Capture of shrinking targets with realistic shrink patterns

Area of Science:

• Human-Computer Interaction
• Cognitive Psychology
• Human Factors Engineering

Background:

• Previous studies examined human capture of uniformly shrinking targets.
• The current research extends this by investigating targets with non-uniform shrinking patterns, mimicking real-world scenarios like aircraft recession.

Purpose of the Study:

• To analyze human performance in capturing targets that shrink at a non-uniform rate, specifically simulating an aircraft receding from an observer.
• To evaluate the applicability of Fitts' index of difficulty to predict capture time for these dynamic targets.
• To determine the probability of target capture under varying initial sizes and shrinking rates.

Main Methods:

• Experiment 1: Measured time to capture targets exhibiting an aircraft-like recession shrink pattern.
• Experiment 1: Calculated Fitts' index of difficulty at the moment of target capture.
• Experiment 2: Assessed target capture probability across different initial target sizes and constant shrink rates (time to halve initial size).

Main Results:

• Experiment 1: Capture time showed a strong correlation with Fitts' index of difficulty, supporting the balanced model.
• Experiment 2: The shrink time constant for 50% capture probability was influenced by initial target size.
• Experiment 2: Rapidly decreasing shrink rates had a diminishing impact on target capture success over time.

Conclusions:

• Fitts' index of difficulty effectively predicts capture time for targets with aircraft-recession-like shrinking patterns.
• Target capture probability is influenced by initial size and shrink rate, though the effect lessens as shrinking decelerates.
• The findings align with existing models and provide insights into human performance with dynamic targets.