Aditya Iqbal Bagaskara
Topic
Human-Centered Cut-to-Length Forestry Operations, Training, and Maintenance - Eye-Tracking Analysis of Cognitive Load, Situational Awareness, and Decision-Making
Currently working on:
Gaze-based metrics measurement in VR in the forestry domain
My research explores how human factors can guide the development of future Cut-to-Length (CTL) forestry work machines. It investigates visual attention and cognitive processing during sustainable harvesting, especially in thinning operations, where decision-making is complex. High-fidelity simulators create realistic work scenarios to observe operator behavior, while eye-tracking enables real-time and temporal analysis of cognitive processes as well as usability testing.
The study assesses emerging machine interfaces and assistance technologies using metrics such as gaze distribution, Areas-of-Interest, and cognitive workload estimates from pupillometric data. By applying eye-tracking, the research aims to clarify how operators develop skills, maintain situational awareness, and adapt strategies. These topics are not yet as thoroughly addressed in forestry as in fields like aviation or automotive engineering. The work supports designing human-centered machines and adaptive training that meets the cognitive needs of both current and future generations of operators. The findings seek to improve learning transfer from simulators, support operator well-being, and encourage sustainable forestry practices. In addition, the project will examine how large language model-based interactive support might enhance knowledge retention and operational efficiency in the field.