# US 12,179,752 B1 · Autonomous vehicle entity vector-based situational awareness scoring matrix > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,179,752 B1 - Document ID: US12179752B1 - Status: Granted - Kind: B1 - Application number: 17/482,969 - Filed: 2021-09-23 - Granted: 2024-12-31 - Earliest claimed: 2016-12-09 - Assignees: United Services Automobile Association (USAA) - Applicants: United Services Automobile Association (USAA) - Inventors: Richard John Wallner - Web page: https://patentgrep.com/patent/US12179752B1 ## CPC - B60W 30/0956: {the prediction being responsive to traffic or environmental parameters} - B60W 40/09: Driving style or behaviour - B60W 50/10: Interpretation of driver requests or demands - G01C 21/3492: {employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968)} - G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)} - G08G 1/164: {Centralised systems, e.g. external to vehicles} - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - G08G 1/167: {Driving aids for lane monitoring, lane changing, e.g. blind spot detection} - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract The present invention provides a vector based awareness matrix or system for mimicking a human driver situational awareness and to control a host autonomous vehicle accordingly. ## Claims ### Claim 1 A method comprising: detecting, while piloting a route to a destination location using an autonomous vehicle, a plurality of road entities; assigning, by the autonomous vehicle, each of the plurality of road entities a provisional unique identifier, wherein a plurality of provisional unique identifiers comprises each provisional unique identifier; receiving an indication from an external source of at least one certified object identifier associated respectively with at least one of the plurality of provisional unique identifiers, wherein the at least one certified object identifier respectively indicates at least one of the plurality of the road entities to the vehicle and the external source, wherein the at least one certified object identifier is configured to be shared among a plurality of vehicles using peer-to-peer wireless communication; receiving, from at least one of the plurality of vehicles and using peer-to-peer wireless communication, external information associated with one or more of the at least one certified object identifier; determining, based upon a collision risk presented by the plurality of road entities to an autonomous vehicle, a score associated with each road entity of the plurality of road entities, wherein at least one score is based on the external information; determining, based on the score for each road entity of the plurality of road entities, a score associated with a risk of collision; determining, based on the risk of collision, accident avoidance and mitigation calculations with respect to each road entity of the plurality of road entities; determining a presence of a traffic control signal; and piloting, based on the accident avoidance and mitigation calculations and determining the presence of the traffic control signal, the autonomous vehicle to a destination location. ### Claim 2 (depends on 1) The method of claim 1, further comprising transmitting a road condition associated with at least one road entity of the plurality of road entities to a centralized traffic resource. ### Claim 3 (depends on 1) The method of claim 1, further comprising determining a type of entity associated with each road entity of the plurality of road entities, wherein a type of entity is associated with estimates for one or more of acceleration, stopping distance, weight, and turning radius, and wherein the score is based on the type. ### Claim 4 (depends on 1) The method of claim 1, wherein the score is based on at least one of speed, direction, or behavior of the each of the other road entities. ### Claim 5 (depends on 1) The method of claim 1, further comprising transmitting a road condition associated with at least one road entity of the plurality of road entities. ### Claim 6 (depends on 1) The method of claim 1, wherein the score is based on at least one of RADAR, LIDAR, LASER, an accelerometer, or a camera. ### Claim 7 (depends on 1) The method of claim 1, wherein at least one road entity of the plurality of road entities comprises a pedestrian; and wherein the method further comprises transmitting a signal to the pedestrian. ### Claim 8 (depends on 1) The method of claim 1, wherein the accident avoidance and mitigation calculations comprise at least one of determining a route of the vehicle, controlling a direction of the vehicle, or controlling a speed of the vehicle. ### Claim 9 A non-transitory computer-readable medium comprising: one or more processors; and instructions that, when executed by the one or more processors, causes: detecting, while piloting a route to a destination location using an autonomous vehicle, a plurality of road entities; assigning, by the autonomous vehicle, each of the plurality of road entities a provisional unique identifier, wherein a plurality of provisional unique identifiers comprises each provisional unique identifier; receiving an indication from an external source of at least one certified object identifier associated respectively with at least one of the plurality of provisional unique identifiers, wherein the at least one certified object identifier respectively indicates at least one of the plurality of the road entities to the vehicle and the external