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2022 JUL 22 (NewsRx) — By a
The assignee for this patent, patent number 11379925, is
Reporters obtained the following quote from the background information supplied by the inventors: “Automobiles share the roads with many other automobiles. From time to time, these automobiles may be involved in a collision with another automobile or some of other object for various reasons, such as, for example, excess speed, following too closely, or simply a lack of attention.
“At least some new automobiles may include autonomous operation technology that facilitates driver-less operation of the automobile. Such autonomous vehicles may include various sensing technologies that may be used to detect the environment in which the autonomous vehicle operates. The sensing technologies may include, for example, optical sensing, radio frequency sensing, photonic, and acoustic sensing, among others. Such sensing technologies may include proximity sensing technologies that may be used to detect and indicate when the automobile gets near another automobile. Such sensor systems are generally intended to enhance the drivability and safety of the automobile. For example, some automobiles may include forward-looking and rear-looking sensors to assist in parking; side-looking sensors to facilitate blind-spot detection; side-looking sensors for lane detection; and forward looking sensors for navigation and braking systems. Autonomous vehicles may use the sensing technologies to, in some circumstances, avoid a collision among one or more other vehicles, pedestrians, cyclists, road hazards, or immovable objects.
“In the automobile insurance industry, insurance policies are crafted with a variety of considerations in mind, including, the risk a given driver (i.e., the insured) represents to an auto insurance company (i.e., the insurer). A driver represents risk to an auto insurance company in terms of, for example, the likelihood the driver will be involved in a collision. An auto insurance company may consider various other factors in quantifying the risk a given driver represents, including, for example, age, vehicle, occupation, and place of residence. Autonomous vehicles, and their owners, may have substantially different risk profiles when compared to a traditional driver. For example, autonomous vehicles may be more likely to be struck by other vehicles due to the autonomous vehicle’s overly cautious behavior. Such likelihood is further increased in urban traffic. Autonomous vehicles may respond differently to environmental conditions when compared to traditional drivers. In some cases, for example, an autonomous vehicle may lack the ability to safely adapt to unforeseen circumstances, such as downed power lines, flooding, or interference with sensing technology. In other cases, for example, an autonomous vehicle may perform more safely than a traditional driver under certain environmental conditions, such as rain, snow, or loose pavement.
“An insurance company may be more or less likely to offer certain policy features to a driver based upon their risk. For example, an insurance company may be unwilling to offer low-deductible policies to high-risk drivers. Insurance companies often determine policy premiums according to a given driver’s risk. A driver considered a low risk of collision may be offered lower premiums for a collision policy than another driver considered a higher risk of collision. Similarly, a driver who insures an expensive sports car is likely to pay higher premiums for a collision policy than another driver who insures an economy-class, four-door sedan. Likewise, an insurance company may tailor a collision policy to a particular autonomous vehicle based upon its risk profile and driving history.”
In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “The present embodiments may relate to systems and methods for allocating fault to a vehicle involved in a collision, and adjusting auto insurance rates accordingly. Many modern vehicles include various sensors for detecting the environment in which the vehicle is operating before, during, and after the collision. These sensors may include forward-looking sensors, rear-looking sensors, and side-looking sensors that may detect environmental conditions, activity of other automobiles, and activity of pedestrians. This data may be collected and analyzed to determine a fault score for the vehicle representing a percentage of fault for the collision allocated to the vehicle. In certain embodiments, further fault scores may be determined for other vehicles, pedestrians, municipalities, software providers, car makers, and environmental conditions. Fault scores may be relayed to an insurance company for adjusting an auto insurance premium based upon fault scores accumulated over time for an insured automobile, or for another entity with which a given insured automobile interacts.
“In one aspect, a system for allocating fault in a collision involving a vehicle is provided. The system may include (1) a sensor coupled to the vehicle and configured to collect contextual data related to the collision, (2) a non-transitory memory configured to store the contextual data, and (3) a processor coupled to the non-transitory memory and configured to (a) gain access to the contextual data and (b) compute and assign a fault percentage to a driver of the vehicle based upon the contextual data. The system may include additional, less, or alternate functionality, including that discussed elsewhere herein.
