The anatomy of a fatigue-related motor vehicle crash or near-crash. The anatomy of a fatigue-related motor vehicle crash or near-crash. This project aims to investigate the time course of multiple physiological and behavioural signals that lead to fall-asleep (on-road) driving events, to inform the next generation of driver state monitoring technologies. Falling asleep at the wheel remains a major cause of road crashes worldwide. Although technologies to monitor driver sleepiness are integral to ....The anatomy of a fatigue-related motor vehicle crash or near-crash. The anatomy of a fatigue-related motor vehicle crash or near-crash. This project aims to investigate the time course of multiple physiological and behavioural signals that lead to fall-asleep (on-road) driving events, to inform the next generation of driver state monitoring technologies. Falling asleep at the wheel remains a major cause of road crashes worldwide. Although technologies to monitor driver sleepiness are integral to the rapidly evolving autonomous vehicle industry, such technologies are limited because they measure the end-state of falling asleep, rather than the physiological and behavioural precursors, thus providing little opportunity for intervention. This project is expected to lead to new driver monitoring systems that reduce fall-asleep crashes.Read moreRead less
Pattern recognition in animals and machines: using machine learning to reveal cues central to the identification of individuals. The power to recognise individuals of a species requires significant image and pattern discrimination abilities. Yet, individual recognition has been found in a huge range of species, from humans to invertebrates demonstrating its importance for social interactions. The project will investigate this ability in lower vertebrates (fish, with no visual cortex), so as to u ....Pattern recognition in animals and machines: using machine learning to reveal cues central to the identification of individuals. The power to recognise individuals of a species requires significant image and pattern discrimination abilities. Yet, individual recognition has been found in a huge range of species, from humans to invertebrates demonstrating its importance for social interactions. The project will investigate this ability in lower vertebrates (fish, with no visual cortex), so as to understand the underlying mechanisms of pattern discrimination. The project will also test how robust this ability is during changes in water quality (elevated carbon dioxide levels and increased turbidity). The outcomes will further our knowledge base in lower vertebrate vision and evolution, and also have implications for human vision, image analysis, and artificial vision.Read moreRead less