# US 11,307,587 B2 · Operating an autonomous vehicle according to road user reaction modeling with occlusions > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,307,587 B2 - Document ID: US11307587B2 - Status: Granted - Kind: B2 - Application number: 17/035,115 - Filed: 2020-09-28 - Published: 2021-04-15 - Granted: 2022-04-19 - Earliest claimed: 2018-12-14 - Assignees: Waymo LLC - Applicants: Waymo LLC - Inventors: Jared Stephen Russell; Jens-Steffen Ralf Gutmann - Web page: https://patentgrep.com/patent/US11307587B2 ## CPC - G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)} - G06T 7/73: using feature-based methods - B60W 30/0956: {the prediction being responsive to traffic or environmental parameters} - B60W 30/18159: {Traversing an intersection} - B60W 60/00276: {for two or more other traffic participants} - G06T 7/70: Determining position or orientation of objects or cameras (camera calibration G06T7/80) - G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads - G06V 20/588: {Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road} - G08G 1/0133: {for classifying traffic situation} - 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} - G06T 2207/30256: Lane; Road marking - G06T 2207/30261: Obstacle - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - 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 - 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 The disclosure provides a method for operating an autonomous vehicle. To operate the autonomous vehicle, a plurality of lane segments that are in an environment of the autonomous vehicle is determined and a first object and a second object in the environment are detected. A first position for the first object is determined in relation to the plurality of lane segments, and particular lane segments that are occluded by the first object are determined using the first position. According to the occluded lane segments, a reaction time is determined for the second object and a driving instruction for the autonomous vehicle is determined according to the reaction time. The autonomous vehicle is then operated based on the driving instruction. ## Claims ### Claim 1 A method for operating an autonomous vehicle, the method comprising: detecting, by one or more computing devices using a detection system of the autonomous vehicle, a first object and a second object in the autonomous vehicle's environment; determining, by the one or more computing devices, one or more lane segments to be occluded by the first object from a perspective of the autonomous vehicle during a set time interval according to a positional relationship between the first object and the one or more lane segments; determining, by the one or more computing devices, a reaction time for the second object according to the occluded one or more lane segments; and operating, by the one or more computing devices, the autonomous vehicle based on the determined reaction time. ### Claim 2 (depends on 1) The method of claim 1, wherein the positional relationship includes a predicted trajectory of the first object during the set time interval. ### Claim 3 (depends on 1) The method of claim 1, wherein determining the one or more lane segments to be occluded includes identifying an area that is blocked from a field of view of the autonomous vehicle based on the positional relationship. ### Claim 4 (depends on 3) The method of claim 3, wherein identifying the area that is blocked from the field of view of the autonomous vehicle based on the positional relationship includes: projecting the field of view of the autonomous vehicle from a location of the autonomous vehicle; and determining the one or more lane segments that are behind the first object relative to the projected field of view. ### Claim 5 (depends on 1) The method of claim 1, wherein: the second object is a type of vehicle associated with a nominal human actor; and determining the reaction time includes predicting when the nominal human actor associated with the second object will react to the autonomous vehicle. ### Claim 6 (depends on 5) The method of claim 5, wherein predicting when the nominal human actor associated with the second object will react to the autonomous vehicle includes determining when a field of view of the nominal human actor includes a minimum amount of the autonomous vehicle. ### Claim 7 (depends on 1) The method of claim 1, wherein determining the reaction time includes: determining a stimulus point at which the second object will most likely begin to react to the autonomous vehicle; and adding an estimated perception time to the stimulus point. ### Claim 8 A system comprising: a detection system configured to detect objects in an environment of an autonomous vehicle, the detected objects including a first object and a second object; and one or more computing devices in communication with the detection system, the one or more computing devices being configured to: determine one or more lane segments to be occluded by the first object from a perspective of the autonomous vehicle during a set time interval according to a positional relationship between the first object and the one or more lane segments; determine a reaction time for the second object according to the occluded one or more lane segments; and operate the autonomous vehicle based on the reaction time. ### Claim 9 (depends on 8) The system of claim 8, wherein the positional relationship includes a predicted trajectory of the first object during the set time interval. ### Claim 10 (depends on 8) The system of claim 8, wherein the one or more computing devices are configured to determine the one or more lane segments to be occluded based on an area identified that is blocked from a field of view of the detection system based on the positional relationship. ### Claim 11 (depends on 8) The system of claim 8, wherein: the second object is a type of vehicle associated with a nominal human actor; and the reaction time is determined based on a predicted point in time when the nominal human actor associated with the second object will react to the autonomous vehicle. ### Claim 12 (depends on 11) The system of claim 11, wherein the reaction time is further determined based on when a field of view of the nominal human actor includes a minimum amount of the autonomous vehicle. ### Claim 13 (depends on 8) The system of claim 8, wherein the reaction time is determined based on: a stimulus point at which the second object will most likely begin to react to the autonomous vehicle; and an additional estimated perception time to the stimulus point. ### Claim 14 (depends on 8) The system of claim 8, further comprising the autonomous vehicle. ### Claim 15 A non-transitory, tangible computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by one or more processors, cause the one or more processors to perform a method, the method comprising: detecting, using a detection system of an autonomous vehicle, a first object and a second object in the autonomous vehicle's environment; determining one or more lane segments to be occluded by the first object from a perspective of the autonomous vehicle during a set time interval according to a positional relationship between the first object and the one or more lane segments; determining a reaction time for the second object according to the occluded one or more lane segments; and operating the autonomous vehicle based on the determined reaction time. ### Claim 16 (depends on 15) The medium of claim 15, wherein the positional relationship includes a predicted trajectory of the first object during the set time interval. ### Claim 17 (depends on 15) The medium of claim 15, wherein determining the one or more lane segments to be occluded includes identifying an area that is blocked from a field of view of the autonomous vehicle based on the positional relationship. ### Claim 18 (depends on 17) The medium of claim 17, wherein identifying the area that is blocked from the field of view of the autonomous vehicle based on the positional relationship includes: projecting the field of view of the autonomous vehicle from a location of the autonomous vehicle; and determining the one or more lane segments that are behind the first object relative to the projected field of view. ### Claim 19 (depends on 15) The medium of claim 15, wherein: the second object is a type of vehicle associated with a nominal human actor; and determining the reaction time includes predicting when the nominal human actor associated with the second object will react to the autonomous vehicle. ### Claim 20 (depends on 19) The medium of claim 19, wherein predicting when the nominal human actor associated with the second object will react to the autonomous vehicle includes determining when a field of view of the nominal human actor includes a minimum amount of the autonomous vehicle.