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Article Dans Une Revue European Journal of Environmental and Civil Engineering Année : 2023

A novel extreme gradient boosting algorithm based model for predicting the scour risk around bridge piers: application to French railway bridges

Résumé

Skid resistance is a significant feature that provides consistent traffic safety management for road pavements. An appropriate level of Skid resistance describes the contribution that the pavement surface makes to tire/road friction, and the surface of the road pavement can reduce vehicle operation cost, traffic accidents, and fatalities, particularly in wet conditions. Wet conditions decrease the level of the skid resistance (pavement friction), and this may lead to serious struggles related to driving on the road pavement (e.g., skidding or hydroplaning), which contributes to higher crash rates. The knowledge of skid resistance is essential to ensure reliable traffic management in transportation systems. Thus, a suitable methodology of skid resistance measurement and the understanding of the characterization of the road pavement are key to allow safe driving conditions. This paper presents a critical review on the current state of the art of the research conducted on skid resistance measurement techniques, taking into account field-based and laboratory-based methodologies, and novel road sensors with regard to various practices of skid resistance, factors influencing the skid resistance, the concept of the minimum skid resistance and thresholds. In conclusion, new trends that are relevant to data collection approaches and innovative procedures to further describe the data treatment are discussed to achieve better understanding, more accurate data interoperability, and proper measurement of skid resistance.
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Dates et versions

hal-04197348 , version 1 (06-09-2023)

Identifiants

Citer

Tianyu Wang, Philippe Reiffsteck, Christophe Chevalier, Zhehao Zhu, Chi-Wei Chen, et al.. A novel extreme gradient boosting algorithm based model for predicting the scour risk around bridge piers: application to French railway bridges. European Journal of Environmental and Civil Engineering, 2023, 27 (3), pp.1104-1122. ⟨10.1080/19648189.2022.2072957⟩. ⟨hal-04197348⟩
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