating data.

16. The tangible, non-transitory computer-readable medium of claim 15, wherein:

the information regarding the one or more autonomous operation features includes information regarding baseline risk levels corresponding to the test results for the one or more autonomous operation features regarding operation of the one or more autonomous operation features in a test environment;

the executable instructions that, when executed by the at least one processor, cause the computer system to determine the one or more autonomous operation risk levels further comprise executable instructions that, when executed by the at least one processor, cause the computer system to;

receive loss data regarding a plurality of vehicles having at least one of the one or more autonomous operation features, wherein the loss data includes one or more of the following;

claims for payments under a plurality of vehicle insurance policies related to the plurality of vehicles, actual payments under the plurality of vehicle insurance policies related to the plurality of vehicles, or indications of collisions from sensor data for the plurality of vehicles, and

determine the one or more autonomous operation risk levels based upon a correlation between the baseline risk levels and the loss data.

17. The tangible, non-transitory computer-readable medium of claim 15, wherein the executable instructions that, when executed by the at least one processor, cause the computer system to monitor operation of the vehicle by collecting operating data of the vehicle further comprise executable instructions that, when executed by the at least one processor, cause the computer system to:

receive an indication of operation of the vehicle, including one or more times and one or more locations corresponding to an occurrence of operation of the vehicle;

receive information regarding settings of the one or more autonomous operation features during operation; and

monitor information regarding the vehicle'"'"'s environment during operation, wherein the information regarding the vehicle'"'"'s environment includes one or more of the following;

road conditions, weather conditions, nearby traffic conditions, type of road, construction conditions, location of pedestrians, movement of pedestrians, movement of other obstacles, signs, traffic signals, or availability of autonomous communications from external sources.

18. The tangible, non-transitory computer-readable medium of claim 15, wherein the information regarding the one or more autonomous operation features comprises one or more of the following:

a type and version of the autonomous operation feature, a type and version of autonomous operation feature control software, or settings of the autonomous operation feature.

19. The tangible, non-transitory computer-readable medium of claim 15, further comprising executable instructions that, when executed by at least one processor of a computer system, cause the computer system to:

receive a request for a quote of a premium associated with a vehicle insurance policy;

determine a premium associated with the vehicle insurance policy based upon a total risk level associated with the total quality metric; and

present an option to purchase the vehicle insurance policy to a customer associated with the vehicle.