Artificial Intelligence for Urban Traffic Management and control
This webpage is dedicated to the UKRI Future Leaders Fellowship "Artificial Intelligence for Autonomic Urban Traffic Control" and to the research on the broader topic of AI for urban traffic management and control performed by Dr Mauro Vallati and his team at the University of Huddersfield.
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.
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. The proposed line of research aims at designing and creating an autonomic urban traffic management and control framework, to anticipate and avoid environmental and mobility issues, and to maximise traffic flows and network use.
I am a Reader in Artificial Intelligence at the University of Huddersfield. My research is about real-world applications of Artificial Intelligence, with a focus on Traffic Control and Healthcare.
Additional information on my website.
This work is funded by UKRI