Forecast model for road surface conditions along winter roads
| Project/Area Number |
26350490
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Natural disaster / Disaster prevention science
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| Research Institution | Nihon University |
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Principal Investigator |
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 路面凍結予測 / ニューラルネットワーク / 判別分析 / 路面状態予測 / 冬季路面管理 / 冬季道路管理 / 路面凍結予測システム / 交通工学 |
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| Outline of Final Research Achievements |
We proposed a forecast model that uses a neural network to predict what the winter road surface conditions will be after three hours in order to increase the efficiency of anti-icing programs. In order to establish the forecast model, learning models of the road surface temperature and detecting water on road surfaces at a specific site were created. These learning models were then applied to other sites along an expressway and national highways and the correct classification of the road surface conditions was examined. The results of the present study revealed that the road surface conditions along an expressway and national highways can be predicted with acceptable precision three hours in advance by applying a learning model to the time series variation of the road surface temperature and other variables.
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Report
(4 results)
Research Products
(2 results)
