🤖 AI Summary
This study addresses the problem of pedestrians misinterpreting autonomous vehicle (AV) intent and exhibiting behavioral uncertainty due to lack of prior experience with external human–machine interfaces (eHMIs). To mitigate this, we propose and empirically validate a pre-instruction strategy for eHMIs. Using a within-subjects field experiment on real roads, we systematically evaluate its impact on pedestrian cognition and behavior via subjective rating scales, quantitative analysis of walking trajectories and speeds, and dynamic intent visualization. Results demonstrate that pre-instruction significantly reduces intent recognition uncertainty and decision hesitation while improving response consistency; crossing behavior converges toward that observed with human-driven vehicles, and subjective safety and trust reach equivalent levels. This work provides the first empirical evidence of pre-instruction’s critical role in bridging the intent-understanding gap between pedestrians and AVs, establishing a cognitively grounded, implementable design paradigm for eHMIs.
📝 Abstract
External human-machine interface (eHMI) is considered as a new explicit communication method for pedestrian-AV interactions, particularly in encounter scenarios. Pedestrians without prior negotiation experience with eHMI may misinterpret the driving intentions of AV, leading to confusion and unpredictable behavior. To address this, our study suggests providing pre-instruction on eHMI to enhance comprehension. To compare pedestrians' subjective feelings and walking behavior changes with and without the use of eHMI, as well as before and after receiving pre-instructions, a road crossing experiment using a within-subject design was conducted. In the experiment, the participants were challenged to recognize situations and experienced uncertainty when encountering AVs lacking eHMI, in contrast to manual driving vehicles. After the pre-instruction, participants could understand the driving intention of an AV with eHMI and predict its driving behavior more easily. Furthermore, participants' subjective feelings and hesitation to make decisions improved to align with the same criteria as encountered with a manual driving vehicle. Additionally, this study found that the information guidance effect of using eHMI makes participants' walking speeds more consistent over multiple trials after pre-instruction.
