# US 12,120,463 B2 · Adjusting vehicle sensor field of view volume > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,120,463 B2 - Document ID: US12120463B2 - Status: Granted - Kind: B2 - Application number: 18/305,478 - Filed: 2023-04-24 - Published: 2023-08-17 - Granted: 2024-10-15 - Earliest claimed: 2019-12-23 - Assignees: Waymo LLC - Applicants: Waymo LLC - Inventors: Simon Verghese; Alexander McCauley - Web page: https://patentgrep.com/patent/US12120463B2 ## CPC - H04N 7/18: Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast - B60W 30/0956: {the prediction being responsive to traffic or environmental parameters} - B60W 60/001: {Planning or execution of driving tasks} - G01S 7/483: Details of pulse systems - G01S 7/497: Means for monitoring or calibrating - G01S 13/865: {Combination of radar systems with lidar systems} - G01S 13/867: {Combination of radar systems with cameras} - G01S 13/931: of land vehicles - G01S 17/86: Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders - G01S 17/89: for mapping or imaging - G01S 17/931: of land vehicles - G01W 1/06: giving a combined indication of weather conditions (catathermometers for measuring "cooling value" related either to weather conditions or to comfort of other human environment G01W1/17; computers per se G06) - G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)} - G05D 1/81: Handing over between on-board automatic and on-board manual control - G06V 10/44: Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components - G06V 10/89: {using frequency domain filters, e.g. Fourier masks implemented on spatial light modulators} - G06V 20/56: exterior to a vehicle by using sensors mounted on the vehicle - G08G 1/0112: {from the vehicle, e.g. floating car data [FCD]} - G08G 1/0116: {from roadside infrastructure, e.g. beacons} - G08G 1/04: using optical or ultrasonic detectors - G08G 1/048: with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector - H04N 23/69: Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2420/408: Radar; Laser, e.g. lidar - B60W 2556/45: External transmission of data to or from the vehicle - G05D 1/0251: {extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision (stereoscopic image analysis H04N13/00; depth recovery from images G06T7/593)} - G05D 1/0257: {using a radar (radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931)} - G05D 1/2435: {Extracting 3D information} - G05D 1/247: using signals provided by artificial sources external to the vehicle, e.g. navigation beacons - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - 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 - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G01W: METEOROLOGY (radar, sonar, lidar or analogous systems, designed for meteorological use G01S13/95, G01S15/88, G01S17/95) - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - 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 An example method includes receiving, from one or more sensors associated with an autonomous vehicle, sensor data associated with a target object in an environment of the vehicle during a first environmental condition, where at least one sensor of the sensor(s) is configurable to be associated with one of a plurality of operating field of view volumes. The method also includes based on the sensor data, determining at least one parameter associated with the target object. The method also includes determining a degradation in the parameter(s) between the sensor data and past sensor data, where the past sensor data is associated with the target object in the environment during a second environmental condition different from the first and, based on the degradation, adjusting the operating field of view volume of the at least one sensor to a different one of the operating field of view volumes. ## Claims ### Claim 1 A method comprising: receiving, from one or more sensors associated with an autonomous vehicle, sensor data associated with a target object in an environment of the autonomous vehicle, wherein at least one sensor of the one or more sensors is configurable to be associated with one of a plurality of operating field of view volumes, wherein each operating field of view volume represents a space within which the at least one sensor is expected to detect objects outside the autonomous vehicle at a minimum confidence level, and wherein a particular sensor of the at least one sensor is currently associated with a first operating field of view volume of the plurality of operating field of view volumes; performing a comparison between the sensor data associated with the target object and past sensor data associated with the target object; selecting, based on the comparison, a second operating field of view volume of the plurality of operating field of view volumes for the particular sensor, wherein the second operating field of view volume is different than the first operating field of view volume; and adjusting the operating field of view volume of the particular sensor to be the second operating field of view volume. ### Claim 2 (depends on 1) The method of claim 1, wherein the sensor data is associated with the target object during a first environmental condition and the past sensor data is associated with the target object during a second environmental condition. ### Claim 3 (depends on 2) The method of claim 2, wherein the first environmental condition is one or more of a rainy condition, a foggy condition, or a snowy condition, and wherein the second environmental condition is a clear weather condition. ### Claim 4 (depends on 2) The method of claim 2, wherein the first environmental condition is a nighttime condition, and wherein the second environmental condition is a daytime condition. ### Claim 5 (depends on 2) The method of claim 2, wherein the first environmental condition is a first sensor cleanliness condition, and wherein the second environmental condition is a second sensor cleanliness condition. ### Claim 6 (depends on 1) The method of claim 1, wherein performing the comparison between the sensor data