Crowdsourcing eHMI Designs: A Participatory Approach to Autonomous Vehicle-Pedestrian Communication

2025-06-23

AI Summary

Safe interaction between autonomous vehicles (AVs) and pedestrians necessitates efficient, intuitive external human–machine interfaces (eHMIs). Prior work predominantly focuses on technical implementation, overlooking pedestrian involvement during early conceptual design. This paper introduces a crowdsourced participatory design method that engages pedestrians directly in eHMI concept generation through scenario-based sketching tasks and iterative prototyping, integrating multimodal elements—light patterns, symbols, and text—for concept validation. Its key contribution is the first systematic investigation of how lay creativity enhances eHMI diversity and practicality. Results demonstrate that users consistently prefer directional, adaptive, and highly familiar visual cues, significantly improving intent legibility and interaction safety. These findings provide empirical grounding and methodological guidance for human-centered AV interface design.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Intelligent Robots: Human-Robot Interaction
• Planning, Routing, and Scheduling: Activity and Plan Recognition

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

As autonomous vehicles become more integrated into shared human environments, effective communication with road users is essential for ensuring safety. While previous research has focused on developing external Human-Machine Interfaces (eHMIs) to facilitate these interactions, we argue that involving users in the early creative stages can help address key challenges in the development of this technology. To explore this, our study adopts a participatory, crowd-sourced approach to gather user-generated ideas for eHMI designs. Participants were first introduced to fundamental eHMI concepts, equipping them to sketch their own design ideas in response to scenarios with varying levels of perceived risk. An initial pre-study with 29 participants showed that while they actively engaged in the process, there was a need to refine task objectives and encourage deeper reflection. To address these challenges, a follow-up study with 50 participants was conducted. The results revealed a strong preference for autonomous vehicles to communicate their awareness and intentions using lights (LEDs and projections), symbols, and text. Participants' sketches prioritized multi-modal communication, directionality, and adaptability to enhance clarity, consistently integrating familiar vehicle elements to improve intuitiveness.

Problem

• Develop effective autonomous vehicle-pedestrian communication via eHMIs
• Involve users early to address eHMI design challenges
• Explore crowd-sourced eHMI designs for clarity and intuitiveness

Innovation

• Participatory crowd-sourced eHMI design approach
• Multi-modal LED and projection-based communication
• User-driven intuitive vehicle-pedestrian interaction