Understanding the Uncertainty in 1D Unidirectional Moving Target Selection
summary
Paper presents a ternary-Gaussian model for endpoint distributions in 1D unidirectional moving-target pointing and fits mu and sigma as functions of target width W and velocity V (initial distance A shows no effect). Three experiments with 12 subjects on a desktop mouse produce R^2 ≈ 0.95 and 0.94 for mu and sigma. Two extensions predict error rates (mean absolute error MAE 2.7%) and power a Bayes-based “based pointer” that yields 33% higher accuracy in a fast-tile game.
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