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

TL;DR

This study explores how dynamic light features on automated vehicles affect pedestrian crossing behavior, finding that animation speed is the most influential factor.

Contribution

The study introduces a factorial design framework to isolate the effects of animation pattern, speed, and light-emitting area on pedestrian behavior.

Findings

Faster animation speed significantly deters pedestrians from crossing by signaling non-yielding intent.

Dynamic lighting features have a stronger influence on pedestrian decisions when the vehicle-pedestrian distance is longer.

Animation pattern and light-emitting area mainly affect visual attention rather than decision-making.

Abstract

What are the main findings?
The research contributes a factorial design framework that systematically isolates the specific effects of animation pattern, speed, and light-emitting area. It identifies animation speed as the most critical dynamic feature of light-based eHMIs, demonstrating that faster light loops significantly deter pedestrians from crossing by signaling non-yielding intent.

The research contributes a factorial design framework that systematically isolates the specific effects of animation pattern, speed, and light-emitting area. It identifies animation speed as the most critical dynamic feature of light-based eHMIs, demonstrating that faster light loops significantly deter pedestrians from crossing by signaling non-yielding intent.

What is the implication of the main finding?
The influence of dynamic cues is highly context-dependent, with lighting features significantly affecting decisions primarily during constant vehicle motion or longer time gaps, whereas vehicle kinematics dominate during deceleration. The AV should dynamically adapt lighting characteristics to optimize pedestrian safety in mixed traffic.

The influence of dynamic cues is highly context-dependent, with lighting features significantly affecting decisions primarily during constant vehicle motion or longer time gaps, whereas vehicle kinematics dominate during deceleration. The AV should dynamically adapt lighting characteristics to optimize pedestrian safety in mixed traffic.

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.

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