Autonomous vehicle collision risk assessment

• US 10,026,130 B1
• Filed: 05/15/2015
• Issued: 07/17/2018
• 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 D.
• Application Number:
  US14/713,184
• Time in Patent Office: 1,159 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 determining collision risk associated with operation of partially autonomous vehicles are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, including types and version of sensors, control systems, and software. This information may be used to determine collision risk levels associated with the features, which may be based upon test data regarding the features or actual collisions. Additional collision risk levels associated with operation by a vehicle operator may also be determined. Expected use levels may further be determined and used with the collision risk levels to determine a total collision risk level associated with operation of the vehicle. The expected use levels may include feature use levels set by the operator under various environmental conditions.

Claims

1. A computer-implemented method for evaluating effectiveness of one or more autonomous operation features in assisting a vehicle operator in controlling a vehicle, 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 and the information including 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;

receiving, at one or more processors from a database, information regarding the vehicle operator indicating prior vehicle usage by the vehicle operator;

determining, by one or more processors, a plurality of collision risk levels associated with autonomous operation of the vehicle under 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, including a plurality of collision risk levels associated with the plurality of versions of the at least one of the one or more autonomous operation features;

determining, by one or more processors, a plurality of expected use levels of the vehicle, wherein the expected use levels are associated with the plurality of operating conditions and wherein the expected use levels are determined based upon operating data recorded in a vehicle data log by one or more on-board computers during previous operation of one or more vehicles by the vehicle operator, such operating data including both entries in the vehicle data log storing data indicating usage of at least one autonomous operation feature from the one or more on-board computers and entries in the vehicle data log storing data indicating sensor data indicative of environmental conditions generated by one or more sensors installed in the vehicle during the previous operation;

determining, by one or more processors, an operator collision-risk profile associated with vehicle operation by the vehicle operator;

determining, by one or more processors, a total collision risk level associated with operation of the vehicle based at least in part upon the determined plurality of collision risk levels, the determined expected use levels, and the determined operator collision-risk profile; and

causing, by one or more processors, one or more of the following actions to be performed based upon the determined total collision risk level;

adjust an insurance policy associated with the vehicle, determine a coverage level associated with the insurance policy, present information regarding the determined total collision risk level to a reviewer via a display of a reviewer computing device to verify the determined total collision risk level, or present the determination to a customer via a display of a customer computing device for review of an adjustment to the insurance policy associated with the vehicle.

2. The method of claim 1, wherein:

the operator collision-risk profile includes a plurality of operator collision risk levels associated with operation of the vehicle by the vehicle operator under the plurality of operating conditions; and

the expected use levels associated with the plurality of operating conditions include information regarding expected operation of the vehicle with autonomous operation features enabled and expected operation of the vehicle with autonomous operation features disabled.

3. The method of claim 1, further comprising receiving, at one or more processors, information regarding previous use of the one or more autonomous operation features of the vehicle, and wherein the plurality of expected use levels are determined, at least in part, based upon the information regarding previous use of the one or more autonomous operation features.

4. The method of claim 3, wherein the information regarding previous use of the one or more autonomous operation features includes one or more of the following:

times, road conditions, weather conditions, or autonomous operation feature settings associated with the previous use of the autonomous operation features.

5. The method of claim 1, wherein the plurality of collision risk levels associated with the one or more autonomous operation features of the vehicle are further determined based upon data regarding actual collisions associated with a plurality of other vehicles having at least one of the one or more autonomous operation features.

6. The method of claim 1, wherein the expected use levels include one or more of (i) expected autonomous operation levels of the vehicle, (ii) expected operation of the vehicle by the vehicle operator, or (iii) expected settings associated with the one or more autonomous operation features.

7. 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 the vehicle, and

determining, by one or more processors, types of the one or more autonomous operation features and types of the one or more sensors installed in the vehicle based upon the information regarding the vehicle; and

the plurality of collision risk levels associated with autonomous operation of the vehicle are determined, at least in part, based upon the sensors installed in the vehicle.

8. A computer system for evaluating effectiveness of one or more autonomous operation features in assisting a vehicle operator in controlling a vehicle, comprising:

one or more processors;

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, and the information including 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;

receive information regarding the vehicle operator indicating prior vehicle usage by the vehicle operator from a database;

determine a plurality of collision risk levels associated with autonomous operation of the vehicle under 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, including a plurality of collision risk levels associated with the plurality of versions of the at least one of the one or more autonomous operation features;

determine a plurality of expected use levels of the vehicle, wherein the expected use levels are associated with the plurality of operating conditions and wherein the expected use levels are determined based upon operating data recorded in a vehicle data log by one or more on-board computers during previous operation of one or more vehicles by the vehicle operator, such operating data including both entries in the vehicle data log storing data indicating usage of at least one autonomous operation feature from the one or more on-board computers and entries in the vehicle data log storing data indicating sensor data indicative of environmental conditions generated by one or more sensors installed in the vehicle during the previous operation;

determine an operator collision-risk profile associated with vehicle operation by the vehicle operator;

determine a total collision risk level associated with operation of the vehicle based at least in part upon the determined plurality of collision risk levels, the determined expected use levels, and the determined operator collision-risk profile; and

cause one or more of the following actions to be performed based upon the determined total collision risk level;

adjust an insurance policy associated with the vehicle, determine a coverage level associated with the insurance policy, present information regarding the determined total collision risk level to a reviewer via a display of a reviewer computing device to verify the determined total collision risk level, or present the determination to a customer via a display of a customer computing device for review of an adjustment to the insurance policy associated with the vehicle.

