Autonomous vehicle technology effectiveness determination for insurance pricing

• US 9,858,621 B1
• Filed: 05/15/2015
• Issued: 01/02/2018
• 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): Ebersman, Bruce I
• Assistant Examiner(s): BRADLEY, JOSHUA DANIEL
• Application Number:
  US14/713,237
• Time in Patent Office: 963 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 50/30 : Transportation; Communications
• 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 determining the effectiveness of one or more autonomous (and/or semi-autonomous) operation features of a vehicle are provided. According to certain aspects, information regarding autonomous operation features of the vehicle may be used to determine an effectiveness metric indicative of the ability of each autonomous operation feature to avoid or mitigate accidents or other losses. The information may include operating data from the vehicle or other vehicles having similar autonomous operation features, test data, or loss data from other vehicles. The determined effectiveness metric may then be used to determine part or all of an insurance policy, which may be reviewed by an insured and updated based upon the effectiveness metric.

Claims

1. A computer-implemented method of evaluating effectiveness of an autonomous or semi-autonomous vehicle technology for controlling a vehicle to avoid or mitigate vehicle accidents, the method comprising:

receiving, at one or more processors, information regarding the autonomous or semi-autonomous vehicle technology of the vehicle;

generating, by one or more computing systems configured to evaluate the autonomous or semi-autonomous vehicle technology operating within a virtual test environment configured to simultaneously test at least one additional autonomous or semi-autonomous vehicle technologies, test results for the autonomous or semi-autonomous vehicle technology, wherein the computing systems generate the test results as hardware or software responses of the autonomous or semi-autonomous vehicle technology to virtual test sensor data that simulates sensor data for operating conditions associated with a plurality of test scenarios within the virtual test environment;

determining, by one or more processors, test data regarding the test results, including an indication of reliability of the autonomous or semi-autonomous vehicle technology based at least in part upon compatibility of a version of or an update to computer-readable instructions involved in implementation of part or all of the autonomous or semi-autonomous vehicle technology with one or more versions of the at least one additional autonomous or semi-autonomous vehicle technologies tested;

determining, by one or more processors, an effectiveness metric indicative of effectiveness of the autonomous or semi-autonomous vehicle technology in avoiding or mitigating vehicle accidents under a plurality of environmental conditions based at least in part upon the received information and the test data, wherein the effectiveness metric is associated with the version of or the update to the computer-readable instructions involved in the implementation of part or all of the autonomous or semi-autonomous vehicle technology;

determining, by one or more processors, part or all of an insurance policy associated with the vehicle based at least in part upon the effectiveness metric associated with the autonomous or semi-autonomous vehicle technology of the vehicle;

causing, by one or more processors, all or a portion of the determined insurance policy to be presented to a customer, via a display of a computing device associated with the customer, for at least one of review, approval, or modification by the customer;

receiving, by one or more processors, a response from the customer indicating at least one of approval or modification of the presented insurance policy; and

updating, by one or more processors, the determined insurance policy associated with the vehicle based at least in part upon the response received from the customer.

2. The computer-implemented method of claim 1, wherein the plurality of environmental conditions include one or more real-world driving conditions that impact at least one of a likelihood of occurrence of vehicle accidents or a severity of vehicle accidents.

3. The computer-implemented method of claim 1, wherein determining the effectiveness metric indicative of effectiveness of the autonomous or semi-autonomous vehicle technology in avoiding or mitigating vehicle accidents under a plurality of environmental conditions further includes analyzing information regarding a plurality of vehicle accidents involving one or more vehicles having the autonomous or semi-autonomous vehicle technology.

4. The computer-implemented method of claim 1, wherein updating the insurance policy includes adjusting at least one of the following costs associated with the insurance policy:

a premium, a discount, or a reward.

5. The computer-implemented method of claim 1, wherein the effectiveness metric is associated with the update to the computer-readable instructions involved in the implementation of part or all of the autonomous or semi-autonomous vehicle technology.

6. The computer-implemented method of claim 5, further comprising testing the update to the computer-readable instructions involved in the implementation of part or all of the autonomous or semi-autonomous vehicle technology;

wherein the effectiveness metric is determined based at least in part upon results of the testing.

7. The computer-implemented method of claim 6, wherein determining the effectiveness metric includes determining whether at least one of a change in accident avoidance or a change in mitigation effectiveness of the autonomous or semi-autonomous vehicle technology has occurred, based at least in part upon the results of the testing of the updated computer-readable instructions involved in the implementation of part or all of the autonomous or semi-autonomous vehicle technology.

8. A computer-implemented method of evaluating effectiveness of an autonomous or semi-autonomous vehicle technology for controlling a vehicle to avoid or mitigate vehicle accidents, the method comprising:

generating, by one or more computing systems configured to evaluate the autonomous or semi-autonomous vehicle technology operating within a virtual test environment configured to simultaneously test at least one additional autonomous or semi-autonomous vehicle technologies, test results for the autonomous or semi-autonomous vehicle technology, wherein the computing systems generate the test results as hardware or software responses of the autonomous or semi-autonomous vehicle technology to virtual test sensor data that simulates sensor data for operating conditions associated with a plurality of test scenarios within the virtual test environment;

determining, by one or more processors, test data regarding the test results, including an indication of reliability of the autonomous or semi-autonomous vehicle technology based at least in part upon compatibility of a version of or update to computer-readable instructions involved in implementation of part or all of the autonomous or semi-autonomous vehicle technology with one or more versions of the at least one additional autonomous or semi-autonomous vehicle technologies tested;

receiving, by one or more processors, risk-related information regarding at least one of the following;

the vehicle, the autonomous or semi-autonomous vehicle technology, usage of the vehicle, or usage of the autonomous or semi-autonomous vehicle technology, wherein the risk-related information includes the test data regarding the test results;

determining, by one or more processors, part or all of an insurance policy associated with the vehicle based at least in part upon the received risk-related information including the test data;

causing, by one or more processors, all or a portion of the determined insurance policy to be presented to a customer, by a display of a computing device associated with the customer, for at least one of review, approval, or modification by the customer;

receiving, by one or more processors, a response from the customer indicating at least one of approval or modification of the presented insurance policy; and

updating, by one or more processors, the insurance policy based at least in part upon the response received from the customer.

