Autonomous vehicle control assessment and selection

• US 10,266,180 B1
• Filed: 11/06/2015
• Issued: 04/23/2019
• Est. Priority Date: 11/13/2014
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Fields, Brian Mark, Huang, Chien Che, Wazeer, Mohamed A, Bennett, Shawn C., Cielocha, Steven C., Bryant, Ronny S., Kohaus, Stephen, Quakenbush, Terry, Novak, Richard A., Chan, Aaron Scott, Main, Craig M., Wu, Weixin, Wollenschlager, Torri, Csanda, Carol Marie, Gorsuch, Stacey, Binion, Todd
• Primary Examiner(s): Black, Thomas G
• Assistant Examiner(s): Huynh, Luat T
• Application Number:
  US14/934,393
• Time in Patent Office: 1,264 Days
• Field of Search: 701 23
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/6893 Cars
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: B60K 35/00 Instruments specially adapted for vehicles; Arrangement of instruments in or on vehicles
• CPC Class Codes: B60W 10/04 including control of propulsion units
• CPC Class Codes: B60W 2040/0809 Driver authorisation; Driver identity check
• CPC Class Codes: B60W 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2050/0071 Controller overrides driver automatically
• CPC Class Codes: B60W 2050/0073 Driver overrides controller
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2050/0215 Sensor drifts or sensor failures
• CPC Class Codes: B60W 2050/046 involving external transmission of data to or from the vehicle, e.g. via telemetry, satellite, Global Positioning System [GPS]
• CPC Class Codes: B60W 2050/143 Alarm means
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2540/26 Incapacity
• CPC Class Codes: B60W 2556/45 : External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2756/10 : Involving external transmission of data to or from the vehicle
• CPC Class Codes: B60W 2900/00 : Indexing codes relating to the purpose of, or problem solved of road vehicle drive control systems not otherwise provided for in groups B60W30/00
• CPC Class Codes: B60W 30/06 : Automatic manoeuvring for parking
• CPC Class Codes: B60W 30/09 : Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/0956 : the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: B60W 40/02 : related to ambient conditions
• CPC Class Codes: B60W 40/08 : related to drivers or passengers
• CPC Class Codes: B60W 40/09 : Driving style or behaviour
• CPC Class Codes: B60W 50/02 : Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
• CPC Class Codes: B60W 50/0205 : Diagnosing or detecting failures; Failure detection models
• CPC Class Codes: B60W 50/045 : Monitoring control system parameters
• CPC Class Codes: B60W 50/082 : Selecting or switching between different modes of propelling
• CPC Class Codes: B60W 50/12 : Limiting control by the driver depending on vehicle state, e.g. interlocking means for the control input for preventing unsafe operation
• CPC Class Codes: B60W 50/14 : Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 60/0053 : from vehicle to occupant
• CPC Class Codes: B60W 60/0059 : Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
• CPC Class Codes: B60W 60/007 : Emergency override Handing over between remote control and on-board control or handing over between remote control arrangements G05D1/227
• CPC Class Codes: B62D 15/0285 : Parking performed automatically
• CPC Class Codes: G01C 21/3407 : specially adapted for specific applications
• CPC Class Codes: G05D 1/0055 : with safety arrangements
• CPC Class Codes: G05D 1/0214 : in accordance with safety or protection criteria, e.g. avoiding hazardous areas monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13
• CPC Class Codes: G05D 1/0278 : using satellite positioning signals, e.g. GPS
• CPC Class Codes: G06F 8/65 : Updates security arrangements therefor G06F21/57
• CPC Class Codes: G06Q 30/0206 : Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0207 : Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0217 : involving input on products or services in exchange for incentives or rewards
• CPC Class Codes: G06Q 40/08 : Insurance
• 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 5/0808 : Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G08B 25/10 : using wireless transmission systems G08B25/009 takes precedence
• CPC Class Codes: G08G 1/091 : Traffic information broadcasting broadcasting communication H04H
• CPC Class Codes: G08G 1/0962 : having an indicator mounted inside the vehicle, e.g. giving voice messages
• CPC Class Codes: G08G 1/14 : indicating individual free spaces in parking areas

Abstract

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With a vehicle owner'"'"'s permission, a vehicle operator identity may be determined; and operating data regarding the autonomous or semi-autonomous vehicle may be received from one or more vehicle-mounted sensors. Based upon the received operating data, (i) autonomous operation risk levels associated with autonomous vehicle operation; and (ii) operator risk levels associated with autonomous vehicle operation by the vehicle operator may be determined. Based upon a comparison of the autonomous operation versus vehicle operator risk levels, the autonomous features may be engaged if it is safer for the vehicle to travel autonomously. Insurance discounts may be provided to risk averse vehicle owners having this safety functionality.

