# US 11,029,699 B2 · Navigating a vehicle based on a detected barrier > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,029,699 B2 - Document ID: US11029699B2 - Status: Granted - Kind: B2 - Application number: 16/863,490 - Filed: 2020-04-30 - Published: 2020-10-08 - Granted: 2021-06-08 - Earliest claimed: 2016-10-11 - Assignees: Mobileye Vision Technologies Ltd. - Applicants: Mobileye Vision Technologies Ltd. - Inventors: Barak Cohen - Web page: https://patentgrep.com/patent/US11029699B2 ## CPC - G05D 1/0246: {using a video camera in combination with image processing means} - B60W 30/09: Taking automatic action to avoid collision, e.g. braking and steering - G01C 21/34: Route searching; Route guidance - G06V 20/56: exterior to a vehicle by using sensors mounted on the vehicle - 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} - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G08G 1/165: {for passive traffic, e.g. including static obstacles, trees} - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - H04N 7/181: {for receiving images from a plurality of remote sources} - B60W 2556/45: External transmission of data to or from the vehicle - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - 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) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE - 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}) - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path. ## Claims ### Claim 1 A vehicle navigation system for a vehicle, the vehicle navigation system comprising: a memory including instructions; and one or more processors that, when in operation, are configured by the instructions to: estimate, by use of a machine learning system, a future path of the vehicle ahead of a current location of the vehicle; analyze at least one of a plurality of images to identify a lane of the vehicle in which the vehicle travels, the plurality of images captured by a camera of the vehicle; identify, based on the at least one of the plurality of images, a lane marking separating a current lane of the vehicle and an adjacent lane; identify a candidate vehicle forward of the vehicle in the lane in which the vehicle travels; and cause the vehicle to traverse the lane marking to change to the adjacent lane in response to identifying the candidate vehicle as an obstacle forward of the vehicle. ### Claim 2 (depends on 1) The vehicle navigation system of claim 1, wherein, to identify the candidate vehicle, the instructions configure the one or more processors to use radar. ### Claim 3 (depends on 1) The vehicle navigation system of claim 1, wherein the candidate vehicle is moving slower than the vehicle. ### Claim 4 (depends on 1) The vehicle navigation system of claim 1, wherein the instructions configure the one or more processors to traverse the lane marking to change to the adjacent lane without input from a driver of the vehicle. ### Claim 5 (depends on 1) The vehicle navigation system of claim 1, wherein, to cause the vehicle to traverse the lane marking to change to the adjacent lane, the instructions configure the one or more processors to make a change in acceleration. ### Claim 6 (depends on 5) The vehicle navigation system of claim 5, wherein the change in acceleration increases the acceleration. ### Claim 7 A non-transitory machine-readable medium including instructions that, when executed by circuitry of a vehicle component, cause the circuitry to perform operations comprising: estimating, by use of a machine learning system, a future path of the vehicle ahead of a current location of the vehicle; analyzing at least one of a plurality of images to identify a lane of the vehicle in which the vehicle travels, the plurality of images captured by a camera of the vehicle; identifying, based on the at least one of the plurality of images, a lane marking separating a current lane of the vehicle and an adjacent lane; identifying a candidate vehicle forward of the vehicle in the lane in which the vehicle travels; and causing the vehicle to traverse the lane marking to change to the adjacent lane in response to identifying the candidate vehicle as an obstacle forward of the vehicle. ### Claim 8 (depends on 7) The machine-readable medium of claim 7, wherein identifying the candidate vehicle includes using radar. ### Claim 9 (depends on 7) The machine-readable medium of claim 7, wherein the candidate vehicle is moving slower than the vehicle. ### Claim 10 (depends on 7) The machine-readable medium of claim 7, wherein causing the vehicle to traverse the lane marking to change to the adjacent lane is performed without input from a driver of the vehicle. ### Claim 11 (depends on 7) The machine-readable medium of claim 7, wherein causing the vehicle to traverse the lane marking to change to the adjacent lane includes making a change in acceleration. ### Claim 12 (depends on 11) The machine-readable medium of claim 11, wherein the change in acceleration increases the acceleration. ### Claim 13 A vehicle comprising: a camera; and a vehicle navigation system including a processor, the vehicle navigation system configured to: estimate, by use of a machine learning system, a future path of the vehicle ahead of a current location of the vehicle; analyze at least one of a plurality of images to identify a lane of the vehicle in which the vehicle travels, the plurality of images captured by the camera; identify, based on the at least one of the plurality of images, a lane marking separating a current lane of the vehicle and an adjacent lane; identify a candidate vehicle forward of the vehicle in the lane in which the vehicle travels; and cause the vehicle to traverse the lane marking to change to the adjacent lane in response to identifying the candidate vehicle as an obstacle forward of the vehicle. ### Claim 14 (depends on 13) The vehicle of claim 13, wherein, to identify the candidate vehicle, the vehicle navigation system is configured to use radar. ### Claim 15 (depends on 13) The vehicle of claim 13, wherein the candidate vehicle is moving slower than the vehicle. ### Claim 16 (depends on 13) The vehicle of claim 13, wherein the vehicle navigation system is configured to traverse the lane marking to change to the adjacent lane without input from a driver of the vehicle. ### Claim 17 (depends on 13) The vehicle of claim 13, wherein, to cause the vehicle to traverse the lane marking to change to the adjacent lane, the vehicle navigation system is configured to make a change in acceleration. ### Claim 18 (depends on 17) The vehicle of claim 17, wherein the change in acceleration increases the acceleration.