Intelligent Edge Computing for Autonomous Aerial and Vehicular Systems

The rapid evolution of intelligent transportation and autonomous systems is transforming the architecture of modern mobility networks. As connected vehicles, unmanned aerial vehicles, and smart infrastructure become increasingly widespread, the demand for real-time data processing and ultra-low-latency communication has surpassed the capabilities of traditional cloud-centric models. Meeting the stringent reliability, responsiveness, and scalability requirements of these dynamic environments requires rethinking not only how data is transmitted, but also where computation occurs. Intelligent edge computing has emerged as a key enabler, bringing processing power closer to vehicles, drones, and infrastructure rather than relying solely on distant data centers. This shift is rapidly becoming a foundational paradigm for next-generation autonomous and connected systems. Intelligent Edge Computing for Autonomous Aerial and Vehicular Systems examines the transformative role of edge intelligence in shaping the future of mobility, with particular emphasis on the convergence of vehicular networks and unmanned aerial systems. This book explores how artificial intelligence, machine learning, and distributed computing can be deployed at the network edge to support real-time, mission-critical operations across vehicles, drones, and intelligent transportation infrastructure. Covering topics such as adversarial attacks, fog computing, and vehicular ad hoc networks, this book is an essential resource for graduate students, doctoral researchers, autonomous systems engineers, telecommunications professionals, policymakers, and industry practitioners.