# US 11,443,627 B2 · Navigation system with parking space identification mechanism and method of operation thereof > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,443,627 B2 - Document ID: US11443627B2 - Status: Granted - Kind: B2 - Application number: 17/132,353 - Filed: 2020-12-23 - Published: 2022-06-23 - Granted: 2022-09-13 - Earliest claimed: 2020-12-23 - Assignees: Telenav, Inc. - Applicants: TeleNav, Inc. - Inventors: Weizhe Liu - Web page: https://patentgrep.com/patent/US11443627B2 ## CPC - G01C 21/28: with correlation of data from several navigational instruments - G08G 1/143: {inside the vehicles} - B60W 30/06: Automatic manoeuvring for parking - B62D 15/0285: {Parking performed automatically} - G06N 3/04: Architecture, e.g. interconnection topology - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06T 7/73: using feature-based methods - G06V 20/586: {of parking space} - G09G 5/37: Details of the operation on graphic patterns (G09G5/38 takes precedence) - B60W 2556/50: of positioning data, e.g. GPS [Global Positioning System] data - G06T 2207/20081: Training; Learning - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/30264: Parking - G09G 2354/00: Aspects of interface with display user - G09G 2380/10: Automotive applications - 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) - 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}) - 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 - B62D: MOTOR VEHICLES; TRAILERS (steering, or guiding on a desired track, of agricultural machines or implements A01B69/00; wheels, castors, axles, increasing wheel adhesion B60B; vehicle tyres, tyre inflation or tyre changing B60C; connections between vehicles of a train or the like B60D; vehicles for use on rail and road, amphibious or convertible vehicles B60F; suspension arrangements B60G; heating, cooling, ventilating or other air treating devices B60H; windows, windscreens, non-fixed roofs, doors or similar devices, protective coverings for vehicles not in use B60J; propulsion plant arrangements, auxiliary drives, transmissions, controls, instrumentation or dashboards B60K; electric equipment or propulsion of electrically-propelled vehicles B60L; power supply for electrically-propelled vehicles B60M; passenger accommodation not otherwise provided for B60N; adaptations for load transportation or to carry special loads or objects B60P; arrangement of signalling or lighting devices, the mounting or supporting thereof or circuits therefor, for vehicles in general B60Q; vehicles, vehicle fittings or vehicle parts not otherwise provided for B60R; servicing, cleaning, repairing, supporting, lifting, or manoeuvring, not otherwise provided for, B60S; brake arrangements, brake control systems or parts thereof B60T; air-cushion vehicles B60V; motor-cycles, accessories therefor B62J, B62K; testing of vehicles G01M) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G09G: ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION (arrangements for transferring data between digital computers and displays G06F3/14; static indicating arrangements comprising an association of a number of separate sources or light control cells G09F9/00; static indicating arrangements comprising integral associations of a number of light sources H01J, H01K, H10H, H05B33/12; scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission, details thereof H04N1/00) ## Abstract A navigation system includes: a user interface configured to: receive a sensor data packet for a scan area; a control circuit, coupled to the user interface, configured to: analyze the sensor data packet submitted to a multilayer neural network already trained including storing the sensor data packet; parse the sensor data packet with the multilayer neural network to generate real world endpoints and a bounding box including identifying the real world coordinates; apply line rules, including identifying a parking space by the real world endpoints including storing the real world endpoints in the storage circuit; compile an overhead depiction including boundary lines of the parking space identified by the real world endpoints and the bounding box in the scan area; merge vehicle maneuvering instructions into the overhead depiction for accessing the parking space; and present the overhead depiction for displaying on a user display. ## Claims ### Claim 1 A navigation system comprising: a user interface configured to: receive a sensor data packet for a scan area; a control circuit, coupled to the user interface, configured to: analyze the sensor data packet submitted to a multilayer neural network already trained including storing the sensor data packet; parse the sensor data packet with the multilayer neural network to generate real world endpoints and a bounding box including identifying the real world coordinates; apply line rules, including identifying a parking space by the real world endpoints including storing the real world endpoints in a storage circuit; compile an overhead depiction including boundary lines of the parking space identified by the real world endpoints and the bounding box in the scan area; merge vehicle maneuvering instructions into the overhead depiction for accessing the parking space; and present the overhead depiction for displaying on a user display. ### Claim 2 (depends on 1) The system as claimed in claim 1 wherein the control circuit is configured to: update a rules memory in a line rules module when the line rules are changed; and detect a motorcycle parking space or a handicapped parking space based on updating the line rules. ### Claim 3 (depends on 1) The system as claimed in claim 1 wherein the control circuit is configured to load real world coordinates in an endpoints and lines module to calculate