The transition toward fully autonomous vehicles AVs represents one of the most ambitious engineering endeavors of the 21st century. Promising to revolutionize transportation by improving safety, reducing traffic congestion, and enhancing mobility efficiency, self driving cars rely on a complex network of sensors, artificial intelligence AI , and continuous data processing. However, the successful operation of these vehicles depends on their ability to process vast amounts of data in real time. Traditional cloud computing architectures, which rely on transmitting data to centralized, remote servers for processing and analysis, struggle to meet the stringent requirements of autonomous driving. To overcome these limitations, edge computing has emerged as a foundational technology for autonomous vehicles. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the source of data generation the “edge” of the network. Edge computing drastically reduces latency, optimizes bandwidth usage, enhances data privacy, and ensures operational resilience even in areas with poor network connectivity. This paper explores the critical role of edge computing in autonomous vehicles. edge computing, cloud computing, autonomous vehicles AVs , automotive industry. 55-65 Issue-4 Volume-10 Matthew N. O. Sadiku | Paul A. Adekunte | Janet O. Sadiku