Systems and methods for allocating fault to autonomous vehicles

Abstract

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.

We claim: 
     
         1 . An autonomous vehicle system comprising:
 a computing device remote from a plurality of autonomous vehicle, the computing device comprising a non-transitory memory for storing computer-implementable instructions, and at least one processor, wherein the at least one processor is configured to:
 receive a plurality of fault scores from a plurality of autonomous vehicle computing devices associated with the plurality of autonomous vehicles, each fault score attributing to each autonomous vehicle a first portion of fault for a collision involving the respective autonomous vehicle; 
 apply machine learning techniques to the plurality of fault scores to identify driving patterns for a set of autonomous vehicles of the plurality of autonomous vehicles being of a similar type; 
 develop a driving profile for the set of autonomous vehicles using the identified driving patterns; 
 receive a first fault score from a first autonomous vehicle computing device associated with a first autonomous vehicle, the first autonomous vehicle being of the similar type to the set of autonomous vehicles; and 
 automatically adjust a first auto insurance premium for the first autonomous vehicle based upon the first fault score and the driving profile for the set of autonomous vehicles. 
   
     
     
         2 . The autonomous vehicle system of  claim 1 , wherein the at least one processor is further configured to receive contextual data from a third party system, the contextual data including information collected by one or more sensors of the third party system and associated with one or more collisions involving the first autonomous vehicle. 
     
     
         3 . The autonomous vehicle system of  claim 2 , wherein the third party system includes a traffic camera system configured to capture images of an area where the one or more collisions occurred. 
     
     
         4 . The autonomous vehicle system of  claim 1 , wherein the at least one processor is further configured to:
 accumulate multiple fault scores associated with the first autonomous vehicle during a predetermined time; and   apply the machine learning techniques to the accumulated multiple fault score to determine one or more adjustments to the first auto insurance premium for the first autonomous vehicle.   
     
     
         5 . The autonomous vehicle system of  claim 1 , wherein the at least one processor is further configured to receive a second fault score attributing to at least one other participant at least a second portion of fault for the collision. 
     
     
         6 . The autonomous vehicle system of  claim 5 , wherein the at least one other participant of the collision includes at least one of a vehicle, a pedestrian, or a municipality. 
     
     
         7 . The autonomous vehicle system of  claim 1 , wherein the type includes at least one of vehicle make, vehicle model, vehicle year, vehicle software, vehicle software version, or vehicle hardware. 
     
     
         8 . A computer-implemented method implemented using a computing device remote from a plurality of autonomous vehicle, the computing device including a non-transitory memory for storing computer-implementable instructions and at least one processor in communication with the non-transitory memory, said method comprising:
 receiving a plurality of fault scores from a plurality of autonomous vehicle computing devices associated with the plurality of autonomous vehicles, each fault score attributing to each autonomous vehicle a first portion of fault for a collision involving the respective autonomous vehicle;   applying machine learning techniques to the plurality of fault scores to identify driving patterns for a set of autonomous vehicles of the plurality of autonomous vehicles being of a similar type;   developing a driving profile for the set of autonomous vehicles using the identified driving patterns;   receiving a first fault score from a first autonomous vehicle computing device associated with a first autonomous vehicle, the first autonomous vehicle being of the similar type to the set of autonomous vehicles; and   automatically adjusting a first auto insurance premium for the first autonomous vehicle based upon the first fault score and the driving profile for the set of autonomous vehicles.   
     
     
         9 . The method of  claim 8  further comprising receiving contextual data from a third party system, the contextual data including information collected by one or more sensors of the third party system and associated with one or more collisions involving the first autonomous vehicle. 
     
     
         10 . The method of  claim 9 , wherein the third party system includes a traffic camera system configured to capture images of an area where the one or more collisions occurred. 
     
     
         11 . The method of  claim 8  further comprising:
 accumulating multiple fault scores associated with the first autonomous vehicle during a predetermined time; and 
 applying the machine learning techniques to the accumulated multiple fault score to determine one or more adjustments to the first auto insurance premium for the first autonomous vehicle. 
 
     
     
         12 . The method of  claim 8  further comprising receiving a second fault score attributing to at least one other participant at least a second portion of fault for the collision. 
     
     
         13 . The method of  claim 12 , wherein the at least one other participant of the collision includes at least one of a vehicle, a pedestrian, or a municipality. 
     
     
         14 . The method of  claim 8 , wherein the type includes at least one of vehicle make, vehicle model, vehicle year, vehicle software, vehicle software version, or vehicle hardware. 
     
     
         15 . At least one non-transitory computer readable medium having computer-executable instructions embodied thereon, when executed by a computing device remote from a plurality of autonomous vehicle and having a non-transitory memory and at least one processor in communication with the non-transitory memory, the computer-executable instructions cause the at least one processor to:
 receive a plurality of fault scores from a plurality of autonomous vehicle computing devices associated with the plurality of autonomous vehicles, each fault score attributing to each autonomous vehicle a first portion of fault for a collision involving the respective autonomous vehicle;   apply machine learning techniques to the plurality of fault scores to identify driving patterns for a set of autonomous vehicles of the plurality of autonomous vehicles being of a similar type;   develop a driving profile for the set of autonomous vehicles using the identified driving patterns;   receive a first fault score from a first autonomous vehicle computing device associated with a first autonomous vehicle, the first autonomous vehicle being of the similar type to the set of autonomous vehicles; and   automatically adjust a first auto insurance premium for the first autonomous vehicle based upon the first fault score and the driving profile for the set of autonomous vehicles.   
     
     
         16 . The computer readable medium of  claim 15 , wherein the computer-executable instructions further cause the at least one processor to receive contextual data from a third party system, the contextual data including information collected by one or more sensors of the third party system and associated with one or more collisions involving the first autonomous vehicle. 
     
     
         17 . The computer readable medium of  claim 16 , wherein the third party system includes a traffic camera system configured to capture images of an area where the one or more collisions occurred. 
     
     
         18 . The computer readable medium of  claim 15 , wherein the computer-executable instructions further cause the at least one processor to:
 accumulate multiple fault scores associated with the first autonomous vehicle during a predetermined time; and   apply the machine learning techniques to the accumulated multiple fault score to determine one or more adjustments to the first auto insurance premium for the first autonomous vehicle.   
     
     
         19 . The computer readable medium of  claim 15 , wherein the at least one processor is further configured to receive a second fault score attributing to at least one other participant at least a second portion of fault for the collision. 
     
     
         20 . The computer readable medium of  claim 15 , wherein the type includes at least one of vehicle make, vehicle model, vehicle year, vehicle software, vehicle software version, or vehicle hardware.