• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.686-693
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• 2014

This study presents a model that enables to predict road surface temperature using neural network theory. Historical road surface temperature data were collected from Road Weather Information System. They used for the calibration of the model. The neural network was designed to predict surface temperature after 1-hour, 2-hour, and 3-hour from now. The developed model was performed on Cheongwon-Sangju highway to test. As a result, the standard deviation of the difference of the predicted and observed was $1.27^{\circ}C$, $0.55^{\circ}C$ and $1.43^{\circ}C$, respectively. Also, comparing the predicted surface temperature and the actual data, R2 was found to be 0.985, 0.923, and 0.903, respectively. It can be concluded that the explanatory power of the model seems to be high.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.221-228
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• 2020

As industrial technology advances, convenience is also being developed. Many people living in big cities are commuting using transportation such as buses, taxis, cars, etc. and enjoy leisure, so research is needed to reduce the damages caused by traffic accidents. This study deals with estimating road-level rainfall in real-time. A rainfall observation data and radar data provided by the Korea meteorological administration were collected in real-time to create an integrated database, which was estimated as road-level rainfall by universal kriging method. Besides, we conducted a study to interactively visualization of mash-up road traffic information in real-time with integrating rainfall information.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.475-478
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• 2009

안개가 교통사고를 유발시키는 원인을 살펴보면 운전자의 시거와 밀접한 관련이 있다. 짙은 안개가 발생하게 되면 돌발상황이 발생하였을 때 도로를 주행하던 차량이 안전하게 정지하기 위해서 필요한 최소 정지거리가 증가하게 되나 안개로 인한 시정이 나빠지게 되어서 사고발생확률이 높은 것이다. 또한 안전한 시거가 확보되지 않기 때문에 단독사고 발생 후 뒤따르던 차량이 전방을 확인하지 못한 상황에서 연쇄 충돌하게 되어 사고가 대형화된다. 이에 본 연구에서는 IT기술인 RFID와 USN을 이용하여 안개로 인한 시정거리에 따라 도로에 있는 과속카메라가 도로주행 한계속도를 자기 스스로 판단하여 자동조절하게 만들고 변경된 한계속도를 그 도로를 이용하는 차량운전자 휴대폰에 문자로 전송해주고 도로전광판에서도 정확하게 주행속도정보를 볼 수 있게 한다. 그리하여 도로주행 한계속도를 어기는 차량에는 범칙금을 부과하게 만든다. 본 연구를 통해 안개에 대한 교통사고의 위험을 줄이고 사회적 경제적으로 이익이 되도록 하기위해 기상상태 변화에 따른 USN 기반의 도로주행 한계속도 지능적 조정 관리시스템을 제안하고자 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1611-1617
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• 2013

Information about trafficability or the condition of road with regard to its being traveled over by vehicles is one of the most critical factors for roadway operation in winter. Specifically, when traveling on snowy or icy surfaces, the traction force varies per vehicle type including tire types, geometric characteristics of roads, and conditions of road surfaces. In general, front-wheel drive or four-wheel drive vehicles have better traction performance on snowy or icy surface than rear-wheel drive vehicles, and the latter type vehicle causes more serious traffic congestion when there is unexpected snowfall. Thus, traffic information regarding trafficability with respect to vehicle types, geometric characteristics of roadway sections, and roadway surface conditions can provide a foundation to make a decision whether to use the associated roadway sections for roadway operators as well as users. Based on the preceding premise, the objective of this study is to present a methodology for developing a trafficability index with respect to vehicle types, geometric characteristics of roadway sections, and roadway surface conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.57-65
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• 2008

Wireless sensor networks achieve environment monitoring and controlling through use of small devices of low cost and low power. Such network is comprised of several sensor nodes, each having a microprocessor, sensor, actuator and wired/wireless transceiver inside a small device. In this paper, we employ the sensor networks in order to design and implement a real-time vehicle safety system. Such system can inform the safe velocity in a specific weather condition to drivers in advance through analyzing the weather data collected from sensor networks. As a result, the drivers can prevent effectively accidents by controlling their car speed.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.441-451
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• 2014

This study proposes a novel performance measure, which is referred to as Hazardous Spacing Index (HSI), to be used for evaluating safety of traffic stream on freeways. The basic principle of the proposed methodology is to investigate whether drivers would have sufficient stopping sight distance (SSD) under limited visibility conditions to eliminate rear-end crash potentials at every time step. Both Road Weather Information Systems (RWIS) and Vehicle Detection Systems (VDS) data were used to derive visibility distance (VD) and SSD, respectively. Moreover, the K-Nearest Neighbors (KNN) method was adopted to predict both VD and SSD in estimating predictive HSIs, which would be used to trigger advanced warning information to encourage safer driving. The outcome of this study is also expected to be used for monitoring freeway traffic stream in terms of safety.

• 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.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.138-146
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• 2024

Purpose: The purpose of this study is to find cases of using information and communication technology and smart mobility technology in snow removal vehicles and equipment for rapid and efficient road snow removal in the event of a snowstorm, and to find ways to utilize them. Method: Cases of domestic and overseas snow removal methods are investigated, and snow removal operation methods incorporating new technologies are presented. Result: Most of the operation of snow removal equipment in Korea uses GPS, CCTV, and road traffic information systems, and in the case of overseas, road weather information systems and road snow removal monitoring systems are used. It is expected that snow removal technology using autonomous snow removal vehicles, which are smart mobility, will be developed in the future. Conclusion: The results of this study can contribute to the policy of using snow removal equipment and snow removal vehicles of local governments and related organizations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.30-41
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• 2022

With the advent of autonomous driving, personal mobility, drones, and smart roads, it is necessary to respond to changes in the road traffic environment in the road guidance system. However, the use of road signs to guide the road is decreasing compared to the past due to the advent of devices such as navigation and smartphones. Therefore, in this study, a large-scale survey was conducted to derive road sign issues and usage plans to respond to future changes. Based on this, this study presented a strategy to diversify road sign functions by analyzing the factors affecting the use of road signs by citizens. As a result, first, it is necessary to provide real-time variable road guidance information that reflects user needs such as traffic, weather, and local events. Second, it is necessary to informatize digital road signs such as reflecting maps with precision. Third, it is necessary to demonstrate road guidance in a virtual environment that reflects various future mobility and road environments.

• Journal of the Society of Disaster Information
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• v.13 no.2
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• pp.199-212
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• 2017

Rapid roadway snow removal is significantly important due to difficult occurrence estimation of heavy snowfall disasters by global warming and climate change. Local governments of S. Korea have snow removal equipments and vehicles based on past experiences without considering snowfall and roadway characteristics. The objective of this research is to develop the demand estimation procedure for snow removal equipments and vehicles based on regional snowfall and roadway characteristics. This research first classifies regional snowfall characteristics using KMO's ten-year snowfall data. Second, roadway snow removal length is computed for local governments. Real possession data is compared with demand estimation of snow removal equipments & vehicles for each local government with roadway snow removal scenarios. Finally, required demands of snow removal equipments & vehicles are predicted by concerning regional snowfall amount and required snow removal hours. Results from this research are used for developing heavy snowfall disaster management policies for optimal demands and snow removal routes of 229 local governments.