Integrating Artificial Intelligence in Pavement Design for Smart and Sustainable Urban Infrastructure: A Review

International Journal of Civil Engineering

© 2026 by SSRG - IJCE Journal

Volume 13 Issue 3

Year of Publication : 2026

Authors : Swati Sonawane, Aroushi Bhagwat, Mugdha Kshirsagar, Shailendra Banne

10.14445/23488352/IJCE-V13I3P120

How to Cite?

Swati Sonawane, Aroushi Bhagwat, Mugdha Kshirsagar, Shailendra Banne, "Integrating Artificial Intelligence in Pavement Design for Smart and Sustainable Urban Infrastructure: A Review," SSRG International Journal of Civil Engineering, vol. 13,  no. 3, pp. 274-286, 2026. Crossref, https://doi.org/10.14445/23488352/IJCE-V13I3P120

Abstract:

Resilient, sustainable, and efficient infrastructures are essential in smart cities, and pavements play a critical role in facilitating mobility and connectivity. Artificial Intelligence (AI) is emerging as a disruptive paradigm in the design and use of pavements; it is providing tools and processes, leveraging real data to facilitate decision-making and improve pavement performance. This review will provide an overview of AI in the domain of pavement engineering that explores the following aspects: Material characterization, design optimization, performance prediction, and maintenance planning. By synthesizing recent research studies, this review illustrates that using techniques such as machine learning, deep learning, and predictive modelling will enhance performance accuracy, increase cost effectiveness, and create adaptive design models that will foster smart city applications. Despite the potential for innovation through the application of AI in pavement engineering, some challenges must be resolved: Comprehensive and standardized datasets are needed, AI models must be more transparent and explainable, and AI applications must be integrated into existing design and management processes. The study concludes with an emphasis that AI has the potential to enable smart, sustainable mobility and that AI represents new technology, but will also be a novel way to optimize future urban infrastructure.

Keywords:

AI, Deep Learning, Intelligent Transportation, Machine Learning, Pavement Design, Predictive Modelling, Smart Cities.

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