Work

A Study on the Effects of the Dynamic Features of Light-Based eHMI on Pedestrians’ Crossing Behavior

Year: 2026

Type: article

Abstract: While light-based external human-machine interfaces (eHMIs) on automated vehicles (AVs) are increasingly studied to mediate pedestrian-vehicle conflicts, gaps persist in understanding how specific dynamic features of the AV's headlights influence pedestrians' prediction of its yielding intention and their crossing behavior. This study systematically investigates the effects of dynamic elements of vehicle lighting-including animation patterns, animation speed, and light-emitting area-on pedestrians' objective and subjective evaluations. A factorial design framework was employed, where participants viewed video simulations of an approaching AV displaying headlight designs combining multiple dynamic features. For different vehicle motion states, the vehicle-pedestrian distance was integrated as a variable to examine its interaction effect with lighting features. Objective measures of cueing effects were complemented by subjective ratings and user preference study via questionnaires. Results showed that there were more crossing behaviors of the pedestrian when presenting higher animation speed of dynamic light eHMIs. Animation pattern and light-emitting area does not play an important role in pedestrian decision-making, but proper design of these two features can evoke higher visual attention. When the vehicle-pedestrian distance is longer, the dynamic features of lighting will more affect people's willingness to cross. The effects of light eHMIs seemed more significant for the AV travelling in constant speed. Our findings advance preliminary suggestions for selecting light-based eHMIs in the appropriate scenarios and can contribute actionable insights for designing intuitive, human-centric AV-pedestrian negotiation strategies.

Source: Sensors

DOI: 10.3390/s26041247

Authors: Yiqi Xiao, Zhiming Liu, Tini Ma, Yingjie Huang

Institutions: University of Shanghai for Science and Technology, Royal College of Art

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,137