Discovery Early Career Researcher Award - Grant ID: DE160101137
Funder
Australian Research Council
Funding Amount
$373,536.00
Summary
The whole is greater than its parts: Improving rail safety through teamwork. This project seeks to develop a train driving risk model that includes human factors, to enable rail organisations to better identify and mitigate safety risks. Train driving is a cognitively demanding task in which errors can quickly lead to catastrophic consequences. Signals passed at danger (SPADs) occur when a train goes past a red light. Despite significant investment in better signalling and communications infrast ....The whole is greater than its parts: Improving rail safety through teamwork. This project seeks to develop a train driving risk model that includes human factors, to enable rail organisations to better identify and mitigate safety risks. Train driving is a cognitively demanding task in which errors can quickly lead to catastrophic consequences. Signals passed at danger (SPADs) occur when a train goes past a red light. Despite significant investment in better signalling and communications infrastructure, SPAD rates remain unacceptably high and are projected to rise. SPAD risk is currently managed with a retrospective approach that fails to consider non-technical human factors such as time pressure, workload and team communications. By including non-technical dimensions, this project seeks to develop a comprehensive model to explain and prevent SPADs.Read moreRead less
Attention vs Perception: When is selection optimal, when relational? This project aims to investigate an important, newly discovered dissociation between early visual selection and perceptual decision-making. Contrary to current theories, attentional and perceptual processes are tuned to different stimulus attributes described in the relational vs. optimal account, which implies that current theories of attention do not describe early attention but later, decisional processes. This project will ....Attention vs Perception: When is selection optimal, when relational? This project aims to investigate an important, newly discovered dissociation between early visual selection and perceptual decision-making. Contrary to current theories, attentional and perceptual processes are tuned to different stimulus attributes described in the relational vs. optimal account, which implies that current theories of attention do not describe early attention but later, decisional processes. This project will provide an accurate description of these processes, which promises important theoretical breakthroughs. Work on this project will also significantly advance methods to detect and describe early attentional processes, by identifying error-prone methods of Psychophysics and Neuroscience studies, and proposing remedies.Read moreRead less