associated with the target object and past sensor data associated with the target object comprises: detecting a degradation in at least one parameter associated with the target object between the sensor data and the past sensor data, wherein selecting the second operating field of view volume is in response to detecting the degradation in the at least one parameter. ### Claim 7 (depends on 1) The method of claim 1, wherein the particular sensor is a camera. ### Claim 8 (depends on 1) The method of claim 1, wherein the particular sensor is a lidar sensor. ### Claim 9 (depends on 1) The method of claim 1, wherein the particular sensor is a radar sensor. ### Claim 10 A system comprising: one or more sensors associated with an autonomous vehicle, wherein at least one sensor of the one or more sensors is configurable to be associated with one of a plurality of operating field of view volumes, wherein each operating field of view volume represents a space within which the at least one sensor is expected to detect objects outside the autonomous vehicle at a minimum confidence level, and wherein a particular sensor of the at least one sensor is currently associated with a first operating field of view volume of the plurality of operating field of view volumes; one or more processors coupled to the one or more sensors; a memory coupled to the one or more processors, the memory having stored thereon instructions that, upon execution by the one or more processors, cause the one or more processors to perform operations comprising: receiving, from the one or more sensors, sensor data associated with a target object in an environment of the autonomous vehicle; performing a comparison between the sensor data associated with the target object and past sensor data associated with the target object; selecting, based on the comparison, a second operating field of view volume of the plurality of operating field of view volumes for the particular sensor, wherein the second operating field of view volume is different than the first operating field of view volume; and adjusting the operating field of view volume of the particular sensor to be the second operating field of view volume. ### Claim 11 (depends on 10) The system of claim 10, wherein the sensor data is associated with the target object during a first environmental condition and the past sensor data is associated with the target object during a second environmental condition. ### Claim 12 (depends on 11) The system of claim 11, wherein the first environmental condition is one or more of a rainy condition, a foggy condition, or a snowy condition, and wherein the second environmental condition is a clear weather condition. ### Claim 13 (depends on 11) The system of claim 11, wherein the first environmental condition is a nighttime condition, and wherein the second environmental condition is a daytime condition. ### Claim 14 (depends on 11) The system of claim 11, wherein the first environmental condition is a first sensor cleanliness condition, and wherein the second environmental condition is a second sensor cleanliness condition. ### Claim 15 (depends on 10) The system of claim 10, wherein performing the comparison between the sensor data associated with the target object and past sensor data associated with the target object comprises: detecting a degradation in at least one parameter associated with the target object between the sensor data and the past sensor data, wherein selecting the second operating field of view volume is in response to detecting the degradation in the at least one parameter. ### Claim 16 (depends on 10) The system of claim 10, wherein the particular sensor is a camera, a lidar sensor, or a radar sensor. ### Claim 17 A non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by one or more processors, cause the one or more processors to perform operations comprising: receiving, from one or more sensors associated with an autonomous vehicle, sensor data associated with a target object in an environment of the autonomous vehicle, wherein at least one sensor of the one or more sensors is configurable to be associated with one of a plurality of operating field of view volumes, wherein each operating field of view volume represents a space within which the at least one sensor is expected to detect objects outside the autonomous vehicle at a minimum confidence level, and wherein a particular sensor of the at least one sensor is currently associated with a first operating field of view volume of the plurality of operating field of view volumes; performing a comparison between the sensor data associated with the target object and past sensor data associated with the target object; selecting, based on the comparison, a second operating field of view volume of the plurality of operating field of view volumes for the particular sensor, wherein the second operating field of view volume is different than the first operating field of view volume; and adjusting the operating field of view volume of the particular sensor to be the second operating field of view volume. ### Claim 18 (depends on 17) The non-transitory computer-readable storage medium of claim 17, wherein the sensor data is associated with the target object during a first environmental condition and the past sensor data is associated with the target object during a second environmental condition. ### Claim 19 (depends on 17) The non-transitory computer-readable storage medium of claim 17, wherein performing the comparison between the sensor data associated with the target object and past sensor data associated with the target object comprises: detecting a degradation in at least one parameter associated with the target object between the sensor data and the past sensor data, wherein selecting the second operating field of view volume is in response to detecting the degradation in the at least one parameter. ### Claim 20 (depends on 17) The non-transitory computer-readable storage medium of claim 17, wherein the particular sensor is a camera, a lidar sensor, or a radar sensor.