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28 December 2022 A BOA-LightGBM hybrid model for estimating the dynamic friction coefficient of asphalt pavements
Yuanjiao Hu, Zhaoyun Sun, Yuxi Han
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Proceedings Volume 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022); 1250627 (2022) https://doi.org/10.1117/12.2662498
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2022), 2022, Beijing, China
Abstract
The skid resistance of the pavement has a significant impact on road safety. To accurately evaluate the change mechanism of skid resistance, a hybrid model based on Bayesian optimization algorithm (BOA) and light gradient boosting machine (LightGBM) is proposed. Firstly, the electric sander is used to obtain the mean texture depth (MTD) of the asphalt pavement. Then, the friction coefficient of road surface under dry and wet conditions is measured by dynamic friction tester at corresponding positions. Finally, a BOA-LightGBM dynamic friction coefficient estimation model is proposed based on the mean texture depth, pavement water content, and vehicle speed. The BOA algorithm is used to adjust the optimal parameters of the model. Compared with the LightGBM model, the results show that the BOA-LightGBM model fits predicted and true values better through the above factors, and the R2 value is 97.21%. It proves that the proposed model has strong stability and nonlinear fitting ability.
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Yuanjiao Hu, Zhaoyun Sun, and Yuxi Han "A BOA-LightGBM hybrid model for estimating the dynamic friction coefficient of asphalt pavements", Proc. SPIE 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022), 1250627 (28 December 2022); https://doi.org/10.1117/12.2662498
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KEYWORDS
Resistance
Data modeling
Roads
Analytical research
Evolutionary algorithms
Optimization (mathematics)
Process modeling
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