If you start your new job as a software developer, what you need to do on day 1 is to set up your environment. The developing environment can mean a lot of things for an experienced developer. But since you are a newbee, I guess your boss’s minimal expectation is to let the codebase run on your machine.

The goal of this project is to write a software pipeline to detect vehicles in a video.Here are links to the labeled data for vehicle and non-vehicle examples to train your classifier. These example images come from a combination of the GTI vehicle image database, the KITTI vision benchmark suite, and examples extracted from the project video itself. Also You are welcome and encouraged to take advantage of the recently released Udacity labeled dataset to augment your training data. Here’s a link to my video result

This project is one step furthur to the Lane Detection Basic. This project dose not require identify lane but also produce a measurement of lane`s curvature and vehicle position relative to the lane. Therefore, it requires some knowledge of camera calibration and image rectification. Here’s a link to my video result.

When we drive, we use our eyes to decide where to go. The lines on the road that show us where the lanes are act as our constant reference for where to steer the vehicle. Naturally, one of the first things we would like to do in developing a self-driving car is to automatically detect lane lines using an algorithm. Project repo can be found here