VEHICLE PARKING ASSIST SYSTEM WITH VISION-BASED PARKING SPACE DETECTION

• US 20170017848A1
• Filed: 07/14/2016
• Published: 01/19/2017
• Est. Priority Date: 07/17/2015
• Status: Active Grant

• Current Assignee: Magna Electronics Incorporated (Magna International Incorporated)
• Original Assignee: Magna Electronics Incorporated (Magna International Incorporated)
• Inventors: Gupta, Nikhil, Corral-Soto, Eduardo R.
• Granted Patent: US 10,078,789 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2422/00 Indexing codes relating to the special location or mounting of sensors
• CPC Class Codes: B60W 30/06 Automatic manoeuvring for parking
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G06V 20/586 of parking space
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/0962 having an indicator mounted inside the vehicle, e.g. giving voice messages
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: G08G 1/168 Driving aids for parking, e.g. acoustic or visual feedback on parking space

Abstract

A parking assist system of a vehicle includes a camera that, when disposed at the vehicle, has a field of view exterior of the vehicle. An image processor is operable to process image data captured by the camera to detect parking space markers indicative of a parking space and to identify empty or available parking spaces. The image processor includes a parking space detection algorithm that detects parking space markers by (i) extracting low level features from captured image data, (ii) classifying pixels as being part of a parking space line or not part of a parking space line, (iii) performing spatial line fitting to find lines in the captured images and to apply parking space geometry constraints, and (iv) detecting and selecting rectangles in the captured images.

Claims

1. A parking assist system of a vehicle, said parking assist system comprising:

a camera configured to be disposed at a vehicle, wherein said camera, when disposed at the vehicle, has a field of view exterior of the vehicle;

an image processor operable to process image data captured by said camera;

wherein said image processor processes captured image data to detect parking space markers indicative of a parking space and to identify empty or available parking spaces; and

wherein said image processor comprises a parking space detection algorithm that detects parking space markers by (i) extracting low level features from captured image data, (ii) classifying pixels as being part of a parking space line or not part of a parking space line, (iii) performing spatial line fitting to find lines in the captured images and to apply parking space geometry constraints, and (iv) detecting and selecting rectangles in the captured images.

2. The parking assist system of claim 1, wherein said camera comprises a pixelated imaging array having a plurality of photosensing elements.

3. The parking assist system of claim 2, wherein said camera comprises a grayscale camera.

4. The parking assist system of claim 1, wherein the detected rectangles are processed to construct hypothesized parking rectangles, whereby said parking space detection algorithm selects an optimal rectangle using machine learning concepts.

5. The parking assist system of claim 1, comprising a control that at least in part controls the vehicle to park the vehicle in a determined and identified empty or available parking space.

6. The parking assist system of claim 1, wherein said camera is part of a multi-camera vision system of the vehicle, and wherein said multi-camera vision system comprises a plurality of cameras disposed at the vehicle so as to have respective fields of view exterior the vehicle.

7. The parking assist system of claim 6, wherein said plurality of cameras comprises a front camera disposed at a forward portion of the vehicle and having a field of view forward of the vehicle, a driver-side camera disposed at a driver side of the vehicle and having a field of view sideward of the vehicle, a passenger-side camera disposed at a passenger side of the vehicle and having a field of view sideward of the vehicle, and a rear camera disposed at a rear portion of the vehicle and having a field of view rearward of the vehicle.

8. The parking assist system of claim 7, wherein said image processor processes image data captured by at least one of said front camera and said rear camera to detect parking space markers indicative of a parking space and to identify empty or available parking spaces.

9. The parking assist system of claim 1, wherein said parking space detection algorithm employs a recursive temporal stabilization mechanism that produces a stable rectangle parking space and is operable to predict parking lines and rectangles when they disappear from the field of view of said camera.

10. A parking assist system of a vehicle, said parking assist system comprising:

a plurality of cameras configured to be disposed at a vehicle so as to have respective fields of view exterior of the vehicle;

an image processor operable to process image data captured by said cameras;

wherein said image processor processes captured image data to (i) detect parking space markers indicative of a parking space and (ii) identify empty or available parking spaces; and

wherein said image processor comprises a parking space detection algorithm that detects parking space markers by (i) extracting low level features from captured image data, (ii) classifying pixels as being part of a parking space line or not part of a parking space line, (iii) performing spatial line fitting to find lines in the captured images and to apply parking space geometry constraints, and (iv) detecting and selecting rectangles in the captured images.

11. The parking assist system of claim 10, wherein each of said cameras comprises a pixelated imaging array having a plurality of photosensing elements.

12. The parking assist system of claim 11, wherein each of said cameras comprises a grayscale camera.

13. The parking assist system of claim 10, wherein the detected rectangles are processed to construct hypothesized parking rectangles, whereby said parking space detection algorithm selects an optimal rectangle using machine learning concepts.

14. The parking assist system of claim 10, comprising a control that at least in part controls the vehicle to park the vehicle in a determined and identified empty or available parking space.

15. The parking assist system of claim 10, wherein said cameras are part of a multi-camera vision system of the vehicle, and wherein image data captured by said cameras is used to provide a surround vision display for viewing by the driver of the vehicle.

16. The parking assist system of claim 10, wherein said plurality of cameras comprises a front camera disposed at a forward portion of the vehicle and having a field of view forward of the vehicle, a driver-side camera disposed at a driver side of the vehicle and having a field of view sideward of the vehicle, a passenger-side camera disposed at a passenger side of the vehicle and having a field of view sideward of the vehicle, and a rear camera disposed at a rear portion of the vehicle and having a field of view rearward of the vehicle.

17. The parking assist system of claim 10, wherein said parking space detection algorithm employs a recursive temporal stabilization mechanism that produces a stable rectangle parking space and is operable to predict parking lines and rectangles when they disappear from the field of view of said camera.

18. A parking assist system of a vehicle, said parking assist system comprising:

a plurality of cameras configured to be disposed at a vehicle so as to have respective fields of view exterior of the vehicle;

wherein said plurality of cameras comprises at least a front camera disposed at a forward portion of the vehicle and having a field of view forward of the vehicle, and a rear camera disposed at a rear portion of the vehicle and having a field of view rearward of the vehicle;

an image processor operable to process image data captured by said front and rear cameras;

wherein said image processor processes captured image data to (i) detect parking space markers indicative of a parking space and (ii) identify empty or available parking spaces;

wherein said image processor comprises a parking space detection algorithm that detects parking space markers by (i) extracting low level features from captured image data, (ii) classifying pixels as being part of a parking space line or not part of a parking space line, (iii) performing spatial line fitting to find lines in the captured images and to apply parking space geometry constraints, and (iv) detecting and selecting rectangles in the captured images;

wherein the detected rectangles are processed to construct hypothesized parking rectangles, whereby said parking space detection algorithm selects an optimal rectangle using machine learning concepts;

wherein said parking space detection algorithm employs a recursive temporal stabilization mechanism that produces a stable rectangle parking space and is operable to predict parking lines and rectangles when they disappear from the field of view of said camera; and

a control that at least in part controls the vehicle to park the vehicle in a determined and identified empty or available parking space.

19. The parking assist system of claim 18, wherein each of said cameras comprises a pixelated imaging array having a plurality of photosensing elements, and wherein each of said cameras comprises a grayscale camera.

20. The parking assist system of claim 18, wherein the detected rectangles are processed to construct hypothesized parking rectangles, whereby said parking space detection algorithm selects an optimal rectangle using machine learning concepts.