Urban transport networks face pressure from urbanization, climate change, and the growing share of connected and automated vehicles, yet intelligent transport systems (ITS) and pavement engineering have evolved largely in parallel. Traffic control is rarely informed by the structural state of the pavement it loads, and pavement management rarely uses real-time traffic data. This structured narrative review synthesizes 85 sources, most published between 2020 and 2026, identified through publisher-platform searches and citation tracking, and checked against a documented Scopus and Web of Science search. Studies are compared across three interacting layers, namely, the smart city information layer (ITS services, V2X communication, cooperative ITS, and traffic management centers), the geometric layer (intersections, multimodal hubs, and lane management), and the physical layer (sustainable materials, climate-resilient pavements, and data-driven pavement management), using explicit rules for coding agreement, contradiction, and strength of evidence. Within each layer, methods converge, but the benefits are demonstrated mainly in simulation, and their magnitude, validation, and transferability remain contested. Across layers, the main gap lies at the digital–physical interface. The authors propose a pavement-aware ITS architecture in which traffic and pavement states share one decision layer, specify its inputs and control objective, outline a validation scenario and its side effects, and derive six priority research directions.
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Vujić et al. (2026) studied this question.
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