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Modeling and evaluation of attention allocation in an intelligent tractor head‐up display interface
Author(s) -
Pei Yeqing,
Song Zhenghe,
Jin Xiaoping,
Yang Zihan,
Wen Changkai,
Shao Xuedong
Publication year - 2020
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20834
Subject(s) - interface (matter) , matching (statistics) , computer science , criticality , information design , human–computer interaction , tractor , index (typography) , user interface , engineering , automotive engineering , statistics , physics , mathematics , bubble , maximum bubble pressure method , parallel computing , world wide web , nuclear physics , operating system
Tractors are becoming increasingly intelligent due to developments in electronics and information technology. Amid the large quantities of information in the driving cab, drivers may lack the attention resources demanded when operating, thus leading to neglect of important information. Therefore, the interface design stage must consider the human factors of the design. Designers must study and optimize the factors influencing attention allocation related to the interface design. In this study, the criticality of information is first proposed for quantifying the importance of various information in the display interface. Subsequently, the factors affecting attention allocation are investigated through experimental methods. Finally, a matching index is proposed to evaluate the interface design with respect to attention allocation. This enables the optimization of the interface design by matching attention allocation and criticality of the information. The matching index can thus serve as a design specification for tractor head‐up display interfaces.