Abstract: The global automotive industry is undergoing a once-in-a-century transformation, in which the convergence of intelligence and connectivity represents not merely a technological evolution but a strategic imperative with far-reaching implications for national industrial competitiveness, transportation system restructuring, and overall societal efficiency. Drawing on systems engineering principles, this paper systematically examines six dimensions of transformative change in intelligent connected vehicles (ICVs), including electronic/electrical architectures, development paradigms, and safety assurance frameworks. It further provides an in-depth analysis of the Vehicle-Road-Cloud Integration architecture from the perspective of cyber-physical systems (CPS) theory. Evidence from both academic research and industrial practice demonstrates that the linear extension of vehicle-centric intelligence faces fundamental systemic constraints, including limitations in physical perception, diminishing returns on computing investment, and persistent challenges posed by long-tail safety scenarios. The deep integration of data-driven intelligence with networked collaboration has emerged not only as a critical pathway for overcoming these constraints, but also as the fundamental direction for the next generation of intelligent driving technologies. Building on this analysis, the paper proposes a systematic framework comprising five foundational platforms—cloud control, high-definition mapping, on-board terminals, computing infrastructure, and cybersecurity. Together, these platforms provide the technological foundation for large-scale industrial deployment and the development of open ecosystem. Given that both automobiles and ships can be regarded representative intelligent mobile platforms, the technological evolution patterns and system architecture insights discussed in this paper may offer useful reference for research and practical implementation in the field of ship intelligence.