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Understanding the tire‒road friction system is fundamental for evaluating the skid resistance of asphalt pavements. Literature analysis reveals that the trajectory of tire–road friction research aligns with the evolution of scientific research paradigms: experimental science, theoretical science, computational science, and data science. Research in this field can be categorized into three scales: the rubber‒pavement scale, the tire‒road scale, and the vehicle scale. Experimental observations have yielded numerous patterns and empirical models, which serve as the foundation of this research field. Although numerical measurement devices have been used for decades, the reproducibility and comparability of the results require further improvement. Tire‒road friction theory and simulations have been well developed across these three scales, but these scales remain largely independent and unconnected. With the advancement of sensing technology, texture features have been widely exploited and used as inputs for various machine learning models to estimate pavement skid resistance. However, these models are limited in their ability to integrate friction mechanisms, resulting in relatively low interpretability. In summary, the synergistic development of the four research paradigms can promote and advance the understanding and application of tire‒road friction mechanisms. This review concludes with a discussion of current challenges and future trends, drawing implications for further research in this field.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).
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