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

Area of Science:

• Transportation Engineering
• Intelligent Transportation Systems
• Automotive Technology

Background:

• Connected, Cooperative, and Automated Mobility (CCAM) promises enhanced efficiency, sustainability, and safety.
• Current CCAM deployment is hindered by fragmented Operational Design Domains (ODDs) and inadequate infrastructure readiness.

Purpose of the Study:

• To review the state-of-the-art in operational, infrastructural, and technological enablers for predictive and extendable ODDs.
• To identify gaps in ODD formalization and validation and analyze infrastructure's influence on CCAM.
• To discuss technological and organizational enablers for adaptive and resilient CCAM operations.

Main Methods:

• Comprehensive literature review of ODD definitions and standardization efforts.
• Analysis of physical infrastructure's impact on vehicle performance and safety.
• In-depth discussion of digital twins, data-driven simulation, and governance frameworks.

Main Results:

• Gaps exist in the formalization and validation of ODD boundaries.
• Physical infrastructure significantly influences CCAM performance and safety.
• Digital twins, simulation models, and governance frameworks are crucial for adaptive CCAM.

Conclusions:

• Predictive and extendable ODDs necessitate a data-driven, interoperable mobility ecosystem.
• Future research should focus on infrastructure readiness indicators, dynamic ODD monitoring, and human-in-the-loop systems.
• Alignment with Safe System Design and AI governance is vital for scalable, trustworthy automated mobility.