# US 10,481,609 B2 · Parking-lot-navigation system and method > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,481,609 B2 - Document ID: US10481609B2 - Status: Granted - Kind: B2 - Application number: 15/373,845 - Filed: 2016-12-09 - Published: 2018-06-14 - Granted: 2019-11-19 - Earliest claimed: 2016-12-09 - Assignees: Ford Global Technologies, LLC - Applicants: Ford Global Technologies, LLC - Inventors: Maryam Moosaei; Jinesh J Jain; Harpreetsingh Banvait - Web page: https://patentgrep.com/patent/US10481609B2 ## CPC - G05D 1/0246: {using a video camera in combination with image processing means} - B60W 30/06: Automatic manoeuvring for parking - G05D 1/00: Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots (drive control systems specially adapted for autonomous road vehicles B60W60/00) - G06V 20/586: {of parking space} - G06V 20/588: {Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road} - G08G 1/142: {external to the vehicles} - G08G 1/146: {where the parking area is a limited parking space, e.g. parking garage, restricted space} - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2420/408: Radar; Laser, e.g. lidar - B60W 2420/54: Audio sensitive means, e.g. ultrasound - B60W 2710/20: Steering systems - G08G 1/168: {Driving aids for parking, e.g. acoustic or visual feedback on parking space} - 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 - 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 A system and method for assisted or autonomous parking of a vehicle is disclosed. The method may begin when the vehicle approaches a feeder lane within a parking lot. At that point, a computer system may decide whether the vehicle should enter the feeder lane. The computer system may use at least one of machine learning, computer vision, and range measurements to determining whether a condition precedent for entering the feeder lane exists. The condition precedent may include an in-bound arrow on the feeder lane or parking lines and/or a parked vehicle adjacent the feeder lane defining a departure angle less than or equal to ninety degrees. If the condition precedent exists, the vehicle may enter the feeder lane. If the condition precedent does not exist, the vehicle may move on to another feeder lane. ## Claims ### Claim 1 A method for determining whether to advance into a feeder lane within a parking lot, the method comprising: approaching, by an autonomous vehicle, the feeder lane within the parking lot; identifying, by the autonomous vehicle, using at least one of machine learning and computer vision, at least one of an in-bound arrow on the feeder lane, and parking lines or a parked vehicle adjacent the feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure is a measure of a change of direction necessary for the autonomous vehicle to appropriately enter one or more parking spaces directly adjacent the feeder lane if the autonomous vehicle were already traveling down the feeder lane; and advancing, by the autonomous vehicle in response to the identifying, into the feeder lane. ### Claim 2 (depends on 1) The method of claim 1, further comprising using one or more sensors on-board the autonomous vehicle to collect data characterizing at least a portion of the feeder lane. ### Claim 3 (depends on 2) The method of claim 2, wherein the identifying comprises applying, by a computer system carried on-board the autonomous vehicle, the at least one of machine learning and computer vision to the data. ### Claim 4 (depends on 3) The method of claim 3, wherein the one or more sensors comprise a camera. ### Claim 5 (depends on 4) The method of claim 4, wherein the data comprises at least one image frame output by the camera. ### Claim 6 (depends on 5) The method of claim 5, wherein the identifying further comprises using, by the computer system, computer vision to select at least one region of interest comprising less than all of the at least one image frame. ### Claim 7 (depends on 6) The method of claim 6, wherein the identifying further comprises generating, by the computer system, at least one cropped subset of the at least one image frame by cropping the at least one region of interest from the at least one image frame. ### Claim 8 (depends on 7) The method of claim 7, wherein the identifying further comprises using, by the computer system, an artificial neural network to classify the at least one cropped subset. ### Claim 9 (depends on 8) The method of claim 8, wherein: the identifying further comprises using, by the computer system, the artificial neural network to determine an affinity score between the at least one cropped subset and each class of a plurality of classes; and the plurality of classes includes a no arrow class, an in-bound arrow only class, an out-bound arrow only class, and an in-bound and out-bound arrow class. ### Claim 10 (depends on 8) The method of claim 8, wherein: the identifying further comprises using, by the computer system, the artificial neural network to determine an affinity score between the at least one cropped subset and each class of a plurality of classes; and the plurality of classes includes a no parking lines class, a parking lines with departure angle of less than or equal to ninety degrees class, and a parking lines with departure angle of greater than ninety degrees class. ### Claim 11 (depends on 8) The method of claim 8, wherein: the identifying further comprises using, by the computer system, the artificial neural network to determine an affinity score between the at least one cropped subset and each class of a plurality of classes; and the plurality of classes includes a no parked vehicle class, a parked vehicle with departure angle of less than or equal to ninety degrees class, and a parked vehicle with departure angle of greater than ninety degrees class. ### Claim 12 A method for determining whether to advance into a first feeder lane within a parking lot, the method comprising: approaching, by an autonomous vehicle, the first feeder lane within the parking lot; collecting, by one or more sensors on-board