Artificial Intelligence for Autonomic Urban Traffic Control

Over half of the world's population now lives in cities, and global urbanisation continues at a steady pace. As this trend continues, mobility is becoming an increasingly critical problem. In the UK alone, the cost of congestion reached nearly £8 billion in 2018 in lost time and fuel consumption, and has become a major health threat. At the same time, new modes of transport, such as Connected Autonomous Vehicles, and new business models (e.g., Mobility as a Service) are disrupting the transportation sector. The traffic control industry has to reinvent itself to operate in a world of decentralised control (vehicles making decisions), ubiquitous sensor information, increasing urbanisation pressure, and large-scale interconnectivity. Artificial Intelligence provides a range of approaches that can leverage the growing volume of available data, and the knowledge gained by traffic authorities in the past decades, to support urban mobility. In particular, the proposed line of research aims at designing and creating an autonomic urban traffic management and control framework. The autonomic framework will have the capability to self-manage and self-configure, and will have an holistic view of the condition of the controlled region to proactively act to prevent environmental and mobility issues, or react to mitigate observed problems.