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
Difficulties of monitoring for rare events. This project aims to identify cognitive and neural processes involved in sustaining attention to moving displays under monitoring conditions.People are poor at monitoring for rare events: they tend to miss infrequent targets. This is a problem in automated systems for transport, rail and air traffic control. If a computer error occurs, the operator needs to intervene quickly. This project will develop a tool for studying monitoring and determine patter ....Difficulties of monitoring for rare events. This project aims to identify cognitive and neural processes involved in sustaining attention to moving displays under monitoring conditions.People are poor at monitoring for rare events: they tend to miss infrequent targets. This is a problem in automated systems for transport, rail and air traffic control. If a computer error occurs, the operator needs to intervene quickly. This project will develop a tool for studying monitoring and determine patterns of brain activity that predict a lapse of attention. The results should contribute to theories of vigilance and improve performance in real-world monitoring situations.Read moreRead less
Understanding and improving sustained attention under vigilance conditions. This project aims to address a major global challenge caused by technological advances: human operators have to monitor computer-control (e.g., in autonomous vehicles, rail and airtraffic control) but sustaining attention is very difficult under these conditions. Developing innovative behavioural and neural methods, this internationally collaborative project bridges basic and applied science to understand lapses of atten ....Understanding and improving sustained attention under vigilance conditions. This project aims to address a major global challenge caused by technological advances: human operators have to monitor computer-control (e.g., in autonomous vehicles, rail and airtraffic control) but sustaining attention is very difficult under these conditions. Developing innovative behavioural and neural methods, this internationally collaborative project bridges basic and applied science to understand lapses of attention under monitoring conditions. It creates a novel intervention, based on brain activity patterns, to improve performance. Outcomes will increase our neural understanding of attention and lay a foundation for a novel system to detect lapses of attention in high-risk environments, preventing errors before they occur.Read moreRead less