the autonomous vehicle, first data characterizing at least a portion of the first feeder lane; confirming, by a computer system carried on-board the autonomous vehicle, an existence of a condition precedent for advancing into the first feeder lane; the confirming comprising detecting the condition precedent by at least one of applying a machine-learning algorithm to the first data, applying a computer-vision technique to the first data, and extracting first range measurements from the first data; the confirming wherein the condition precedent for advancing into the first feeder lane comprises at least one of an in-bound arrow on the first feeder lane, parking lines adjacent the first feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure defined by the parking lines adjacent the first feeder lane is a measure of a change of direction necessary for the autonomous vehicle to appropriately enter a parking space defined by the parking lines adjacent the first feeder lane if the autonomous vehicle were already traveling down the first feeder lane, and at least one parked vehicle adjacent the first feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure defined by the at least one parked vehicle adjacent the first feeder lane is a measure of a change of direction necessary for the autonomous vehicle to turn and park alongside the at least one parked vehicle adjacent the first feeder lane if the autonomous vehicle were already traveling down the first feeder lane; and advancing, by the autonomous vehicle, into the first feeder lane in response to the confirming. ### Claim 13 (depends on 12) The method of claim 12, further comprising approaching, by the autonomous vehicle, a second feeder lane within the parking lot. ### Claim 14 (depends on 13) The method of claim 13, further comprising collecting, by the one or more sensors, second data characterizing at least a portion of the second feeder lane. ### Claim 15 (depends on 14) The method of claim 14, further comprising confirming, by the computer system carried on-board the autonomous vehicle, an absence of a condition precedent for advancing into the second feeder lane. ### Claim 16 (depends on 15) The method of claim 15, wherein the confirming the absence comprises at least one of applying the machine-learning algorithm to the second data, applying the computer-vision technique to the second data, and extracting second range measurements from the second data. ### Claim 17 (depends on 16) The method of claim 16, wherein the condition precedent for advancing into the second feeder lane comprises at least one of: an in-bound arrow on the second feeder lane; parking lines adjacent the second feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure defined by the parking lines adjacent the second feeder lane is a measure of a change of direction necessary for the autonomous vehicle to appropriately enter a parking space defined by the parking lines adjacent the second feeder lane if the autonomous vehicle were already traveling down the second feeder lane; and at least one parked vehicle adjacent the second feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure defined by the at least one parked vehicle adjacent the second feeder lane is a measure of a change of direction necessary for the autonomous vehicle to turn and park alongside the at least one parked vehicle adjacent the second feeder lane if the autonomous vehicle were already traveling down the second feeder lane. ### Claim 18 (depends on 17) The method of claim 17, further comprising avoiding, by the autonomous vehicle, the second feeder lane in response to the confirming the absence. ### Claim 19 (depends on 12) The method of claim 12, wherein: the one or more sensors comprise a camera; the data comprises at least one image frame output by the camera; the identifying further comprises using, by the computer system, computer vision to select at least one region of interest comprising less than all of the at least one image frame; the identifying further comprises generating, by the computer system, at least one cropped subset of the at least one image frame by cropping the at least one region of interest from the at least one image frame; and the identifying further comprises using, by the computer system, an artificial neural network to classify the at least one cropped subset. ### Claim 20 An autonomous vehicle comprising: one or more sensors carried on-board the autonomous vehicle; at least one processor carried on-board the autonomous vehicle; and memory operably connected to the at least one processor, the memory storing software programmed to direct the autonomous vehicle to a first feeder lane within a parking lot, collect data output by the one or more sensors that characterizes at least a portion of the first feeder lane, use at least one of machine learning, computer vision, and range measurement to determine whether a condition precedent for entering the first feeder lane is reflected in the data, wherein the condition precedent comprises a presence of at least one of an in-bound arrow on the first feeder lane, parking lines adjacent the first feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure defined by the parking lines is a measure of a change of direction necessary for the autonomous vehicle to appropriately enter a parking space defined by the parking lines if the autonomous vehicle were already traveling down the first feeder lane, and at least one parked vehicle adjacent the first feeder lane defining a departure angle less than or equal to ninety degrees, wherein the angle of departure defined by the at least one parked vehicle is a measure of a change of direction necessary for the autonomous vehicle to turn and park alongside the at least one parked vehicle if the autonomous vehicle were already traveling down the first feeder lane, direct the autonomous vehicle to enter the first feeder lane when the condition precedent is present, and direct the autonomous vehicle to a second feeder lane when the condition precedent is not present.