Revisiting the steering law : curvature, complexity, and the path to a new predictive model
department or school: Applied Science, Faculty of
department or school: Electrical and Computer Engineering, Department of
data provider: DSpace
degree campus: UBCV
creator: Chen, Jennie Jia Yi
issued: 2025-04-28T13:23:37Z
issued: 2025
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: The Steering Law has long been a fundamental model in predicting movement time for tasks involving navigating through constrained paths such as menu selections and virtual environments. The base model and past research on its extensions primarily focused on simple geometries such as straight lines and simple or compound circular arcs. While useful in simple user interfaces, they do not capture the complexities of real-world tasks where curvatures can vary arbitrarily. This limits the generalizability of the model to envi- ronments where users interact with more irregular paths. This thesis revisits and extends the Steering Law by introducing the total curvature pa- rameter K into the equation to account for the overall curviness characteristic of a path. Drawing on an information-theoretic interpretation of human motor behavior, we propose an extension to the Steering Law where K contributes as logarithmic noise in the movement time prediction equation: MT= a + b L + c·log2(K + 1) + d L·K To validate this extension, we conducted a mouse-steering experiment (N= 20) on fixed- width paths characterized by 3 levels of length and 3 levels of curviness. Width was held constant to isolate curvature effects. Results demonstrate that the introduction of K significantly improves model fitness for movement time prediction over traditional models. We further identify a significant in- teraction between length and curviness, which led to improved performance when incor- porated into the model. We also show that previous models developed for circular arc trajectories, when reformulated using the K parameter, generalize well to our experimental data. These findings support the hypothesis that curvature introduces a form of perceptual or motor noise that increases task difficulty in human steering behavior. Beyond empirical validation, this thesis presents a detailed account of the theoretical framing and experimental reasoning through a series of pilot studies and design explo- ra…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/90833
note: Revisiting the Steering Law: Curvature, Complexity, andthe Path to a New Predictive ModelbyJennie Jia Yi ChenB.Eng., McGill University, 2021A THESIS SUBMITTED IN PARTIAL FULFILLMENTOF THE REQUIREMENTS FOR THE DEGREE OFMaster of Applied ScienceinTHE FACULTY OF GRADUATE AND POSTDOCTORALSTUDIES(Electrical and Computer Engineering)The University of British Columbia(Vancouver)April 2025© Jennie Jia Yi Chen, 2025The following individuals certify that they have read, and recommend to the Faculty ofGraduate and Postdoctoral Studies for acceptance, the thesis entitled:Revisiting the Steering Law: Curvature, Complexity, and the Path to a New Predic-tive Modelsubmitted by Jennie Jia Yi Chen in partial fulfillment of the requirements for the degreeof Master of Applied Science in Electrical and Computer Engineering.Examining Committee:Sidney S. Fels, Professor, Electrical and Computer Engineering, UBCSupervisorSeptimiu E. Salcudean, Professor, Electrical and Computer Engineering, UBCSupervisory Committee MemberDongwook Yoon, Professor, Computer Science, UBCSupervisory Committee MemberiiAbstractThe Steering Law has long been a fundamental model in predicting movement time fortasks involving navigating through constrained paths such as menu selections and virtualenvironments. The base model and past research on its extensions primarily focused onsimple geometries such as straight lines and simple or compound circular arcs. Whileuseful in simple user interfaces, they do not capture the complexities of real-world taskswhere curvatures can vary arbitrarily. This limits the generalizability of the model to envi-ronments where users interact with more irregular paths.This thesis revisits and extends the Steering Law by introducing the total curvature pa-rameter K into the equation to account for the overall curviness characteristic of a path.Drawing on an information-theoretic interpretation of human motor behavior, we proposean extension to the Steering Law where K contributes as loga…
has type: Thesis/Dissertation
date issued: 2025-05
is shown at: 10.14288/1.0448609
language: eng
degree discipline: Electrical and Computer Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Fels, Sidney
type: Text
identifier URI: http://hdl.handle.net/2429/90833