“In another aspect, a system for allocating fault in a collision involving an autonomous vehicle is provided. The system may include (1) a plurality of sensors coupled to the autonomous vehicle and configured to collect contextual data related to the collision, (2) a first processor coupled to the plurality of sensors and configured to: (a) execute a control program stored in a non-transitory memory to operate the autonomous vehicle, and (b) generate driving data representing operation of the autonomous vehicle by the first processor, and (3) a second processor coupled to the plurality of sensors and the first processor, the second processor configured to: (a) gain access to the contextual data and the driving data, and (b) compute a fault percentage for at least the autonomous vehicle. The system may include additional, less, or alternate functionality, including that discussed elsewhere herein.
“In yet another aspect, a method of allocating fault in a collision involving a vehicle is provided. The method may include (1) generating driving data representing operation of the vehicle, (2) detecting contextual information using a plurality of sensors affixed to the vehicle, (3) receiving contextual data representing the contextual information at a processor, and (4) processing, by the processor, the driving data and the contextual data to compute a fault score for the vehicle, the fault score representing a percentage of fault for the collision allocated to an operator of the vehicle. The method may include additional, less, or alternate functionality, including that discussed elsewhere herein, and/or may be implemented, in whole or part, via a computer system, communication network, or one or more local or remote processors, such as those associated with a vehicle, vehicle controller, customer mobile device (e.g., smart phone), and/or insurance provider, and/or via computer-executable instructions stored on non-transitory computer-readable medium or media.
“In another aspect, a premium determination system is provided. The premium determination system may include (1) a communication interface configured to (a) receive contextual data related to a collision involving at least a first vehicle and (b) receive a first fault score and a second fault score for the collision transmitted from the first vehicle, the first fault score representing a first percentage of fault allocated to the first vehicle, the second fault score representing a second percentage of fault allocated to an entity accountable for an environmental condition present at the collision, and (2) a processor coupled to the communication interface and a non-transitory medium, the non-transitory medium containing computer-executable instructions that, when executed by the processor, configure the processor to (a) accumulate respective fault scores for the first vehicle over a period of time, the accumulated fault score for the first vehicle including the first fault score for the collision, and (b) determine an auto insurance premium for the first vehicle based upon the accumulated fault score for the first vehicle. The system may include additional, less, or alternate functionality, including that discussed elsewhere herein.”
The claims supplied by the inventors are:
“1. An autonomous vehicle system for allocating fault in a collision involving an autonomous vehicle, the autonomous vehicle system comprising: the autonomous vehicle; a plurality of sensors affixed to the autonomous vehicle; and an autonomous vehicle computing device coupled to the autonomous vehicle, the autonomous vehicle computing device comprising i) a non-transitory memory for at least storing driving data and contextual data collected by the plurality of sensors, and ii) a processor in communication with the non-transitory memory and the plurality of sensors, wherein the plurality of sensors are configured to: detect the driving data and the contextual data including driving conditions associated with the autonomous vehicle and related to the collision involving the autonomous vehicle, and transmit, to the processor, the driving data and the contextual data, and wherein the processor is configured to: execute a stored control program configured to operate the autonomous vehicle, during execution of the stored control program, generate other driving data including driving information representing an operation of the autonomous vehicle during the execution of the stored control program, determine that the collision involving the autonomous vehicle has occurred, in response to the collision being determined, analyze the driving data and the contextual data, and compute and assign, based upon the contextual data and the driving data, a first fault score for the autonomous vehicle, and a second fault score for at least one other participant of the collision, wherein the first fault score is reduced at least in proportion to the second fault score.
“2. The autonomous vehicle system of claim 1, wherein the plurality of sensors are further configured to detect activity of the at least one other participant to the collision, the activity including activity prior to the collision and activity during the collision.
“3. The autonomous vehicle system of claim 1, wherein at least one sensor of the plurality of sensors comprises an optical sensor, and wherein the first fault score and the second fault score total one hundred percent.
“4. The autonomous vehicle system of claim 1, wherein at least one sensor of the plurality of sensors is further configured to detect a condition of an environment in which the collision occurs.
“5. The autonomous vehicle system of claim 4, wherein at least one sensor of the plurality of sensors comprises an acoustic sensor for detecting the condition of the environment.
