A Comprehensive Review of Winter Road Surface Conditions Monitoring and Modeling: From Sensing to Decision Support for Sustainable and Resilient Transportation Systems

Accurate and timely assessment of winter road surface conditions (WRSC) is critical to maintaining road safety, minimizing weather-related disruptions, and ensuring the cost effectiveness and sustainability of winter road maintenance (WRM) operations. As climate variability and extreme winter events become more frequent, transportation systems increasingly rely on precise, data-driven approaches for WRSC monitoring and modeling to support reliable mobility. This paper presents a comprehensive literature review of WRSC monitoring and modeling approaches. Although a wide range of sensing technologies and modeling techniques have been developed, existing studies scattered across various disciplines often lack an integrated perspective that connects monitoring, modeling, and decision support. To address this gap, this review provides a structured and integrative overview of WRSC research, synthesizing advances in monitoring technologies, including stationary and mobile in situ sensors, vehicle-based observations, and remote sensing platforms, with developments in WRSC modeling. Modeling approaches are categorized into physics-based models, conventional statistical methods, geospatial and spatiotemporal techniques, and artificial intelligence approaches, including machine learning and deep learning. Emerging hybrid and multimodal frameworks that combine heterogeneous data sources through data fusion and intelligent modeling are highlighted for their potential to improve spatial coverage, predictive accuracy, and real-time applicability. The review further identifies key methodological, data-related, and operational challenges that constrain large-scale deployment and transferability across regions. Finally, future research directions are discussed with an emphasis on integrated monitoring-modeling frameworks, uncertainty-aware decision support, and scalable solutions to enable safer, smarter, and more sustainable and resilient winter transportation systems.