• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.117-132
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• 2021

Due to the terrain in Korea, there are many road sections passing through mountainous areas. During the winter, there is a higher risk of traffic accidents, due to black ice caused by the lack of sunlight. Despite domestic road freezing safety measures, accidents caused by road freezing results in severe traffic accidents. Under these considerations, this study analyzed whether traffic safety signs that change in response to the external temperature help drivers recognize frozen road segments. The study was conducted through analysis of the effect of the signs on a driver's perspective. For the signs under development, out of the signs designed by experts, the sign design which received the highest visibility and effectiveness evaluation ratings from the general public was selected. The sign was implemented through Virtual Reality (VR) and installed on the right side of the road to analyze the effect on gazing and driving behavior. As a result of analyzing the driver's driving behavior, a speed reduction of about 7km/h or more was found in the sign section. Therefore, It was found that the existence of the sign had a strong relationship with the rate of the drivers' speed reduction.

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.577-582
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• 2009

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.191-198
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• 2009

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.603-608
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• 2009

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.221-226
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• 2009

• 한국도로학회:학술대회논문집
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• 2010.09a
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• pp.315-320
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• 2010

• 한국도로학회:학술대회논문집
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• 2010.03a
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• pp.255-260
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• 2010

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.524-526
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• 2021

As the invention of automobiles and construction of roads for vehicles began, the occurrence of traffic accidents began to increase. Accordingly, efforts were made to prevent traffic accidents by changing the road construction method and using signal systems such as traffic lights, but until now, numerous human and property damages have occurred every year due to traffic accidents caused by freezing of the road due to bad weather. In this paper, we propose a method of transmitting ice detection data detected using vehicle sensor data to vehicle navigation to reduce traffic accidents caused by road freezing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.521-523
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• 2021

As the invention of automobiles and construction of roads for vehicles began, the occurrence of traffic accidents began to increase. Accordingly, efforts were made to prevent traffic accidents by changing the road construction method and using signal systems such as traffic lights, but even today, numerous human and property damages have occurred due to traffic accidents caused by freezing of the road due to bad weather. In this paper, in order to reduce traffic accidents due to road freezing, we propose a method of transferring the ice detection information obtained by deep learning of infrared wavelength data obtained using an infrared camera to the vehicle's navigation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.55-66
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• 2020

This study developed four algorithms and their associated indices that can quantify and qualify road hazards along roadways. Initially, relevant raw data can be collected from commercial vehicles by camera and DTG. Well-processed data, such as potholes, road freezing, and fog, can be generated from the Integrated management system. Road hazard algorithms combine these data with road inventory data in the Data Sharing Platform. Depending on well-processed data, four different road hazard algorithms and their associated indices were developed. To test the algorithms, an experimental plan based on passive DTG attached in probe vehicles was performed at two different test locations. Selection of the test routes was based on historical data. Although there were limitations using random data for commercial vehicles, hazardous roadways sections, such as fog, road freezing, and potholes, were generated based on actual historical data. As a result, no algorithm error was found in the entire test. Because this study provides road hazard information according to a section, not a point, it can be practically helpful to road users as well as road agencies.