This guide presents a structured and comprehensive framework for understanding, assessing and progressively advancing autonomous cities. It defines autonomous cities as urban environments in which constituent systems such as mobility, energy, water, safety, health, public services and digital infrastructure operate with varying levels of sensing, decision-making, execution and learning capability. The concept is not intended to imply a city without human governance. Rather, it describes a continuum in which human institutions, public objectives and autonomous technologies interact to improve urban performance and resilience.
The report begins by distinguishing autonomous systems from automated systems. Automated systems execute pre-defined tasks with limited human intervention, whereas autonomous systems can perceive their environment, process information, make decisions and adapt behaviour within defined operational boundaries. Artificial intelligence, including machine learning, computer vision, natural language processing, large language models and agentic AI, is an important enabler of autonomy. However, autonomy also depends on sensors, actuators, control systems, data governance, operational procedures and institutional safeguards.
