Self Driving Car Engineer Project 4 - Advanced Lane Line Detection

Benjamin Söllner, 22 Jun 2017

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The goals / steps of this project are the following:

• Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.
• Apply a distortion correction to raw images.
• Use color transforms, gradients, etc., to create a thresholded binary image.
• Apply a perspective transform to rectify binary image ("birds-eye view").
• Detect lane pixels and fit to find the lane boundary.
• Determine the curvature of the lane and vehicle position with respect to center.
• Warp the detected lane boundaries back onto the original image.
• Output visual display of the lane boundaries and numerical estimation of lane curvature and vehicle position.

Files Submitted

My project includes the following files:

• CarND 04 Advanced Lane Line Detection.ipynb / .html: the (rendered) iPython notebook with the algorithm
• writeup_report.md / .html: the writeup of this project including the showcase images (you are reading it)
• project_video_output.mp4: the output video with lane line markings and lane metrics