Enhancing wayfinding in science & technology parks: insights from visual attention modeling

This study explores how the visual saliency of signs, landmarks, and paths influences predicted gaze behavior in a second-generation science and technology park. Using predictive visual attention modeling with 3M Visual Attention Software (VAS), we analyzed manipulated images of the CPQD campus from two mobility-related viewing perspectives – vehicular and pedestrian – under three visual saliency conditions. Results show that landmarks consistently attract the most attention, while enhanced signage and path visibility improve visual focus. The findings offer practical insights for designing more legible and wayfinding-friendly innovation campuses, supporting spatial orientation and fostering informal encounters in environments where such interaction is valued.