abstract

The integration of Artificial Intelligence (AI) with transport Digital Twins (DTs) is transforming intelligent transportation systems by enabling real-time monitoring, predictive analytics, traffic optimization, infrastructure management, and autonomous decision support. However, the increasing autonomy and complexity of AI-enabled transport Digital Twins introduce significant challenges related to transparency, accountability, cybersecurity, privacy, data quality, algorithmic bias, human oversight, and operational safety. Existing Digital Twin architectures primarily emphasize technical interoperability and real-time synchronization, while conventional AI governance frameworks often provide limited guidance for the continuous and context-dependent operation of transport Digital Twins. This paper proposes a Socio-Technical Governance Framework for Trustworthy AI-Enabled Transport Digital Twins (STG-TDT). The framework integrates technical controls, organizational governance, human oversight, risk management, ethical assurance, cybersecurity, privacy protection, and continuous performance monitoring across the complete Digital Twin lifecycle. The proposed framework consists of six interconnected layers: data and sensing governance, Digital Twin integrity, AI governance, cybersecurity and privacy, human and organizational oversight, and continuous assurance. A multidimensional Trustworthiness Assurance Score is further proposed to evaluate reliability, safety, security, transparency, explain ability, privacy, fairness, accountability, and resilience. The framework is aligned conceptually with established AI risk-management and AI-management approaches, including the NIST AI Risk Management Framework and ISO/IEC 42001. The paper demonstrates how socio-technical governance can provide a systematic foundation for deploying trustworthy AI-enabled transport Digital Twins while maintaining operational safety, regulatory accountability, and public confidence.