source, wherein the at least one certified object identifier is configured to be shared among a plurality of vehicles using peer-to-peer wireless communication; receiving, from at least one of the plurality of vehicles and using peer-to-peer wireless communication, external information associated with one or more of the at least one certified object identifier; determining, based upon a collision risk presented by the plurality of road entities to an autonomous vehicle, a score associated with each road entity of the plurality of road entities, wherein at least one score is based on the external information; determining, based on the score for each road entity of the plurality of road entities, a score associated with a risk of collision; determining, based on the risk of collision, accident avoidance and mitigation calculations with respect to each road entity of the plurality of road entities; determining a presence of a traffic control signal; and piloting, based on the accident avoidance and mitigation calculations and determining the presence of the traffic control signal, the autonomous vehicle to a destination location. ### Claim 10 (depends on 9) The non-transitory computer-readable medium of claim 9, wherein the instructions further cause transmitting a road condition associated with at least one road entity of the plurality of road entities to a centralized traffic resource. ### Claim 11 (depends on 9) The non-transitory computer-readable medium of claim 9, wherein the instructions further cause determining a type of each road entity of the plurality of road entities, wherein a type of entity is associated with estimates for one or more of acceleration, stopping distance, weight, and turning radius, and wherein the score is based on the type. ### Claim 12 (depends on 9) The non-transitory computer-readable medium of claim 9, wherein the score is based on at least one of speed, direction, or behavior of the each of the other road entities. ### Claim 13 (depends on 9) The non-transitory computer-readable medium of claim 9, wherein the instructions further cause transmitting a signal representative of road conditions to at least one of the each of the other road entities. ### Claim 14 (depends on 9) The non-transitory computer-readable medium of claim 9, wherein the score is based on at least one of RADAR, LIDAR, LASER, an accelerometer, or a camera. ### Claim 15 (depends on 9) The non-transitory computer-readable medium of claim 9, wherein at least one road entity of the plurality of road entities comprises a pedestrian; and wherein the instructions further cause transmitting a signal to the pedestrian. ### Claim 16 A device comprising: one or more processors; and instructions that, when executed by the one or more processors, causes the device to: detecting, while piloting a route to a destination location using an autonomous vehicle, a plurality of road entities; assigning, by the autonomous vehicle, each of the plurality of road entities a provisional unique identifier, wherein a plurality of provisional unique identifiers comprises each provisional unique identifier; receiving an indication from an external source of at least one certified object identifier associated respectively with at least one of the plurality of provisional unique identifiers, wherein the at least one certified object identifier respectively indicates at least one of the plurality of the road entities to the vehicle and the external source, wherein the at least one certified object identifier is configured to be shared among a plurality of vehicles using peer-to-peer wireless communication; receiving, from at least one of the plurality of vehicles and using peer-to-peer wireless communication, external information associated with one or more of the at least one certified object identifier; determine, based upon a collision risk presented by the plurality of road entities to an autonomous vehicle, a score associated with each road entity of the plurality of road entities, wherein at least one score is based on the external information; determine, based on the score for each road entity of the plurality of road entities, a score associated with a risk of collision; and determine, based on the risk of collision, accident avoidance and mitigation calculations with respect to each road entity of the plurality of road entities; determine a presence of a traffic control signal; and pilot, based on the accident avoidance and mitigation calculations and determining the presence of the traffic control signal, the autonomous vehicle to a destination location. ### Claim 17 (depends on 16) The device of claim 16, wherein the instructions further cause the device to transmit a road condition associated with at least one road entity of the plurality of road entities to a centralized traffic resource. ### Claim 18 (depends on 16) The device of claim 16, wherein the instructions further cause the device to determine a type of each road entity among the plurality of road entities, wherein a type of entity is associated with estimates for one or more of acceleration, stopping distance, weight, and turning radius, and wherein the score is based on the type. ### Claim 19 (depends on 16) The device of claim 16, wherein the score is based on at least one of speed, direction, or behavior of each of the road entities. ### Claim 20 (depends on 16) The device of claim 16, wherein the score is based on at least one of RADAR, LIDAR LASER, an accelerometer, or a camera.