Claims

1. A computer-implemented method for operating an autonomous or semi-autonomous vehicle, comprising:

receiving, at one or more processors, operating data regarding the autonomous or semi-autonomous vehicle, wherein the operating data includes data from one or more sensors disposed within the autonomous or semi-autonomous vehicle regarding a current operating environment of the autonomous or semi-autonomous vehicle;

determining, by one or more processors, one or more autonomous operation risk levels associated with operation of the autonomous or semi-autonomous vehicle by one or more autonomous operation features based upon the received operating data, wherein the one or more autonomous operation risk levels indicate current risk for control of an aspect of vehicle operation within the current operating environment by the one or more autonomous operation features;

determining, by one or more processors, one or more operator risk levels associated with operation of the autonomous or semi-autonomous vehicle by the vehicle operator based upon the received operating data, wherein the one or more operator risk levels indicate current risk for control of the aspect of vehicle operation within the current operating environment by the vehicle operator;

determining, by one or more processors, to engage at least one of the one or more autonomous operation features based upon a comparison of (i) the determined one or more autonomous operation risk levels and (ii) the determined one or more operator risk levels; and

causing, by one or more processors, the at least one of the one or more autonomous operation features to engage.

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

determining, by one or more processors, an identity of a vehicle operator;

receiving, at one or more processors, a vehicle operator profile associated with the vehicle operator; and

presenting, by one or more processors, an alert to the vehicle operator regarding engagement of the at least one of the one or more autonomous operation features;

and wherein the one or more operator risk levels associated with operation of the autonomous or semi-autonomous vehicle by the vehicle operator are determined further based upon data stored within the vehicle operator profile.

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

receiving, by one or more processors, autonomous communication data from one or more external sources,

wherein determining to engage at least one of the one or more autonomous operation features is further based upon the received autonomous communication data.

4. The computer-implemented method of claim 1, wherein determining the one or more operator risk levels includes determining, by one or more processors, an attentiveness level of the vehicle operator.

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

causing, by one or more processors, an option to override the determination to engage the at least one of the one or more autonomous operation features to be presented to the vehicle operator;

receiving, at one or more processors, a selection of the option to override the determination to engage the at least one of the one or more autonomous operation features;

causing, by one or more processors, the at least one of the one or more autonomous operation features to either (i) be prevented from being disengaged or (ii) be reengaged; and

adjusting, by one or more processors, one or more costs associated with an insurance policy associated with the vehicle operator based upon the selection of the option to override the determination to engage the at least one of the one or more autonomous operation features.

6. The computer-implemented method of claim 1, further comprising adjusting, by one or more processors, one or more costs associated with an insurance policy associated with the vehicle operator based upon the determination to engage the at least one of the one or more autonomous operation features based upon the determined one or more autonomous operation risk levels and the one or more operator risk levels.

7. The computer-implemented method of claim 1, further comprising adjusting, by one or more processors, one or more insurance policies based upon the determined one or more autonomous operation risk levels and the determined one or more operator risk levels, wherein the one or more insurance policies include at least one of:

a vehicle insurance policy, a life insurance policy, home insurance policy, a rental insurance policy, a condominium insurance policy, a disability insurance policy, a business insurance policy, a health insurance policy, or a liability insurance policy.

8. The computer-implemented method of claim 1, wherein the operating data includes data regarding the vehicle environment, including one or more of the following:

traffic conditions, construction, road integrity, type of road, geographical location, time of day, precipitation, visibility, light levels, wind, or other weather conditions.

9. The computer-implemented method of claim 1, wherein a default vehicle operator profile is received as the vehicle operator profile when the vehicle operator cannot be identified as a known vehicle operator.

10. A computer system for operating an autonomous or semi-autonomous vehicle, comprising:

one or more processors;

one or more sensors disposed within the autonomous or semi-autonomous vehicle and communicatively connected to the one or more processors; 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 operating data regarding the autonomous or semi-autonomous vehicle, wherein the operating data includes data from one or more sensors disposed within the autonomous or semi-autonomous vehicle regarding a current operating environment of the autonomous or semi-autonomous vehicle;

determine one or more autonomous operation risk levels associated with operation of the autonomous or semi-autonomous vehicle by one or more autonomous operation features based upon the received operating data, wherein the one or more autonomous operation risk levels indicate current risk for control of an aspect of vehicle operation within the current operating environment by the one or more autonomous operation features;

determine one or more operator risk levels associated with operation of the autonomous or semi-autonomous vehicle by the vehicle operator based upon the received operating data, wherein the one or more operator risk levels indicate current risk for control of the aspect of vehicle operation within the current operating environment by the vehicle operator;

determine to engage at least one of the one or more autonomous operation features based upon a comparison of (i) the determined one or more autonomous operation risk levels and (ii) the determined one or more operator risk levels; and

cause the at least one of the one or more autonomous operation features to engage.

