Improving performance in high risk environments using guided distraction and iconic cues. This project tests a novel strategy to assist operators in high-risk automated environments, in order to maintain their performance in low workload situations. Using guided distraction, this project will be able to show improvements in attention to critical tasks and in overall system performance, thereby reducing the potential for error.
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