This technical book outlines the development of a control architecture for autonomous vehicles. The objective is to design a comprehensive control architecture for autonomous vehicles, encompassing essential elements such as navigation, map building, and memory management. The focus is on the intricate details of module interfaces, data structures, and the selection of appropriate algorithms. Leveraging research at Sydney University's "SUAVE" experimental platform (1993), the book delves into the setup of autonomous vehicles, including the integration of control hardware, motion controllers, and ultrasonic sensors. It discusses the implementation of map building algorithms and control architecture across two computers: one interfacing with sensors and the other managing control architecture and navigation. The design principles are rooted in established literature on control architectures, navigation techniques, and map building for autonomous mobile vehicles (AMVs). Detailed design and implementation of the navigation module, map building, and memory management algorithms are a key focus, with development carried out in C. The book emphasizes extensive simulations across various AMV missions to assess the performance of these modules. The navigation module proved adept at creating smooth navigation paths and effectively managing obstacles, including dynamic ones. The local map structure is optimized for memory efficiency and processing speed, ensuring accurate obstacle representation. The ultrasonic sensor model incorporates a Kalman Filter to minimize noise. The overall control architecture is highlighted for its flexibility and effectiveness, with all software components developed in C.