Automated Vehicle Traffic: A Review of Operational Challenges, Infrastructure Requirements and Research Directions

TL;DR

This paper reviews the challenges and requirements for deploying automated vehicle systems, focusing on operational domains, infrastructure, and future research directions.

Contribution

The paper provides a comprehensive review of operational design domains and infrastructure requirements for automated mobility, identifying key research gaps and enablers.

Findings

Fragmented operational design domains and limited infrastructure readiness hinder large-scale CCAM deployment.

Digital twins and data-driven simulations are essential for adaptive and resilient automated mobility operations.

Future research should focus on infrastructure readiness indicators and human-in-the-loop systems for mixed traffic safety.

Abstract

The evolution of Connected, Cooperative, and Automated Mobility (CCAM) systems represents a shift in transportation, potentially achieving benefits in efficiency, sustainability, and safety. Large-scale deployments of CCAM systems are, however, still constrained by fragmented Operational Design Domain (ODD) and limited infrastructure readiness. This paper reviews the state of the art regarding operational, infrastructural, and technological enablers for predictive and extendable ODDs. First, a literature review of existing definitions and ongoing standardization work is presented, focusing on gaps in the formalization and validation of ODD boundaries. Second, the influence of physical infrastructure elements on vehicle performance and safety is analyzed. Third, technological and organizational enablers, which include digital twins, data-driven simulation models, and governance frameworks, are discussed in depth as essential in adaptive and resilient CCAM operations. The review concludes that predictive and extendable ODDs require a data-driven and interoperable mobility ecosystem linking vehicles, infrastructure, and governance. Future research should focus on developing measurable indicators for infrastructure readiness, advancing simulation tools for dynamic ODD monitoring, and integrating human-in-the-loop systems for safe mixed traffic. Aligning these advances with Safe System Design and AI governance frameworks will enable scalable and trustworthy automated mobility.

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