Abstract
A railway system degrades over time due to several factors such as aging, traffic conditions, usage, environmental conditions, natural and man-made hazards. Moreover, the lack or inadequate maintenance and restoration works may also contribute to the degradation process. In this aspect it is important to understand the performance of transportation infrastructures, the variables influencing its degradation, as well as the necessary actions to minimize the degradation process over time, improve the security of the users, minimize the environment impact as well as the associated costs. Thus, it is crucial to follow structured maintenance plans during the life cycle of the infrastructure supported by the forecasting of the degradation over time. This paper presents a brief description of the variables influencing the degradation of a rail-way system, and the way the performance of the railway track can be measured, within a probabilistic environment. The work developed in other transportation infrastructures, like roadway, is briefly presented for comparison purposes and benchmarking. It also presents an overview of the predictive models being used in railway systems, from the mechanistic to the data-driven models, where the statistical and artificial intelligence models are included.
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Acknowledgments
This work was partly financed by FEDER funds through the Competitivity Factors Operational Programme—COMPETE and by national funds through FCT Foundation for Science and Technology within the scope of the project POCI-01-0145-FEDER-007633. This work was supported by the European Commission-Shi. 2 Rail Program under the project “IN2TRACK2–826255-H2020-S2RJU-2018/H2020-S2RJU CFM-2018”.
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Morais, M.J., Sousa, H.S., Matos, J.C. (2021). An Overview of Performance Predictive Models for Railway Track Assets in Europe. In: Matos, J.C., et al. 18th International Probabilistic Workshop. IPW 2021. Lecture Notes in Civil Engineering, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-030-73616-3_11
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