Peeking Ahead of the Field Study: Exploring VLM Personas as Support Tools for Embodied Studies in HCI

TL;DR

This paper introduces a rapid, low-cost method using Vision-Language Model personas to simulate human responses in embodied HCI studies, reducing reliance on costly field studies.

Contribution

It demonstrates that VLM personas can effectively mimic human responses in street-crossing tasks, offering a promising tool for preliminary and preparatory HCI research.

Findings

VLM personas closely mimic human crossing times

They lack behavioral variability and depth

Potential for formative studies and data augmentation

Abstract

Field studies are irreplaceable but costly, time-consuming, and error-prone, which need careful preparation. Inspired by rapid-prototyping in manufacturing, we propose a fast, low-cost evaluation method using Vision-Language Model (VLM) personas to simulate outcomes comparable to field results. While LLMs show human-like reasoning and language capabilities, autonomous vehicle (AV)-pedestrian interaction requires spatial awareness, emotional empathy, and behavioral generation. This raises our research question: To what extent can VLM personas mimic human responses in field studies? We conducted parallel studies: 1) one real-world study with 20 participants, and 2) one video-study using 20 VLM personas, both on a street-crossing task. We compared their responses and interviewed five HCI researchers on potential applications. Results show that VLM personas mimic human response patterns (e.g., average crossing times of 5.25 s vs. 5.07 s) lack the behavioral variability and depth. They show promise for formative studies, field study preparation, and human data augmentation.