MENG Sitong,BAI Aijuan,ZHENG Zijun,et al.Analysis of Winter Pavement Ice Warning Threshold of Yakang Expressway in Western Sichuan[J].Journal of Chengdu University of Information Technology,2023,38(05):615-620.[doi:10.16836/j.cnki.jcuit.2023.05.018]
川西雅康高速道路冬季路面结冰预警阈值分析
- Title:
- Analysis of Winter Pavement Ice Warning Threshold of Yakang Expressway in Western Sichuan
- 文章编号:
- 2096-1618(2023)05-0615-06
- Keywords:
- Yakang expressway; icy roads; pavement temperature; slip coefficient; early warning monitoring
- 分类号:
- P429
- 文献标志码:
- A
- 摘要:
- 针对雅康高速冬季由道路结冰导致的交通事件频发问题，利用2020年11月-2021年1月雅康高速两个隧道口的气象和路况观测数据，分析高速公路路面结冰的气象环境条件，建立大气温度与路面温度的关系模型，进行道路结冰风险等级的精细化判识。研究表明:在有路况观测的高速路段，路面湿滑系数能够较迅速地反映道路结冰状态，湿滑系数小于0.58是雅康高速路面结冰湿滑的阈值条件。将大气温度低于2.5 ℃，路面温度低于-2.5 ℃且有降水出现作为路面结冰的基本环境条件。雅康高速大气温度和路面温度的线性回归模型系数为0.97，优于抛物线模型，可以较好地拟合道路温度，并用于判识道路结冰的风险判识。
- Abstract:
- Aiming at the frequent traffic incidents caused by road icing in winter, the meteorological and road condition observation data of the two tunnel entrances of Yakang Expressway from November 2020 to January 2021 were used to analyze the meteorological environmental conditions of highway pavement icing, establish a relationship model between atmospheric temperature and pavement temperature, and make a refined identification of road icing risk level. The results show that in the highway section with road condition observation, the slippery coefficient of the road surface can reflect the road icing state more quickly, and the slip coefficient is less than 0.58, which is the threshold condition for icy and slippery pavement of Yakang Expressway. The atmospheric temperature is below 2.5 ℃, the road surface temperature is below -2.5 ℃ and the precipitation is used as the basic environmental conditions for road surface icing. The coefficient of linear regression model of Yakang high-speed atmospheric temperature and road surface temperature is 0.97, which is better than the parabolic model, which can better fit the road temperature and be used to identify the risk of road ice.
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备注/Memo
收稿日期:2022-04-27
基金项目:国家自然科学基金资助项目(U2242202); 中国气象局创新发展专项资助项目(CXFZ2022J012); 高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金资助项目(SCQXKJYJXMS202210)
通信作者:郑自君.E-mail:441727466@qq.com.