9. The computer-implemented method of claim 8, wherein determining part or all of the insurance policy associated with the vehicle includes at least one of updating, adjusting, or generating the insurance policy based at least in part upon information regarding one or more of the following:

(i) the autonomous or semi-autonomous vehicle technology, (ii) environmental conditions impacting an effectiveness of the autonomous or semi-autonomous vehicle technology, (iii) actual operation of the vehicle, or (iv) actual operation of one or more components of the autonomous or semi-autonomous vehicle technology.

10. The computer-implemented method of claim 8, wherein the risk-related information regarding the autonomous or semi-autonomous vehicle technology includes information regarding the version of the computer-readable instructions involved in the implementation of part or all of the autonomous or semi-autonomous vehicle technology.

11. The computer-implemented method of claim 8, wherein determining part or all of the insurance policy associated with the vehicle includes:

estimating, by one or more processors, a risk factor associated with the insurance policy based at least in part upon at least one of the following (i) the autonomous or semi-autonomous vehicle technology;

or (ii) one or more accident-related conditions that impact an effectiveness of the autonomous or semi-autonomous vehicle technology;

at least one of generating, updating, or adjusting the insurance policy based at least in part upon at least one of the following;

(i) the estimated risk factor associated with the insurance policy, or (ii) information regarding actual operation of the vehicle by a vehicle operator.

12. The computer-implemented method of claim 11, wherein the information regarding actual operation of the vehicle includes information from one or more sensors disposed within the vehicle regarding at least one of the following:

typical driving patterns, typical routes, geographic location of vehicle operation, type of vehicle trips, duration of vehicle trips, time of day of vehicle trips, or traffic congestion during typical vehicle trips.

13. The computer-implemented method of claim 8, wherein determining part or all of the insurance policy associated with the vehicle includes:

determining, by one or more processors, an accident risk factor associated with the vehicle based at least in part upon the received risk-related information, including accident-related conditions impacting an effectiveness of the autonomous or semi-autonomous vehicle technology.

14. The computer-implemented method of claim 8, wherein determining part or all of the insurance policy associated with the vehicle includes:

determining, by one or more processors, the insurance policy based at least in part upon information regarding an impact on an effectiveness of the autonomous or semi-autonomous vehicle technology of at least one of actual operating conditions or actual operating behavior of a vehicle operator associated with the vehicle.

15. The computer-implemented method of claim 14, wherein the information regarding the impact on the effectiveness of the autonomous or semi-autonomous vehicle technology includes information regarding at least one of the following:

typical driving patterns, typical routes, geographic location of vehicle operation, type of vehicle trips, duration of vehicle trips, time of day of vehicle trips, traffic congestion during typical vehicle trips, typical daily commute, typical weather conditions during usage of the vehicle, typical seasonal usage of the vehicle, or body type of the vehicle.

16. The computer-implemented method of claim 8, wherein updating the insurance policy includes adjusting at least one of the following cost associated with the insurance policy:

a premium, a discount, or a reward.

17. The computer-implemented method of claim 8, wherein the response from the customer is received from the computing device associated with the customer by wireless communication.

18. The computer-implemented method of claim 8, wherein determining part or all of the insurance policy associated with the vehicle includes determining at least one of the following:

a premium, a rate, a risk category, a risk category level, a discount, or a reward.

19. A tangible, non-transitory computer-readable medium storing instructions for evaluating effectiveness of an autonomous or semi-autonomous vehicle technology for controlling a vehicle to avoid or mitigate vehicle accidents that, when executed by at least one processor of a computer system, cause the computer system to:

generate test results for the autonomous or semi-autonomous vehicle technology, wherein the test results are generated as hardware or software responses of the autonomous or semi-autonomous vehicle technology to virtual test sensor data that simulates sensor data for operating conditions associated with a plurality of test scenarios within a virtual test environment configured to simultaneously test at least one additional autonomous or semi-autonomous vehicle technologies;

determine test data regarding the test results, including an indication of reliability of the autonomous or semi-autonomous vehicle technology based at least in part upon compatibility of a version of or update to computer-readable instructions involved in implementation of part or all of the autonomous or semi-autonomous vehicle technology with one or more versions of the at least one additional autonomous or semi-autonomous vehicle technologies tested;

receive risk-related information regarding at least one of the following;

the vehicle, the autonomous or semi-autonomous vehicle technology, usage of the vehicle, or usage of the autonomous or semi-autonomous vehicle technology, wherein the risk-related information includes the test data regarding the test results;

determine part or all of an insurance policy associated with the vehicle based at least in part upon the received risk-related information including the test data;

cause all or a portion of the determined insurance policy to be presented to a customer, by a display of a computing device associated with the customer;

receive a response from the customer indicating at least one of approval or modification of the presented insurance policy; and

update the insurance policy based at least in part upon the response received from the customer.

20. The tangible, non-transitory computer-readable medium of claim 19, wherein the information regarding actual operation of the vehicle includes information from one or more sensors disposed within the vehicle regarding at least one of the following:

typical driving patterns, typical routes, geographic location of vehicle operation, type of vehicle trips, duration of vehicle trips, time of day of vehicle trips, or traffic congestion during typical vehicle trips.