A human-centric eXplainable Automated Vehicle. The aim is to create a computational model to address the inability of Automated Vehicles (AV), powered by Artificial intelligence, to self explain their behaviours. This project applies novel multidisciplinary methodologies in a real-world self-driving setting to formalise the essence of driving explanations. It explores the when, why and how a driver is seeking an explanation and what type of automated explanation is truly human-interpretable. Exp ....A human-centric eXplainable Automated Vehicle. The aim is to create a computational model to address the inability of Automated Vehicles (AV), powered by Artificial intelligence, to self explain their behaviours. This project applies novel multidisciplinary methodologies in a real-world self-driving setting to formalise the essence of driving explanations. It explores the when, why and how a driver is seeking an explanation and what type of automated explanation is truly human-interpretable. Expected outcomes include the discovery of an acceptable, transparent and ethical explanation system that helps humans to understand the AVs decision making. This field will continue to rise in prominence and produce much-needed work to improve the widespread adoption of AVs.Read moreRead less
Understanding evolution in natural systems using robotic models. This project aims to build biologically-inspired robotic and computational systems, and then modify these in ways which are either not possible, or have not yet occurred in natural systems. A comparison of these two systems will then allow a quantitative understanding of how well optimised biological structures are and where the limitations to optimisation lie. Expected outcomes include advancing the understanding of evolutionary p ....Understanding evolution in natural systems using robotic models. This project aims to build biologically-inspired robotic and computational systems, and then modify these in ways which are either not possible, or have not yet occurred in natural systems. A comparison of these two systems will then allow a quantitative understanding of how well optimised biological structures are and where the limitations to optimisation lie. Expected outcomes include advancing the understanding of evolutionary processes, and will provide significant benefits, such as aiding the manufacture of efficient autonomous robots.Read moreRead less