The AWS DeepRacer, a fully autonomous 1/18th scale race car powered by an Intel Atom Processor, is designed to deploy advanced control algorithms including reinforcement learning, model predictive control, and imitation learning. Our team has access to several AWS DeepRacers, and we are dedicated to utilizing these vehicles to build a realistic model of an urban intersection.

The primary goal of this project is to design and implement a 1/18th scale urban intersection, equipped with traffic lights and road surface markings. We plan to develop an advanced sensing system that employs the DeepRacer's built-in sensors or external cameras to accurately monitor each vehicle's location and movement within the model. Furthermore, we aim to design a comprehensive control system that manages the vehicles' operations using real-world data, ensuring a genuine and dynamic display of autonomous vehicle technology.

Task:
Design and construct a detailed 1/18th scale model of an urban intersection, featuring key elements such as traffic lights and road markings.

Develop and integrate a sensing system to observe and track the position of each AWS DeepRacer in the model environment, using the vehicle's onboard sensors or external camera systems as necessary.

Create a sophisticated control system capable of directing the autonomous vehicles based on the gathered data, aiming to replicate realistic urban traffic conditions.