Towards Developing Socially Compliant Automated Vehicles: State of the Art, Experts Expectations, and A Conceptual Framework

2025-01-10

AI Summary

Existing research on socially compliant autonomous vehicles (SCAVs) suffers from conceptual ambiguity and a lack of integrative frameworks, hindering progress in safety, efficiency, and public acceptance within mixed-traffic environments. Method: This study conducts the first systematic scoping review of SCAV literature and triangulates findings through expert interviews across multiple countries and a large-scale online survey involving policymakers, engineers, and the general public. Contribution/Results: We propose and empirically validate the first comprehensive conceptual framework for SCAV development. The framework rigorously defines three core dimensions of social compliance—normative understanding, behavior adaptation, and explainable interaction—and articulates a socio-technical co-development pathway bridging algorithmic design and institutional governance. It further identifies critical technical, regulatory, and societal gaps. This work establishes a foundational theoretical basis and actionable guidance for SCAV standardization, algorithmic implementation, and cross-sectoral policy coordination.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Learning Human Values and Preferences

Application Category

• Responsible Web: Algorithmic accountability and transparency on the web
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

Automated Vehicles (AVs) hold promise for revolutionizing transportation by improving road safety, traffic efficiency, and overall mobility. Despite the steady advancement in high-level AVs in recent years, the transition to full automation entails a period of mixed traffic, where AVs of varying automation levels coexist with human-driven vehicles (HDVs). Making AVs socially compliant and understood by human drivers is expected to improve the safety and efficiency of mixed traffic. Thus, ensuring AVs compatibility with HDVs and social acceptance is crucial for their successful and seamless integration into mixed traffic. However, research in this critical area of developing Socially Compliant AVs (SCAVs) remains sparse. This study carries out the first comprehensive scoping review to assess the current state of the art in developing SCAVs, identifying key concepts, methodological approaches, and research gaps. An expert interview was also conducted to identify critical research gaps and expectations towards SCAVs. Based on the scoping review and expert interview input, a conceptual framework is proposed for the development of SCAVs. The conceptual framework is evaluated using an online survey targeting researchers, technicians, policymakers, and other relevant professionals worldwide. The survey results provide valuable validation and insights, affirming the significance of the proposed conceptual framework in tackling the challenges of integrating AVs into mixed-traffic environments. Additionally, future research perspectives and suggestions are discussed, contributing to the research and development agenda of SCAVs.

Problem

• Autonomous Vehicles
• Mixed Traffic Environment
• Social Norms Compliance

Innovation

• Autonomous Vehicles
• Social Compliance
• Theoretical Framework