路面结冰条件判别标准及SVM预测分析研究

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Abstract The relationship between precipitation types and meteorological factors was surveyed based on the effect analysis of main meteorological parameters on asphalt pavement surface icing conditions and prediction analysis model of asphalt pavement temperature was established. This study aims to determine the correlation between icy pavement and meteorological factors and implement an accurate prediction of the icing condition of pavement. Considering the road slipperiness criterion presented by Norrman, a discriminative standard of icing condition of asphalt pavement surface in the central area of Zhejiang Province was proposed. Based on the above analysis results, a prediction model of pavement surface icing condition involved in asphalt pavement and ambient temperatures under the condition of different precipitation types was constructed by using support vector machine (SVM) method. Results demonstrate that (1) the distribution characteristics of daily mean air temperature, daily mean pavement temperature, daily average wind speed, and average daily rainfall have remarkable differences under the condition of different precipitation types, wherein the variation features of daily mean air temperature and daily mean pavement temperature are obvious; (2) the indirect prediction of precipitation type and pavement surface temperature could be accomplished in terms of meteorological monitoring data; (3) the influence of pavement surface icing conditions on driving safety is lower than that of rainwater freezing on a cold surface, melting snow at air temperature above 0℃, and melting snow at air temperature below 0℃; and (4) the SVM-based prediction model of pavement surface icing condition has an accurate analysis result with misreporting rate below 6%. The generalization ability of the proposed model is good and fully demonstrates the application prospects of SVM in the pavement weather prediction field. This study can provide theoretical and technical support for real-time warning about icy asphalt pavements in winter.

Key words： road engineering icing prediction model support vector machine(SVM) asphalt pavement meteorological factors prediction analysis

Received: 01 October 2017

Fund:Supported by the Natural Science Foundation of Zhejiang Province of China (No. LY18E080020), the Natural Science Foundation of China (No. 51408550)

Corresponding Authors: QIU Xin E-mail: xqiu@zjnu.cn

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	QIU Xin
	XU Jing-xian
	TAO Jue-qiang
	YANG Qing

Cite this article:

QIU Xin,XU Jing-xian,TAO Jue-qiang, et al. Asphalt Pavement Icing Condition Criterion and SVM-based Prediction Analysis[J]. Journal of Highway and Transportation Research and Development, 2018, 12(4): 1-9.

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http://manu27.magtech.com.cn/Jwk_gljtkj_en/EN/ OR http://manu27.magtech.com.cn/Jwk_gljtkj_en/EN/Y2018/V12/I4/1

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