9. The computer system of claim 8, wherein:

the operator collision-risk profile includes a plurality of operator collision risk levels associated with operation of the vehicle by the vehicle operator under the plurality of operating conditions; and

the expected use levels associated with the plurality of operating conditions include information regarding expected operation of the vehicle with autonomous operation features enabled and expected operation of the vehicle with autonomous operation features disabled.

10. The computer system of claim 8, wherein the executable instructions further cause the computer system to:

receive information regarding previous use of the one or more autonomous operation features of the vehicle, wherein the information regarding previous use of the one or more autonomous operation features includes one or more of the following;

times, road conditions, weather conditions, or autonomous operation feature settings associated with the previous use of the autonomous operation features; and

determine the plurality of expected use levels, at least in part, based upon the information regarding previous use of the one or more autonomous operation features.

11. The computer system of claim 8, wherein the plurality of collision risk levels associated with the one or more autonomous operation features of the vehicle are further determined based upon data regarding actual collisions associated with a plurality of other vehicles having at least one of the one or more autonomous operation features.

12. The computer system of claim 8, wherein the expected use levels include one or more of (i) expected autonomous operation levels of the vehicle, (ii) expected operation of the vehicle by a vehicle operator, or (iii) expected settings associated with the one or more autonomous operation features.

13. The computer system of claim 8, wherein the executable instructions further cause the computer system to:

receive information regarding the vehicle, and

determine types of the one or more autonomous operation features and types of the one or more sensors installed in the vehicle based upon the information regarding the vehicle; and

determine the plurality of collision risk levels associated with autonomous operation of the vehicle, at least in part, based upon the sensors installed in the vehicle.

14. A tangible, non-transitory computer-readable medium storing instructions for evaluating effectiveness of one or more autonomous operation features in assisting a vehicle operator in controlling a vehicle 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, and the information including 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;

receive information regarding the vehicle operator indicating prior vehicle usage by the vehicle operator from a database;

determine a plurality of collision risk levels associated with autonomous operation of the vehicle under 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, including a plurality of collision risk levels associated with the plurality of versions of the at least one of the one or more autonomous operation features;

determine a plurality of expected use levels of the vehicle, wherein the expected use levels are associated with the plurality of operating conditions and wherein the expected use levels are determined based upon operating data recorded in a vehicle data log by one or more on-board computers during previous operation of one or more vehicles by the vehicle operator, such operating data including both entries in the vehicle data log storing data indicating usage of at least one autonomous operation feature from the one or more on-board computers and entries in the vehicle data log storing data indicating sensor data indicative of environmental conditions generated by one or more sensors installed in the vehicle during the previous operation;

determine an operator collision-risk profile associated with vehicle operation by the vehicle operator;

determine a total collision risk level associated with operation of the vehicle based at least in part upon the determined plurality of collision risk levels, the determined expected use levels, and the determined operator collision-risk profile; and

cause one or more of the following actions to be performed based upon the determined total collision risk level;

adjust an insurance policy associated with the vehicle, determine a coverage level associated with the insurance policy, present information regarding the determined total collision risk level to a reviewer via a display of a reviewer computing device to verify the determined total collision risk level, or present the determination to a customer via a display of a customer computing device for review of an adjustment to the insurance policy associated with the vehicle.

15. The tangible, non-transitory computer-readable medium of claim 14, wherein:

the operator collision-risk profile includes a plurality of operator collision risk levels associated with operation of the vehicle by the vehicle operator under the plurality of operating conditions; and

the expected use levels associated with the plurality of operating conditions include information regarding expected operation of the vehicle with autonomous operation features enabled and expected operation of the vehicle with autonomous operation features disabled.

16. The tangible, non-transitory computer-readable medium of claim 14, further comprising executable instructions that, when executed by at least one processor of a computer system, cause the computer system to:

receive information regarding previous use of the one or more autonomous operation features of the vehicle, wherein the information regarding previous use of the one or more autonomous operation features includes one or more of the following;

times, road conditions, weather conditions, or autonomous operation feature settings associated with the previous use of the autonomous operation features; and

determine the plurality of expected use levels, at least in part, based upon the information regarding previous use of the one or more autonomous operation features.

17. The tangible, non-transitory computer-readable medium of claim 14, wherein the plurality of collision risk levels associated with the one or more autonomous operation features of the vehicle are further determined based upon data regarding actual collisions associated with a plurality of other vehicles having at least one of the one or more autonomous operation features.