The rapid advancement of new energy vehicle technology, coupled with the integration of artificial intelligence (AI), has significantly contributed to the development of intelligent connected vehicles (ICVs). These vehicles, equipped with the Internet of Things (IoT) and advanced end devices, can sense their surroundings, engage in adaptive learning, and perform autonomous driving tasks. Central to the future of ICVs is the human-vehicle-road collaborative perception system, which enables dynamic, multi-dimensional interaction between drivers, vehicles, and road infrastructure. This paper explores the key technologies that underpin this collaboration, focusing on the integration of perception systems, communication technologies, and AI-driven big data analytics. It also addresses the challenges associated with data privacy, real-time traffic management, and the technical bottlenecks in current intelligent transportation systems. The research highlights the importance of sensor fusion, V2X communication, and AI-based decision making in achieving fully autonomous driving and intelligent traffic management. The study provides a detailed examination of the technological ecosystem required for the effective operation of ICVs, emphasizing the role of local processing systems and the development of infrastructure such as 5G networks, smart traffic signals, and energy-efficient solutions.