Skip to content

Latest commit

 

History

History
36 lines (25 loc) · 1.69 KB

README.md

File metadata and controls

36 lines (25 loc) · 1.69 KB
Raw

Advanced Lane Finding

Udacity - Self-Driving Car NanoDegree

This is the Advanced Lane Finding project from Udacity Self-Driving Car Engineer Nanodegree.

The goal of this project is to develop a pipeline to process a video stream from a forward-facing camera mounted on the front of a car and output an annotated video which identifies:

  • The positions of the lane lines
  • The location of the vehicle relative to the center of the lane
  • The radius of curvature of the road

Pipeline

The pipeline created for this project processes images in the following steps:

  • 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 the 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.

Dependencies:

Python 3.5 and the following dependencies:

Write-up

Check out the writeup template for this project and use it as a starting point for creating your own writeup.