Traffic optimization is an issue that affects everyone on a daily basis. Traffic signals can be the most frustrating aspect of driving – especially when they are poorly optimized to deal with dynamic traffic flow. With this project I successfully developed an algorithm that can optimize traffic signal patterns on grids of any shape and length. Given a starting population of cars, my implementation of a genetic algorithm was able to determine the pattern of light signals that would minimize the amount of time cars spent waiting at traffic lights. The algorithm computes an optimal light sequence in a realistic amount of time but also has the ability to be scaled back to produce less optimal sequences in exchange for faster run times.