Vehicle and vehicle parking system
A vehicle is provided. The vehicle includes a camera configured to detect a target object in a parking space and a controller programmed to advance the vehicle into the parking space based on a yaw angle of the vehicle and a distance to the target object in response to the camera detecting the presence of the target object. The distance to the target object is based on a vector representing a boundary of the target object.
1. A method of parking a vehicle comprising:
detecting a target object in a parking space with a camera; and
advancing the vehicle into the parking space based on
an angle between the target object and a perpendicular of a camera field of vision, and
a distance from the camera to the target object based on a regression analysis that includes a vector representing a boundary segment of the target object as an input variable.
2. The method of claim 1 , wherein the vector is generated based on an observed horizontal projection of the boundary segment and a distortion of the target object.
3. The method of claim 2 , wherein the regression analysis also includes an angle between the vector and the horizontal projection as an input variable.
4. The method of claim 3 , wherein the regression analysis also includes a position of the target object in the camera field of vision as an input variable.
5. The method of claim 3 , wherein the distortion is based on a difference in position between a camera detected centroid of the target object and an expected centroid of the target object.
6. The method of claim 5 , wherein the expected centroid is generated based on an observed second boundary segment of the target object.
7. The method of claim 1 , wherein the distance from the camera to the target object is based on a single observation of the location the target object.
8. The method of claim 1 , wherein the regression analysis determines the distance to the target object based on the pixel location of the vector in the camera field of vision.
9. A vehicle comprising:
a camera configured to detect a target object in a parking space; and
a controller programmed to, in response to the camera detecting the target object, advance the vehicle into the parking space based on a vehicle yaw angle and a distance to the target object, the distance being based on a regression analysis that includes a vector representing a boundary segment of the target object as an input variable.
10. The vehicle of claim 9 , wherein the vector is generated based on an observed horizontal projection of the boundary segment and a distortion of the target object.
11. The vehicle of claim 10 , wherein the regression analysis also includes an angle between the vector and the horizontal projection as an input variable.
12. The vehicle of claim 11 , wherein the regression analysis also includes a position of the target object in a field of vision of the camera as an input variable.
13. The vehicle of claim 11 , wherein the distortion is based on a difference in position between a camera detected centroid of the target object and an expected centroid of the target object.
14. The vehicle of claim 13 , wherein the expected centroid is generated based on an observed second boundary segment of the target object.
15. The vehicle of claim 9 , wherein the regression analysis determines the distance to the target object based on the pixel location of the vector in the camera field of vision.
16. A vehicle comprising:
a camera configured to output a signal indicating the presence of a target object in a parking space; and
a controller in communication with the camera and programmed to, in response to receiving the signal, advance the vehicle into the parking space based on a distance from the camera to the target object and an angle between the target object and a perpendicular of a field of vision of the camera, the distance being based on a regression analysis that includes a vector representing a boundary segment of the target object, an angle between the vector and a horizontal projection of the boundary segment, and a position of the target object in the field of vision as input variables.
17. The vehicle of claim 16 , wherein the vector is generated based on the horizontal projection and a distortion of the target object.
18. The vehicle of claim 17 , wherein the distortion is based on a difference in position between a camera detected centroid of the target object and an expected centroid of the target object.
19. The vehicle of claim 18 , wherein the expected centroid of the target object is generated based on an observed second boundary segment of the target object.
20. The vehicle of claim 16 , wherein the regression analysis determines the distance to the target object based on the pixel location of the vector in the camera field of vision.