11. The computer system of claim 10, wherein the program memory further stores executable instructions that cause the computer system to:

determine an identity of a vehicle operator;

receive a vehicle operator profile associated with the vehicle operator; and

present an alert to the vehicle operator regarding engagement of the at least one of the one or more autonomous operation features;

and wherein the one or more operator risk levels associated with operation of the autonomous or semi-autonomous vehicle by the vehicle operator are determined further based upon data stored within the vehicle operator profile.

12. The computer system of claim 10, wherein the executable instructions that cause the computer system to determine the one or more operator risk levels cause the computer system to determine an attentiveness level of the vehicle operator.

13. The computer system of claim 10, wherein the program memory further stores executable instructions that cause the computer system to:

cause an option to override the determination to engage the at least one of the one or more autonomous operation features to be presented to the vehicle operator;

receive a selection of the option to override the determination to engage the at least one of the one or more autonomous operation features;

cause the at least one of the one or more autonomous operation features to either (i) be prevented from being disengaged or (ii) be reengaged; and

adjust one or more costs associated with an insurance policy associated with the vehicle operator based upon the selection of the option to override the determination to engage the at least one of the one or more autonomous operation features.

14. The computer system of claim 10, wherein the program memory further stores executable instructions that cause the computer system to:

adjust one or more costs associated with an insurance policy associated with the vehicle operator based upon the determination to engage the at least one of the one or more autonomous operation features based upon the determined one or more autonomous operation risk levels and the one or more operator risk levels.

15. A tangible, non-transitory computer-readable medium storing executable instructions for operating an autonomous or semi-autonomous vehicle that, when executed by at least one processor of a computer system, cause the computer system to:

receive operating data regarding the autonomous or semi-autonomous vehicle, wherein the operating data includes data from one or more sensors disposed within the autonomous or semi-autonomous vehicle regarding the current operating environment of the autonomous or semi-autonomous vehicle;

determine one or more autonomous operation risk levels associated with operation of the autonomous or semi-autonomous vehicle by one or more autonomous operation features based upon the received operating data, wherein the one or more autonomous operation risk levels indicate current risk for control of an aspect of vehicle operation within the current operating environment by the one or more autonomous operation features;

determine one or more operator risk levels associated with operation of the autonomous or semi-autonomous vehicle by the vehicle operator based upon the received operating data, wherein the one or more operator risk levels indicate current risk for control of the aspect of vehicle operation within the current operating environment by the vehicle operator;

determine to engage at least one of the one or more autonomous operation features based upon a comparison of (i) the determined one or more autonomous operation risk levels and (ii) the determined one or more operator risk levels; and

cause the at least one of the one or more autonomous operation features to engage.

16. The tangible, non-transitory computer-readable medium of claim 15, further storing executable instructions that cause the computer system to:

determine an identity of a vehicle operator;

receive a vehicle operator profile associated with the vehicle operator; and

present an alert to the vehicle operator regarding engagement of the at least one of the one or more autonomous operation features;

and wherein the one or more operator risk levels associated with operation of the autonomous or semi-autonomous vehicle by the vehicle operator are determined further based upon data stored within the vehicle operator profile.

17. The tangible, non-transitory computer-readable medium of claim 15, wherein the executable instructions that cause the computer system to determine the one or more operator risk levels cause the computer system to determine an attentiveness level of the vehicle operator.

18. The tangible, non-transitory computer-readable medium of claim 15, further storing executable instructions that cause the computer system to:

cause an option to override the determination to engage the at least one of the one or more autonomous operation features to be presented to the vehicle operator;

receive a selection of the option to override the determination to engage the at least one of the one or more autonomous operation features;

cause the at least one of the one or more autonomous operation features to either (i) be prevented from being disengaged or (ii) be reengaged; and

adjust one or more costs associated with an insurance policy associated with the vehicle operator based upon the selection of the option to override the determination to engage the at least one of the one or more autonomous operation features.

19. The tangible, non-transitory computer-readable medium of claim 15, further storing executable instructions that cause the computer system to:

adjust one or more costs associated with an insurance policy associated with the vehicle operator based upon the determination to engage the at least one of the one or more autonomous operation features based upon the determined one or more autonomous operation risk levels and the one or more operator risk levels.

20. The tangible, non-transitory computer-readable medium of claim 15, wherein the operating data includes data regarding the vehicle environment, including one or more of the following:

traffic conditions, construction, road integrity, type of road, geographical location, time of day, precipitation, visibility, light levels, wind, or other weather conditions.