School of Computer Science and Statistics
Traffic networks can be significantly affected by unexpected events such as accidents, road closures or sudden congestion. Conventional route-planning approaches may struggle to adapt efficiently to these changes. This project investigates whether reinforcement learning can learn adaptive routing strategies that respond to unexpected disruptions. The learned approach will be evaluated in a simulated transport network … Read more
Vehicles approaching highway merges or lane-changing situations need to coordinate their actions to maintain safety and traffic efficiency. This project investigates whether multiple reinforcement learning agents can learn cooperative lane-changing strategies. Different training approaches will be compared with conventional rule-based strategies. The project will evaluate their impact on traffic safety, travel time and overall traffic … Read more
Choosing the best route through a city is challenging because traffic conditions change continuously. Reinforcement learning (RL) provides a way for an agent to learn effective route-selection strategies by interacting with a simulated transport network. This project will investigate whether an RL-based approach can learn to select routes that reduce travel time and congestion compared … Read more
Different travellers may have different preferences when choosing how and when to travel. While some may prioritise travel time, others may prefer cheaper, less crowded or more environmentally friendly options. This project investigates whether reinforcement learning can be used to learn personalised mobility recommendations based on individual preferences and feedback. The project will explore how … Read more
In cooperative multi-agent reinforcement learning, several agents have to learn how to work together. A challenge is that they can sometimes settle on a reasonably good way of cooperating, even though a much better joint solution exists. This project investigates whether the way learning experiences are selected and used during training could influence which solution … Read more
Drying clothes outdoors is one of the most affordable and environmentally friendly methods, but in Ireland’s unpredictable weather, laundry that is nearly dry can quickly become wet again. This project will focus on the design and development of a smart laundry drying assistant that helps users make better decisions about when to dry clothes outside. … Read more
Before fully autonomous driving is achieved, connected autonomous vehicles (CAVs) will operate for a certain period in mixed traffic, which includes both CAVs and human-driven vehicles (HDVs). The dynamic and interactive conditions in mixed traffic scenarios renders CAV decision making particularly challenging. This project will investigate the use of Graph Convolutional Deep Reinforcement Learning for … Read more
Forecasting the onset of conflict at a fine-grained temporal level has important implications for early-warning systems and can provide timely information to policymakers, humanitarian organisations, and peacekeeping actors. Typical conflict prediction methods rely on variables such as political instability, economic conditions, population characteristics, or historical conflict patterns. However, this data is often relatively coarse in … Read more
A previous MSc student built HydroNav (https://hydronav-frontend.vercel.app/), a platform that estimates Ireland’s green hydrogen production potential from renewable electricity and scores candidate facility sites on a national grid. That work established a useful pipeline and a working codebase, but its central quantity rests on a definition that does not match how the Irish system actually … Read more
Project Description: Optical fibre networks are critical to global connectivity, yet they are susceptible to accidental damage or deliberate tampering. While distributed acoustic sensing (DAS) has been widely investigated for disturbance detection, an alternative approach relies on monitoring the state of polarisation (SOP) of light propagating in the fibre. The SOP is highly sensitive to … Read more