In these projects I used Computer Vision and Machine Learning to detect and track lanes and vehicles. 

In the lane tracking project (green overlay) I built a lane-finding algorithm that made use of distortion correction, color transforms, gradient thresholding, and image rectification. The algorithm proved to be robust enough to correctly detect the lanes even with rapidly changing pavement and shadows.

In the Vehicle Detection and Tracking Project (bounding boxes) I created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients, and support vector machines (SVM). Optimized and evaluated the model on video data from a dash cam taken during highway driving.