•  
  •  
 

DEPTH AND VISUAL DISCERNMENT OF DRONES BASED ON DIFFERING COLOR PATTERNS

Abstract

Effective depth perception and visual discernment are critical for safe and efficient drone operation, yet pilots often struggle to accurately judge a drone’s position and movement relative to its surroundings. Prior research has shown that color patterns effectively improve visibility and depth judgments. This study evaluated whether color patterns enhance drone perceptibility. Specifically, the research examined whether a striped red and black drone increases depth accuracy compared to solid red and solid black drones. Using a modified three-rod test, 31 participants estimated the drone's center position while it moved at a constant speed between two fixed target points. Participants provided an audio cue when they perceived the drone to be in line with target points, with errors in perception measured as deviations from the actual target point. A within-subjects design was used, with participants assigned to each of three drone color conditions in a counterbalanced order. These data were analyzed using repeated measures ANOVA to determine if drone color pattern significantly affects perceptual accuracy. The results indicated no significant differences in depth-perception error across the three conditions: striped (M = 4.99 feet, SD = 2.55), red (M = 4.64 feet, SD = 2.00), and black (M = 4.60 feet, SD = 2.56), F(2, 60) = 0.50, p = .610, η²p = 0.02. Although there was no significant difference between conditions, these findings could inform training programs for drone operators, emphasizing visual cues or supplementary aids when operating in complex or low-contrast environments. Future studies could explore larger sample sizes, additional color pattern combinations, or varied operational contexts to inform drone design improvements, enhance safety, and reduce reliance on secondary operators for visual tracking. By optimizing visibility through color and pattern adjustments, this research aims to enhance perceptual efficiency in both recreational and commercial drone applications.

This document is currently not available here.

Share

COinS