A Study for Evaluations of Automobile Digital Dashboard Layouts Based on Cognition Electroencephalogram

Electroencephalogram (EEG) performed an increasingly important role in user experience research. The study applied P300, one of the main components of event-related potentials (ERPs), into the evaluation of digital dashboard layouts. The amplitude and latency of P300 were used to objectively quantify the cognitive differences of the subjects. By comparing the results with that of a subjective system usability scale, the feasibility of this method was verified. Through statistical analysis, the layout most suitable for the subjects' cognitive characteristics was found. By the amplitude and latency of P300, a support vector machine (SVM) model was established to explore the relationship between P300 and dashboard layout. The results showed a good prediction accuracy of 80%. Analysis of variance (ANOVA) indicated significant differences among the four groups of P300 induced by different layout types (p < 0.01). And Type A was the most reasonable one from the perspective of attention allocation. Among the nine schemes of Type A, the one in flat design style with a warm tone presented the highest system usability (m = 95.833). The conclusions provided a theoretical basis for the layout evaluation of digital dashboards, and a reference for the design of human-vehicle interface, especially in the era of car-sharing.