• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1507-1516
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• 2020

This study analyzed the scenario for road freezing section by applying the road freezing evaluation algorithm. To apply road freezing algorithm, the influencing factors on road freezing were reviewed. Observation data from four points, Mokgam IC, Jeongneung tunnel, Seongsan bridge, and Yeomchang bridge were used for analysis. All observatories are installed on the expressway, and they are classified for the analysis of road freezing characteristics. When the difference between the road surface temperature and dew-point temperature of the road freezing evaluation algorithm was 3℃ or less, the section where road freezing occurred was checked. In addition, road freezing evaluation was derived through the change of the road surface condition and water film thickness of the freezing section.

• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1355-1369
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• 2021

This study improved the algorithm for the road ice prediction algorithm and analyzed the prediction rate when comparing actual field measurement data and algorithm prediction value. For analysis, road and weather conditions were measured in Geumdong-ri, Sinbuk-myeon, Pocheon-si. First algorithm selected previous research result algorithm. And the 4th algorithm was improved according to the actual freezing conditions and measured values. Finally, five algorithms were developed: freezing by condensation, freezing by precipitation, freezing by snow, continuous freezing, and freezing by wind speed. When forecasting using an algorithm at the Pocheon site, the freezing hit rate was improved to 93.2%. When calculating the combination ratio for the algorithm. the algorithm for freezing due to condensation and the continuation of the frozen state accounted for 95.7%.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.531-541
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• 2018

Road freezing caused by snowfall during wintertime causes traffic congestion and many accidents. To prevent such problems, we developed, in this study, a system to predict road freezing based on weather forecast data and the freezing generation modules. The weather forecast data were obtained from a high-resolution model with 1 km resolution for Jeju Island from 00:00 KST on December 1, 2017, to 23:00 KST on February 28, 2018. The results of the weather forecast data show that index of agreement (IOA) temperature was higher than 0.85 at all points, and that for wind speed was higher than 0.7 except in Seogwipo city. In order to evaluate the results of the freezing predictions, we used model evaluation metrics obtained from a confusion matrix. These metrics revealed that, the Imacho module showed good performance in precision and accuracy and that the Karlsson module showed good performance in specificity and FP rate. In particular, Cohen's kappa value was shown to be excellent for both modules, demonstrating that the algorithm is reliable. The superiority of both the modules shows that the new system can prevent traffic problems related to road freezing in the Jeju area during wintertime.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.5
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• pp.113-121
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• 2013

The road icing forecast and snow detection system using state evaluation algorithm of multi sensor optimizes snow melting system to control spread time and amount of chemical spread application This system operates integrated of contact/non-contact sensor and infrared camera. The state evaluation algorithm of the system evaluates road freezing danger condition and snowfall condition (snowfall intensity also) using acquired data such as temperature/humidity, moisture detection and result of image signal processing from field video footage. In the field experiment, it proved excellent and reliable evaluated result of snowfall state detection rate of 89% and wet state detection rate of 94%.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.8-19
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• 2016

Potholes are caused by the presence of water in the underlying soil structure, which weakens the road pavement by expansion and contraction of water at freezing and thawing temperatures. Recently, automatic pothole detection systems have been studied, such as vibration-based methods and laser scanning methods. However, the vibration-based methods have low detection accuracy and limited detection area. Moreover, the costs for laser scanning-based methods are significantly high. Thus, in this paper, we propose a new pothole detection system using a commercial black-box camera. Normally, the computing power of a commercial black-box camera is limited. Thus, the pothole detection algorithm should be designed to work with the embedded computing environment of a black-box camera. The designed pothole detection algorithm has been tested by implementing in a black-box camera. The experimental results are analyzed with specific evaluation metrics, such as sensitivity and precision. Our studies confirm that the proposed pothole detection system can be utilized to gather pothole information in real-time.