One of the pivotal challenges presented to urban road traffic controllers is the effective utilisation of transport infrastructure, as a result of growing urbanisation, the finite network capacity, and of the increasing number of road vehicles. In this context, the arrival of connected autonomous vehicles (CAVs) represents a unique opportunity for a fundamental change in urban mobility, and urban traffic control should take an active role in integrating CAVs into the mobility ecosystem in order to maximise benefits. To support this integration, we propose to leverage on a centralised architecture that can exploit, for instance, Artificial Intelligence techniques to distribute vehicles in a controlled urban region, with the aims of reducing congestion and fostering a balanced use of the available road network. In this paper, we describe the overall framework that is under development in the AI4ME project, funded by the UK Engineering and Physical Sciences Research Council. Further, we demonstrate the impact of the proposed approach using real-world historical data of a large UK town.
|Title of host publication||Proceedings of the 27th Intelligent Transportation Systems World Congress (ITS 2020)|
|Publication status||Accepted/In press - 14 Apr 2020|
|Event||27th Intelligent Transportation Systems World Congress: The New Age of Mobility - Los Angeles Convention Center, Los Angeles, United States|
Duration: 4 Oct 2020 → 8 Oct 2020
Conference number: 27
|Conference||27th Intelligent Transportation Systems World Congress|
|Period||4/10/20 → 8/10/20|