Affiliation:
1. College of Automotive Engineering Jilin University Changchun China
Abstract
AbstractManual operations remain crucial in critical human‐machine interactions due to limitations in automatic control algorithms and technologies. While ergonomic analysis and evaluation techniques for interactive interfaces are advancing, recent approaches emphasize integrating graphical interface experiences with intuitive controls. Conventional methods often lack precision or overlook the interaction effect of different influencing factors, leading to inadequate assessment of essential manual operations for intricate interfaces, such as multifunctional operation panels. To address these challenges, this study aimed to investigate the interaction effects of various factors on the manual operation performance of operators when using a multifunctional operation panel and aims to develop a more comprehensive and broadly applicable evaluation model for such panels. An experiment was designed to consider the type, size, layout of controls, and operational task type as the main factors affecting manual operation performance. Multivariate analysis of variance was used to identify significant interaction effects among the operation factors. The findings underscored the importance of these interactions in evaluating manual operation performance. Multivariate linear regression further examined the influence of these factors, enhancing the evaluation methodology. The study emphasizes the critical role of understanding interaction effects in assessing the manual operation performance of multifunctional operation panels, particularly in improving the design of the panel or operation tasks.