“6. The autonomous vehicle system of claim 4, wherein the condition of the environment includes a road condition.
“7. The autonomous vehicle system of claim 1, wherein the processor is further configured to: write the driving data to the non-transitory memory; assign the first fault score assigned to the autonomous vehicle based upon the driving data; and alter the first fault score when the contextual data indicates that a condition of an environment contributed to the collision.
“8. The autonomous vehicle system of claim 1, wherein the processor is further configured to: compute and assign, based upon the contextual data and the driving data, a third fault score for one or more non-participants of the collision, wherein the at least one other participant and the one or more non-participants are at least one of a pedestrian, a cyclist, a condition of an environment, and a government entity, and wherein the first fault score for the autonomous vehicle is reduced in proportion to the second fault score and the third fault score.
“9. The autonomous vehicle system of claim 1, wherein the processor is associated with a server.
“10. The autonomous vehicle system of claim 1, wherein the processor is associated with a vehicle controller of the autonomous vehicle.
“11. A computer-implemented method for allocating fault in a collision involving an autonomous vehicle, said method implemented using an autonomous vehicle computing device including a non-transitory memory and a processor in communication with the non-transitory memory and a plurality of sensors affixed to the autonomous vehicle, said method comprising: executing, by the processor, a stored control program configured to operate the autonomous vehicle; during execution of the stored control program, generating, by the processor, other driving data including driving information representing an operation of the autonomous vehicle during the execution of the stored control program; receiving, by the processor, driving data and contextual data collected by at least one of the plurality of sensors, the contextual data including driving conditions associated with the autonomous vehicle and related to the collision involving the autonomous vehicle; determining, by the processor, that the collision involving the autonomous vehicle has occurred; in response to the collision being determined, analyzing, by the processor, the driving data and the contextual data; and computing and assigning, by the processor based upon the contextual data and the driving data, a first fault score for the autonomous vehicle, and a second fault score for at least one other participant of the collision, wherein the first fault score is reduced at least in proportion to the second fault score.
“12. The method of claim 11 further comprising detecting, by the plurality of sensors, activity of the at least one other participant to the collision, the activity including activity prior to the collision and activity during the collision.
“13. The method of claim 11, wherein at least one sensor of the plurality of sensors comprises an optical sensor, and wherein the first fault score and the second fault score total one hundred percent.
“14. The method of claim 11, wherein at least one sensor of the plurality of sensors is further configured to detect a condition of an environment in which the collision occurs.
“15. The method of claim 11, wherein the autonomous vehicle computing device is at least one of a remote server and a vehicle controller of the autonomous vehicle.
“16. The method of claim 11 further comprising: writing, by the processor, the driving data to the non-transitory memory; assigning, by the processor, the first fault score assigned to the autonomous vehicle based upon the driving data; and altering, by the processor, the first fault score when the contextual data indicates that a condition of an environment contributed to the collision.
“17. The method of claim 11 further comprising: computing and assigning, by the processor based upon the contextual data and the driving data, a third fault score for one or more non-participants of the collision, wherein the at least one other participant and the one or more non-participants are at least one of a pedestrian, a cyclist, a condition of an environment, and a government entity, and wherein the first fault score for the autonomous vehicle is reduced in proportion to the second fault score and the third fault score.
“18. A non-transitory computer readable medium having computer-executable instructions embodied thereon, when executed by an autonomous vehicle computing device coupled to an autonomous vehicle and having a non-transitory memory, and a processor in communication with the non-transitory memory and a plurality of sensors affixed to the autonomous vehicle, wherein the computer-executable instructions cause the processor configured to: receive driving data and contextual data collected by at least one of the plurality of sensors, the contextual data including driving conditions associated with the autonomous vehicle and related to a collision involving the autonomous vehicle; execute a stored control program configured to operate the autonomous vehicle; during execution of the stored control program, generate other driving data including driving information representing an operation of the autonomous vehicle during the execution of the stored control program; determine that the collision involving the autonomous vehicle has occurred; in response to the collision being determined, analyze the driving data and the contextual data; and compute and assign, based upon the contextual data and the driving data, a first fault score for the autonomous vehicle, and a second fault score for at least one other participant of the collision, wherein the first fault score is reduced at least in proportion to the second fault score.”
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