CarND-LaneLines-P1

Project 1 for Udacity's Self-Driving Car Engineer Nanodegree Program

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

Original	Original w/ lane lines

Reflections

The pipeline

The pipeline went through a series of steps:

1. OpenCV gray scale
2. OpenCV Gaussian Blur
3. OpenCV Canny function
4. Create a masked area to focus on
5. Hough lines and modify draw_lines() to draw one straight line

Modifying draw_lines() was done by finding which points belonged to which lane line through their slope.

• Left lane: x increases, while y decreases

• Right lane: x increases, while y increases

Once we separate the segment into either or, we can then find the average of their points to create an average lane line from all the segments. Arbitrary y1 and y2 for the final lines are given by the image's shape to look consistent.

6. Apply the new averaged lines to original image

Shortcomings with current pipeline

• Being dynamic. A road consists of much more than straight paths, so a curve will most definitely show this pipeline's weaknesses.
• Shadows. I tried my implementation with the challenge.mp4 and the shadows would trip up the lines.
• The values for kernel, rho, and etc. I feel like they're arbitrary. They only look good for a certain image quality. I feel like given another video or image of a different format, size, or quality would make me change values of the region of interest and other varibles.

Improvements

Trying to find a way to curve with the lane lines and when an image changes with a shadow. The next lesson goes into HSV and HSL so I believe applying those effects might help.