The work aims to combine eye tracking, cognition and electroencephalogram (EEG) experiments to optimize the eHMI design to improve the interaction efficiency between autonomous vehicles (AVs) and pedestrians on uncontrolled road sections. Firstly, the cognitive performance of different interface information combinations was evaluated using AHP-TOPSIS and E-Prime. Eye movement experiments were used to analyze the influence of different installation positions of eHMI interfaces on visual attention. Finally, through EEG experiments, the influence of color stimulation on attention and decision-making efficiency was verified from the perspective of neural response. The upper part of the license plate and the bottom of the windshield were the optimal installation areas of the eHMI. The reaction time of the graphic and text combined interface was the shortest (1.08 s), which was superior to the single form. The yellow stimulation triggered the highest peak of P300 (11.746 μV), with the best cognitive performance. Moreover, the pedestrian-centered design could effectively reduce the cognitive load. The research constructs an eHMI design framework integrating visual guidance, cognitive optimization and neural mechanisms, providing theoretical support for the safe interaction and standardization of autonomous driving in an environment without signal control.
Key words
external human computer interaction interface (eHMI) /
electroencephalogram (EEG) /
road sections without signal control /
autonomous vehicle (AVs) /
eye tracking experiment /
AHP-TOPSIS
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