The Effectiveness of Sensor Visualizations and Graphic Augmentations for Detecting Vertical Obstacles

Abstract

Slow or failed detection of low-salience vertical obstacles and associated wires is one of today's leading causes of fatal helicopter accidents. The risk of collisions with such obstacles is likely to increase as advanced aerial mobility and broadening drone activity promises to increase the density of air traffic at low altitudes, while growing demand for electricity and communication will expand the number of vertical structures. The current see-and-avoid detection paradigm relies on pilots to spend much of their visual attention looking outside for obstacles. This method is inadequate in low-visibility conditions, cluttered environments, and given the need for pilots to engage in multiple competing visual tasks. With the expected growing number of hazards and an increased traffic volume, the current approach to collision avoidance will become even less tenable. A human-in-the-loop helicopter simulator study was conducted to assess the effectiveness of sensor visualizations (image intensification or thermal imaging) and graphic augmentations (a bounding box around a tower and a circle surrounding the base of the tower) for supporting fast and reliable detection of vertical structures. Graphic augmentations resulted in faster tower detection time when ambient visibility and illumination were reduced close to the limit for visual flight. Bounding boxes around towers were detected first in all conditions but tended to mask the obstacle they were meant to highlight. Sensor visualization affected tower detection time only at night, where night vision goggles were more effective than the infrared thermal sensor.