# US 12,110,009 B2 · Parking space detection method and system

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- Number: US 12,110,009 B2
- Document ID: US12110009B2
- Status: Granted
- Kind: B2
- Application number: 18/151,069
- Filed: 2023-01-06
- Published: 2024-07-11
- Granted: 2024-10-08
- Earliest claimed: 2023-01-06
- Assignees: Valeo Schalter und Sensoren GmbH
- Applicants: Valeo Schalter und Sensoren GmbH
- Inventors: Lihao Wang; Antonyo Musabini; Christel Leonet; Rachid Benmokhtar
- Web page: https://patentgrep.com/patent/US12110009B2

## CPC

- B60W 30/06: Automatic manoeuvring for parking
- G08G 1/146: {where the parking area is a limited parking space, e.g. parking garage, restricted space}
- B60R 1/22: for viewing an area outside the vehicle, e.g. the exterior of the vehicle
- G06V 10/46: Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features (colour feature extraction G06V10/56)
- G06V 10/82: using neural networks
- G06V 20/586: {of parking space}
- G08G 1/143: {inside the vehicles}
- G08G 1/144: {on portable or mobile units, e.g. personal digital assistant [PDA]}
- G08G 1/147: {where the parking area is within an open public zone, e.g. city centre}
- B60R 2300/607: from a bird's eye viewpoint
- B60R 2300/806: for aiding parking
- B60W 2420/403: Image sensing, e.g. optical camera
- 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
- 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})
- B60R: VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

A method that includes obtaining a first image from a first camera disposed on a vehicle and generating a birds-eye view (BEV) image using the first image. The method further includes processing, with a machine-learned model, the BEV image to produce parking slot prediction data. The parking slot prediction data includes a first center coordinate for a first available parking slot, a first parking slot confidence, and a first corner displacement data. The first corner displacement data includes a first relative coordinate pair that locates a first corner relative to the first center coordinate and a second relative coordinate pair that locates a second corner relative to the first center coordinate. The method further includes determining a first location of the first available parking slot using the parking slot prediction data and parking the vehicle in the first available parking slot when the first parking slot confidence meets a threshold.

## Claims

### Claim 1

A method, comprising:
obtaining a first image from a first camera disposed on a vehicle;
generating a birds-eye view (BEV) image using the first image;
processing, with a machine-learned model, the BEV image to produce parking slot prediction data, wherein the parking slot prediction data comprises:
a first center coordinate for a first available parking slot;
a first corner displacement data, comprising:
a first relative coordinate pair that locates a first corner relative to the first center coordinate; and
a second relative coordinate pair that locates a second corner relative to the first center coordinate;
a first parking slot confidence;
determining a first location of the first available parking slot using the parking slot prediction data; and
parking the vehicle in the first available parking slot when the first parking slot confidence meets a threshold.

### Claim 2 (depends on 1)

The method of claim 1, wherein the parking slot prediction data further comprises:
a second center coordinate for a second available parking slot;
a second corner displacement data, comprising:
a third relative coordinate pair that locates a third corner relative to the second center coordinate;
a fourth relative coordinate pair that locates a fourth corner relative to the second center coordinate; and
the method further comprising determining a second location of the second available parking slot using the parking slot prediction data.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
obtaining a second image from a second camera disposed on the vehicle;
wherein the BEV image is generated using the first image and the second image.

### Claim 4 (depends on 1)

The method of claim 1, wherein the BEV image is generated through inverse perspective mapping.

### Claim 5 (depends on 1)

The method of claim 1, wherein while parking the vehicle, the first center coordinate and first corner displacement data are continuously updated based on the machine-learned model processing newly generated BEV images.

### Claim 6 (depends on 1)

The method of claim 1, further comprising:
representing the first available parking slot with a first parking representation, wherein the first parking representation is fully specified by the first center coordinate and the first corner displacement data;
determining one or more entry lines for the first available parking slot; and
determining an area enclosed by the first parking representation.

### Claim 7 (depends on 1)

The method of claim 1, wherein the parking slot prediction data further comprises:
a first corner visibility data, wherein the first corner visibility data indicates whether each corner in the first corner displacement data is visible or occluded; and
a first slot surface material, wherein the first slot surface material specifies a material class for the first available parking slot.

### Claim 8 (depends on 1)

The method of claim 1, further comprising:
determining a slot orientation for the first available parking slot, wherein the slot orientation is one of: perpendicular, parallel, and fishbone.

### Claim 9

A system, comprising:
a vehicle;
a first camera disposed on the vehicle;
a birds-eye view (BEV) image;
a machine-learned model; and
a computer, comprising one or more computer processors, the computer configured to:
obtain a first image from the first camera;
construct the BEV image from the first image;
process, with the machine-learned model, the BEV image to produce parking slot prediction data, wherein the parking slot prediction data comprises:
a first center coordinate for a first available parking slot;
a first corner displacement data, comprising:
a first relative coordinate pair that locates a first corner relative to the first center coordinate; and
a second relative coordinate pair that locates a second corner relative to the first center coordinate; and
a first parking slot confidence;
determine a first location of the first available parking slot using the parking slot prediction data; and
park the vehicle in the first available parking slot without the assistance of a driver when the first parking slot confidence meets a threshold.

### Claim 10 (depends on 9)

The system of claim 9, wherein the parking slot prediction data further comprises:
a second center coordinate for a second available parking slot;
a second corner displacement data, comprising:
a third relative coordinate pair that locates a third corner relative to the second center coordinate;
a fourth relative coordinate pair that locates a fourth corner relative to the second center coordinate; and
a second parking slot confidence;
wherein the computer is further configured to determine a second location of the second available parking slot using the parking slot prediction data.

### Claim 11 (depends on 9)

The system of claim 9, further comprising:
a second camera disposed on the vehicle,
wherein the computer is further configured to:
obtain a second image from the second camera; and
construct the BEV image using the first image and the second image.

### Claim 12 (depends on 9)

The system of claim 9, wherein while parking the vehicle, the first center coordinate and first corner displacement data are continually updated using the machine-learned model processing newly obtained BEV images.

### Claim 13 (depends on 9)

The system of claim 9, wherein the parking slot prediction data further comprises:
a first corner visibility data, wherein the first corner visibility data indicates whether each corner in the first corner displacement data is visible or occluded; and
a first slot surface material, wherein the first slot surface material specifies a material class for the first available parking slot.

### Claim 14 (depends on 9)

The system of claim 9, wherein the computer is further configured to:
determine a slot orientation for the first available parking slot, wherein the slot orientation is one of: perpendicular, parallel, and fishbone.