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A Study Of Road Surface Ice Prediction Based On Highway Operations And Safety

机译:基于公路运营和安全的道路表面冰预测研究

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To improve the high-risk situation of driving on icy road in cold weather, a more economy applicable measure for road ice forecasting is proposed compared with the Road Weather Information System widely used abroad. A temperature controlled laboratory with a short section of road was used to simulate the scene driving on the highway. According to the changes of temperature and precipitation, the corresponding changes of temperature close to the surface, road surface temperature and road surface ice were recorded to show the rules of the road surface temperature changes and icing development. The main purpose was to build the road surface ice prediction model. After the network training of the experiment samples using a BP neural network, the road surface ice prediction model is put forward, especially for the ice prediction of some high-risk sections, including bridges, tunnels, shady sections etc. Besides, the method contributes to the development and application of low cost icy road prediction techniques.
机译:为了提高寒冷天气冰冷道路驾驶的高风险状况,与广泛使用的道路天气信息系统相比,提出了一种经济适用的道路冰预测措施。使用短段的温度控制实验室用于模拟在高速公路上驾驶的场景。根据温度和降水的变化,记录了接近表面,道路表面温度和道路表面冰的相应温度变化,以显示道路表面温度变化和结冰发展的规则。主要目的是建立道路表面冰预测模型。在使用BP神经网络的实验样本的网络训练之后,提出了路面冰预测模型,特别是对于一些高风险部分的冰预测,包括桥梁,隧道,阴暗部分等,该方法有贡献低成本冰冷路预测技术的开发与应用。

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