the real world endpoints. ### Claim 4 (depends on 1) The system as claimed in claim 1 wherein the control circuit is configured to verify the sensor data packet including a scan of the scan area, real world coordinates of an optical sensor, and extrinsic parameters of the optical sensor. ### Claim 5 (depends on 1) The system as claimed in claim 1 wherein the control circuit is configured to generate the real world endpoints and the bounding box includes the control circuit performing a geometric conversion based on the real world coordinates of an optical sensor, and extrinsic parameters of the optical sensor. ### Claim 6 (depends on 1) The system as claimed in claim 1 wherein the control circuit is configured to detect a handicapped parking space by identifying a placard between the boundary lines. ### Claim 7 (depends on 1) The system as claimed in claim 1 wherein the control circuit configured to present the overhead depiction for displaying on a user display includes a device accessing the parking space identified by the multilayer neural network. ### Claim 8 (depends on 1) The system as claimed in claim 1 further comprising a communication circuit, coupled to the control circuit, configured to send the sensor data packet and receive the overhead depiction through a network for refining the multilayer neural network. ### Claim 9 A method of operation for a navigation system comprising: receiving a sensor data packet for a scan area; analyzing the sensor data packet submitted to a multilayer neural network already trained including storing the sensor data packet; parsing the sensor data packet with the multilayer neural network to generate real world endpoints and a bounding box including identifying the real world coordinates; applying line rules, including identifying a parking space by the real world endpoints including storing the real world endpoints in a storage circuit; compiling an overhead depiction including boundary lines of the parking space identified by the real world endpoints and the bounding box in the scan area; merging vehicle maneuvering instructions into the overhead depiction for accessing the parking space; and presenting the overhead depiction for displaying on a user display. ### Claim 10 (depends on 9) The method as claimed in claim 9 further compromising: updating a rules memory in a line rules module when the line rules are updated; and detecting a motorcycle parking space or a handicapped parking space based on updating the line rules. ### Claim 11 (depends on 9) The method as claimed in claim 9 further comprising loading real world coordinates in an endpoints and lines module to calculate the real world endpoints. ### Claim 12 (depends on 9) The method as claimed in claim 9 further comprising verifying the sensor data packet including a scan of the scan area, real world coordinates of an optical sensor, and extrinsic parameters of the optical sensor. ### Claim 13 (depends on 9) The method as claimed in claim 9 further comprising generating the real world endpoints and the bounding box includes performing a geometric conversion based on the real world coordinates of an optical sensor, and extrinsic parameters of the optical sensor. ### Claim 14 (depends on 9) The method as claimed in claim 9 further comprising detecting a handicapped parking space by identifying a placard between the boundary lines. ### Claim 15 A non-transitory computer readable medium including instructions for a navigation system comprising: receiving a sensor data packet for a scan area; analyzing the sensor data packet submitted to a multilayer neural network already trained including storing the sensor data packet; parsing the sensor data packet with the multilayer neural network to generate real world endpoints and a bounding box including identifying the real world coordinates; applying line rules, including identifying a parking space by the real world endpoints including storing the real world endpoints in a storage circuit; compiling an overhead depiction including boundary lines of the parking space identified by the real world endpoints and the bounding box in the scan area; merging vehicle maneuvering instructions into the overhead depiction for accessing the parking space; and presenting the overhead depiction for displaying on a user display. ### Claim 16 (depends on 15) The non-transitory computer readable medium including the instructions as claimed in claim 15 further compromising: updating a rules memory in a line rules module when the line rules are updated; and detecting a motorcycle parking space or a handicapped parking space based on updating the line rules. ### Claim 17 (depends on 15) The non-transitory computer readable medium including the instructions as claimed in claim 15 further comprising loading real world coordinates in an endpoints and lines module to calculate the real world endpoints. ### Claim 18 (depends on 15) The non-transitory computer readable medium including the instructions as claimed in claim 15 further comprising verifying the sensor data packet including a scan of the scan area, real world coordinates of an optical sensor, and extrinsic parameters of the optical sensor. ### Claim 19 (depends on 15) The non-transitory computer readable medium including the instructions as claimed in claim 15 further comprising generating the real world endpoints and the bounding box includes performing a geometric conversion based on the real world coordinates of an optical sensor, and extrinsic parameters of the optical sensor. ### Claim 20 (depends on 15) The non-transitory computer readable medium including the instructions as claimed in claim 15 further comprising detecting a handicapped parking space by identifying a placard between the boundary lines.