Steering through a Dynamically Varying Path

Existing research in steering often focuses on static paths. However, in real-world systems, such as interfaces for lasso and video games, there are no guarantees that the paths will maintain their initial width and distance during steering. We thus explore steering movements on a dynamically varying path, widening or narrowing. To this end, we empirically studied the impact of several task parameters - including changed path width, path occupancy duration, and position - on steering through the dynamically varying path. As a result, we found different steering movements and performance to the previous steering task in the static path in terms of movement time and error rate. Additionally, we tested various previous extended models and found poor fitness results (mean $R^2_{adjusted}=0.53$) compared to the presented models (mean $R^2_{adjusted}=0.92$). We believe our model will assist GUI and game designers in evaluating their applications.