TY - JOUR
T1 - Climate change effects on ballasted railway tracks
T2 - A focus on structural aspects and adaptation measures based on early-warning systems and digital technologies
AU - Koohmishi, Mehdi
AU - Dai, Peng
AU - Kaewunruen, Sakdirat
AU - Guo, Yunlong
N1 - Not yet published as of 09/07/2025.
PY - 2025/6/13
Y1 - 2025/6/13
N2 - This paper provides a comprehensive review of the effects of climate change on the structural and operational performance of ballasted railway tracks, with a specific attention to integrating early-warning systems and digital technologies for climate change adaptation (CCA). Climate change factors, particularly temperature fluctuations and increased rain and flooding intensity, pose significant risks to railway infrastructures between cities, such as rail buckling, track deformation, and increased maintenance costs due to extreme weather events. To address these challenges, this paper discusses the potential of state-of-the-art technologies like Artificial Intelligence, Internet of Things, Remote Sensing, and Building Information Modelling in enhancing CCA strategies. These technologies are explored in the context of design, construction, maintenance and end-of-life management phases, providing multi-scale and multi-temporal solutions to improve infrastructure resilience. Although these technologies are in the early stages of development, their integration holds promise for revolutionizing railway CCA efforts, offering predictive maintenance and real-time monitoring capabilities for enhanced infrastructure sustainability. The study emphasizes the need for continuous innovation in CCA methodologies to keep pace with evolving climate risks.
AB - This paper provides a comprehensive review of the effects of climate change on the structural and operational performance of ballasted railway tracks, with a specific attention to integrating early-warning systems and digital technologies for climate change adaptation (CCA). Climate change factors, particularly temperature fluctuations and increased rain and flooding intensity, pose significant risks to railway infrastructures between cities, such as rail buckling, track deformation, and increased maintenance costs due to extreme weather events. To address these challenges, this paper discusses the potential of state-of-the-art technologies like Artificial Intelligence, Internet of Things, Remote Sensing, and Building Information Modelling in enhancing CCA strategies. These technologies are explored in the context of design, construction, maintenance and end-of-life management phases, providing multi-scale and multi-temporal solutions to improve infrastructure resilience. Although these technologies are in the early stages of development, their integration holds promise for revolutionizing railway CCA efforts, offering predictive maintenance and real-time monitoring capabilities for enhanced infrastructure sustainability. The study emphasizes the need for continuous innovation in CCA methodologies to keep pace with evolving climate risks.
UR - https://www.sciencedirect.com/journal/journal-of-traffic-and-transportation-engineering-english-edition
M3 - Article
SN - 2095-7564
JO - Journal of Traffic and Transportation Engineering (English Edition)
JF - Journal of Traffic and Transportation Engineering (English Edition)
ER -