Mitigating Bus Bunching using Reinforcement Learning – No longer available

An ideal bus route would offer highly predictable inter-bus arrival times to travellers, in particular, overcoming the well-known ‘bus bunching’ phenomenon – “I waited ages then three came together!”. There are many sources of variability in journey times such as traffic conditions, the impact of traffic lights, and interference between buses themselves, e.g.,  queueing at … Read more

Improving Urban Travel-time Reliability with Connected and Automated Vehicles and Reinforcement Learning – No longer available

Poor travel-time reliability (TTR) in our cities means that travel times for the same journey are both highly variable and unpredictable, and also gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Being able to offer a high degree of TTR is therefore highly desirable for travellers and … Read more

Slot-based Motorway Driving for Connected and Automated Vehicles – No longer available

The Research Ireland funded ClearWay1 project is investigating new models of road management is which each vehicle is allocated a so-called ‘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). … Read more

ML-powered Parking Assistance System – No longer available

Parking in busy locations eg at large-scale events (such as concerts and mass-participation sporting events) or in shopping centres at busy times (eg during ‘Christmas shopping’) often results in traffic congestion in surrounding areas (see, for example, [1], for an extreme example!). This may arise due to vehicles searching for, entering, and leaving parking spaces … Read more

Swarm Intelligence for Travel Time Reliability – No longer available

Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, … Read more

Improving Road Transportation Resilience using LLMs and Agentic AI – No longer available

Mobility is the lifeblood of human connectedness and economic progress, and roads are a critical component of the transportation system for both people and goods. Unfortunately, roads are potentially vulnerable to medium- to long-term disruptions (ie, lasting hours to days) due to extreme weather, infrastructure failures, accidents, maintenance, and unexpected demand all resulting in high … Read more

[Taken] Explainability in Time Series Anomaly Detection

This project investigates methods for explaining anomalies detected in time series data. The aim is not only to identify when an anomaly occurs, but also to provide understandable explanations of why the observation or time period was considered anomalous. The project may explore feature importance, subsequence explanations, prototype examples, counterfactuals, or other explainable AI techniques … Read more

[Taken] Evaluation and Explanation of Guardrail Models in LLMs

This project evaluates guardrail or safety models designed to detect, prevent, or filter unsafe and undesirable outputs from large language models (LLMs). The focus is on developing a systematic evaluation framework and comparing the effectiveness of different guardrail approaches. This project would be ideal for BA ICS/MCS, BA CS (JH), BA CSLL and integrated masters. … Read more