Parabolic lane boundary model
parabolicLaneBoundary object contains information about a parabolic
lane boundary model.
To generate parabolic lane boundary models that fit a set of boundary points and an
approximate width, use the
findParabolicLaneBoundaries function. If
you already know your parabolic parameters, create lane boundary models by using the
parabolicLaneBoundary function (described here).
creates an array of parabolic lane boundary models from an array of
boundaries = parabolicLaneBoundary(
B C] parameters for the parabolic equation y =
Ax2 + Bx +
C. Points within the lane boundary models are in world
parabolicParameters — Coefficients for parabolic models
[A B C] real-valued vector | matrix of
[A B C] values
Coefficients for parabolic models of the form y =
Bx + C, specified as an
[A B C] real-valued vector or as a matrix of
[A B C] values. Each row of
parabolicParameters describes a separate
parabolic lane boundary model.
Parameters — Coefficients for parabolic model
[A B C] real-valued vector
Coefficients for a parabolic model of the form
y = Ax2 +
Bx + C, specified as a real-valued vector of the form
[A B C].
BoundaryType — Type of boundary
Type of lane boundary, specified as a
LaneBoundaryType enumeration. Supported lane boundary types are:
Lane boundary objects always return
BoundaryType as type
Solid. Update these types to match the types of the lanes that are being fitted. To update a lane boundary type, use the
LaneBoundaryType. syntax. For example, this code sample shows how to update the first output lane boundary to type
boundaries(1) = LaneBoundaryType.BottsDots;
Strength — Strength of boundary model
Strength of the boundary model, specified as a real scalar.
Strength is the ratio of the number of unique x-axis locations on the boundary to the length of the boundary specified by the
XExtent property. A solid line without any breaks has a higher strength than a dotted line that has breaks along the full length of the boundary.
XExtent — Length of boundary along x-axis
[minX maxX] real-valued vector
Length of the boundary along the x-axis, specified as a real-valued vector of the form
[minX maxX] that describes the minimum and maximum x-axis locations.
|Obtain y-coordinates of lane boundaries given x-coordinates|
Create Parabolic Lane Boundaries
Create left-lane and right-lane parabolic boundary models.
llane = parabolicLaneBoundary([-0.001 0.01 0.5]); rlane = parabolicLaneBoundary([-0.001 0.01 -0.5]);
Create a bird's-eye plot and lane boundary plotter. Plot the lane boundaries.
bep = birdsEyePlot('XLimits',[0 30],'YLimits',[-5 5]); lbPlotter = laneBoundaryPlotter(bep,'DisplayName','Lane boundaries'); plotLaneBoundary(lbPlotter, [llane rlane]);
Find Parabolic Lane Boundaries in Bird's-Eye-View Image
Find lanes in an image by using parabolic lane boundary models. Overlay the identified lanes on the original image and on a bird's-eye-view transformation of the image.
Load an image of a road with lanes. The image was obtained from a camera sensor mounted on the front of a vehicle.
I = imread('road.png');
Transform the image into a bird's-eye-view image by using a preconfigured sensor object. This object models the sensor that captured the original image.
bevSensor = load('birdsEyeConfig'); birdsEyeImage = transformImage(bevSensor.birdsEyeConfig,I); imshow(birdsEyeImage)
Set the approximate lane marker width in world units (meters).
approxBoundaryWidth = 0.25;
Detect lane features and display them as a black-and-white image.
birdsEyeBW = segmentLaneMarkerRidge(im2gray(birdsEyeImage), ... bevSensor.birdsEyeConfig,approxBoundaryWidth); imshow(birdsEyeBW)
Obtain the image coordinates corresponding to the lane candidate positions. The
find function returns pixel indices that correspond to the candidate lane positions. By convention, the order of the image coordinates is always reversed relative to the pixel indices. For more information about image coordinates, see Coordinate Systems.
Obtain the corresponding lane boundary points in vehicle coordinates by using the
[imageY,imageX] = find(birdsEyeBW); xyBoundaryPoints = imageToVehicle(bevSensor.birdsEyeConfig,[imageX,imageY]);
Find lane boundaries in the image by using the
findParabolicLaneBoundaries function. By default, the function returns a maximum of two lane boundaries. The boundaries are stored in an array of
boundaries = findParabolicLaneBoundaries(xyBoundaryPoints,approxBoundaryWidth);
insertLaneBoundary to overlay the lanes on the original image. The
XPoints vector represents the lane points, in meters, that are within range of the ego vehicle's sensor. Specify the lanes in different colors. By default, lanes are yellow.
XPoints = 3:30; figure sensor = bevSensor.birdsEyeConfig.Sensor; lanesI = insertLaneBoundary(I,boundaries(1),sensor,XPoints); lanesI = insertLaneBoundary(lanesI,boundaries(2),sensor,XPoints,'Color','green'); imshow(lanesI)
View the lanes in the bird's-eye-view image.
figure BEconfig = bevSensor.birdsEyeConfig; lanesBEI = insertLaneBoundary(birdsEyeImage,boundaries(1),BEconfig,XPoints); lanesBEI = insertLaneBoundary(lanesBEI,boundaries(2),BEconfig,XPoints,'Color','green'); imshow(lanesBEI)
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
To select a set of parabolic lane boundary models from an array of
parabolicLaneBoundary objects, use either indexing by position or linear
indexing. Logical indexing is not supported. For example,
boundaries = findParabolicLaneBoundaries(xyBoundaryPoints,... approxBoundaryWidth);
boundaries = 1×5 parabolicLaneBoundary array with properties: Parameters BoundaryType Strength XExtent Width
index = [1 3 5]; selectedBoundaries = boundaries(index)
selectedBoundaries = 1×3 parabolicLaneBoundary array with properties: Parameters BoundaryType Strength XExtent Width
Introduced in R2017a