School of Computer Science and Statistics
Vinny Cahill Model-based RL has become the state-of-the-art approach in the field of reinforcement learning, where agents learn to solve problems through trial and error. Unlike model-free RL, model-based RL first learns a world model from the actual environment. The agent is then trained within this world model before being evaluated in the real environment. However, most … Read more
So-called ‘capacity drop’ is a phenomenon that sometimes occurs when joining vehicles interrupt the flow of traffic on a motorway, effectively reducing the capacity of the road. To address this problem, this project will investigate the design of a cooperative motorway on-ramp merging algorithm for automated vehicles. From the perspective of vehicles joining the motorway, … Read more
This project will investigate the use of reinforcement learning to develop a highway journey booking system incorporating a dynamic pricing strategy to allow traffic demand to be shaped in ways that will improve traffic efficiency and enhance sustainability by reducing emissions and fuel consumption. The goal will be to evaluate the potential benefit of the … Read more
A ‘digital twin’ is a digital model of a real physical artefact or environment that mirrors the state of its real-world counterpart (ideally) in real time by integrating data available via the ‘Internet of Things’ (IoT). A digital twin of a roadway would represent the physical road and its current traffic flow and provide a … Read more
An ideal bus route would offer highly predictable journey times to travellers so that the same journey taken at the same time of day on different occasions would take the same amount of time. While there are many sources of variability in journey times such as traffic conditions, passenger boarding and offloading time, and the … Read more
Large-scale deployment of (semi-)automated vehicles (AVs) is inevitable. However, the benefits of this deployment for traffic management in a world in which AVs and other vehicles will necessarily coexist (i.e., in ‘mixed’ traffic) remain unclear. Reduced congestion, greater energy efficiency, and improved resilience of the traffic system to unexpected events are expected. In this context, … Read more
The SFI-funded ClearWay project is investigating new models of road management is which each vehicle is allocated a slot in which to travel for the duration of its journey. Adherence to travelling in its allocated slot ensures congestion-free travel from source to destination for each vehicle (in the absence of unexpected events). A central control … Read more