Comparison Study of Visual Search on 6 Different Types of Icons

Liang, Yongqiang; Wang, Wei; Qu, Jinping; Yang, Jie

doi:10.1088/1742-6596/1060/1/012031

Cited by 4 publications

(5 citation statements)

References 9 publications

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“…Naturally, questions still remain around how the information should be graphically adapted on a display. Visual prominence is a measure of how easily a user can access the information on an HMI and is well established with studies covering a wide range of aspects in understanding how visual prominence can be achieved, particularly in the design of HMIs [30]- [32]. However, for this study, understanding how visual prominence should change was out of the scope.…”

Section: A Adaptive Interfaces For Partially Automated Vehiclesmentioning

confidence: 99%

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Using Glance Behaviour to Inform the Design of Adaptive HMI for Partially Automated Vehicles

Ulahannan

Thompson

Jennings

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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Section: A Adaptive Interfaces For Partially Automated Vehiclesmentioning

confidence: 99%

“…In total, 27 participants were recruited for this study (14 Male; 13 Female). Participants age was reported in age brackets as follows: 10 (18-24), 13 (25)(26)(27)(28)(29)(30)(31)(32)(33)(34), 1 (41-50), 3 (71-80). The mean age of participants was 32.3 years, with a standard deviation of 16.6.…”

Section: B Participantsmentioning

confidence: 99%

Using Glance Behaviour to Inform the Design of Adaptive HMI for Partially Automated Vehicles

Ulahannan

Thompson

Jennings

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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“…At the end of the experiment, the eye movement data for each participant was stored and labelled. Based on the suggestions of previous studies (e.g., Brunyé & Gardony, 2017;Liang et al, 2018;Pang et al, 2020), the eye movement parameters of average pupil diameter, fixation number, fixation duration, saccade amplitude, and saccade velocity peak were used in the analysis. At the end of the experiment, we asked participants to identify their preferred design elements from each trial.…”

Section: Methodsmentioning

confidence: 99%

Emotional Intelligence and Individual Visual Preferences: A Predictive Machine Learning Approach

Al-Samarraie

Sarsam

Lonsdale

et al. 2022

International Journal of Human–Computer Interaction

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Differences in individuals' psychological and cognitive characteristics have been always found to play a significant role in influencing our behaviour and preferences. While a number of studies have identified the impact of these characteristics on individuals' visual design preferences, understanding how emotional intelligence (EI) would influence this process is yet to be explored. This study investigated the link between individuals' EI dimensions (e.g., emotionality, self-control, sociability, and well-being) and their eye movement behaviour in an attempt to build a prediction model for visual design preferences. A total of 136 participants took part in this study. The feature selection and prediction of EI and eye movement data were performed using the genetic search method in conjunction with the bagging method. The results showed that participants high in self-control and emotionality exhibited different eye movement behaviours when performing five visual selection tasks. The prediction results (93.87% accuracy) revealed that specific eye parameters can predict the link between certain EI dimensions and 2 preferences for visual design. This study adds new insights into Human-Computer Interaction, EI and rational choice theories. The findings also encourage researchers and designers to consider EI in the development of intelligent and adaptive systems.

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“…First, graphical symbols are means of communication: they are used to convey complex concepts within a lesser space than a full written sentence does (Gittins 1986;Womack 2005). They can be easier to remember than written words (Stenberg 2006), faster to categorise (Job et al 1992), easier to find during a visual search (Ojanpää 2006;Liang et al 2018), easier to read from a fixed distance (Rettenmaier et al 2020), and are also easier for individuals living with dyslexic problems (Kim and Wiseheart 2017). Comprehensible symbols (aka 'icons' if presented on a computer screen) can help users retain information when learning how to use a system as compared to a text-only interface (Huang et al 2019).…”

Section: The Importance Of Symbolsmentioning

confidence: 99%

User-centred design evaluation of symbols for adaptive cruise control (ACC) and lane-keeping assistance (LKA)

2021

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Advanced driving assistance systems (ADAS) are now numerous, each relieving drivers of their responsibility for the control of different aspects of the driving task. Notably, adaptive cruise control (ACC) for longitudinal control, or lane departure prevention (LDP) and lane centring control (LCC) for lateral control, two variations of the lane-keeping assistance (LKA) system. Drivers must familiarise themselves with various symbols to correctly identify and activate the system they wish to be using and the existing standard graphical symbols for ACC and LKA are often replaced by manufacturers in favour of their own symbols. With a user-centred approach in mind, we previously conducted a focus group where drivers were invited to design their own symbols and discuss those symbols currently in-use. In the present research, we administered an online survey and analysed the responses from 328 drivers regarding different levels of knowledge about ADAS, to evaluate the usability of a selection of these symbols. Our results indicate that the standard ACC symbol would not be the most suitable of the four symbols tested, whereas, the standard LKA/LDP symbol was greatly confused with any of the four LCC symbols we tested, especially if hands were present on the symbol. Finally, drivers without prior knowledge of ADAS had more difficulties interpreting those symbols in general. Considerations for the development and evaluation of graphical symbols are discussed.

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Comparison Study of Visual Search on 6 Different Types of Icons

Cited by 4 publications

References 9 publications

Using Glance Behaviour to Inform the Design of Adaptive HMI for Partially Automated Vehicles

Using Glance Behaviour to Inform the Design of Adaptive HMI for Partially Automated Vehicles

Emotional Intelligence and Individual Visual Preferences: A Predictive Machine Learning Approach

User-centred design evaluation of symbols for adaptive cruise control (ACC) and lane-keeping assistance (LKA)

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