Finding Lane Lines on the Road

Finding Lane Lines on the Road

The goals / steps of this project are the following:

• Make a pipeline that finds lane lines on the road
• Reflect on your work in a written report

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Reflection

1. Describe your pipeline. As part of the description, explain how you modified the draw_lines() function.

The main part of the pipeline consisted of following steps:

• Take the image
• use opencv to create a gray scaled image
• apply gaussian smoothing on it using Gaussian Blur of opencv.
• then it uses a canny filter to detect edges in the image using the color gradient. The parameters are hardcoded.
• then the algo ignores areas which are not of interest. Mainly in the center, were the camera recorded the lane lines of our lane.
• On that image, we apply the Hough transformation to find lines. We recieve for every detected line its location.
• To decide, which lines are relevant or not relevant, only certain slopes are alowed for the left and the right lane line. Other lines are ignored.
• The slope of the relevant lines are then avaraged for the right and left side.
• Using this avaraged slope and coordinates of the detected lines, we draw the linear function on top of the image with wich we started at the beginning.
• The result is that the linear function lies mostly directly on the correctly detected line.

Using the functionality mentioned above, we apply it on video which are a collection of images.

2. Identify potential shortcomings with your current pipeline

Shortcomings:

• Hardcoded parameters are used.
• Ansatz is heuristic! No machine learning is used to fine tune the parameters.
• Calibration of camera and coordinate system of the vehicle is missing.
• Linear function is not the best model for lane lines used.

3. Suggest possible improvements to your pipeline

• A possible improvement would be to write better python code. Since it is my first time with python, it is acceptable.
• Devide code in more functions.
• Use classes and objects.