Towards Adaptive External Communication in Autonomous Vehicles: A Conceptual Design Framework

2025-08-17

AI Summary

Current external human–machine interfaces (eHMIs) for autonomous vehicles predominantly adopt static, passive designs, limiting adaptability to diverse road users and dynamic traffic scenarios—thereby compromising scalability and inclusivity. To address this, we propose the first conceptual design framework for adaptive eHMIs, grounded in cyber-physical systems (CPS) principles and structured as a three-layer “perception–decision–interaction” architecture. This enables real-time sensing of road user states and environmental changes, coupled with dynamic adjustment of communication strategies. The framework integrates theory-driven abstract modeling with iterative expert workshops to systematically support eHMI design, analysis, and evaluation. Our work fills a critical methodological gap in adaptive eHMI research, advancing human–vehicle interaction from static to dynamic paradigms, and establishing a structured foundation for addressing associated ethical and technical challenges.

Technology Category

• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Humans and AI: Intelligent User Interfaces
• Intelligent Robots: Human-Robot Interaction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

External Human-Machine Interfaces (eHMIs) are key to facilitating interaction between autonomous vehicles and external road actors, yet most remain reactive and do not account for scalability and inclusivity. This paper introduces a conceptual design framework for adaptive eHMIs-interfaces that dynamically adjust communication as road actors vary and context shifts. Using the cyber-physical system as a structuring lens, the framework comprises three layers: Input (what the system detects), Processing (how the system decides), and Output (how the system communicates). Developed through theory-led abstraction and expert discussion, the framework helps researchers and designers think systematically about adaptive eHMIs and provides a structured tool to design, analyse, and assess adaptive communication strategies. We show how such systems may resolve longstanding limitations in eHMI research while raising new ethical and technical considerations.

Problem

• Dynamic adjustment of eHMIs for varying road actors
• Scalability and inclusivity challenges in current eHMIs
• Ethical and technical considerations in adaptive communication

Innovation

• Dynamic eHMIs adjust communication for varying road actors
• Cyber-physical system with Input, Processing, Output layers
• Framework aids systematic design of adaptive communication strategies