• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.445-452
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• 2007

We proposed a detection scheme of weather information in CCTV video images in this paper. The scheme obtains the RGB distribution of shiny day and divide a target image into cloud, rain, snow and for RGB distributions. shiny day RGB distribution. Our scheme designed systematically to detection and separation special characteristics of images from complex weather information. Our algorithm has less overhead than the previous methods to use weather database DB at the view of time and space. And our algorithm can be use in real world system with low cost of implementation. Also, our algorithm use informations of temperature, humidity, date, and time to detect the information of weather with high quality.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.147-153
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• 2017

PURPOSES : This research aims to estimate the occurrence of hydroplaning on roads based on the road alignment types and rainfall intensity in Seoul. METHODS : Three types of data were used for estimation of hydroplaning in this study. The Inner Circulation Road (12.5 km) to the Bukbu Expressway (7.4 km) in Seoul was selected as the test road and data was collected for road information using a probe-vehicle. Precipitation was observed from Automatic Weather System in Seoul. These data were interpolated by applying Inverse Distance Weighted Methodology for hydroplaning estimation. Finally, the water depth information of the roads was observed using an RCM411 device. RESULTS : This study demonstrated that the cross slope with small-angle-tilt or vertical section with large-angle-tilt are the primary factors causing hydroplaning on the roads. The flow velocity on steep slope is high; however, large drainage lengths result in hydroplaning on the roads. CONCLUSIONS : This result can contribute towards the reduction of car accidents on rainy days. Furthermore, information regarding hydroplaning can be delivered to drivers more rapidly and precisely in the future.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.1
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• pp.48-55
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• 2009

In order to keep safe driving conditions under road networks, there are several formations such as road structure, road surface condition, traffic occupancy and supplement of an accurate information of traffic status ahead To support safe-driving on each road formation, each formation is supplied with various information to help the driver. However, in some cases like rapid status change at local-scale geography, traffic information systems often displays insufficient information because of the lack of information correlation. In order to accurately aware the driver, all road formation must be in sync. It is important to supply accurate information to the driver because this information directly impacts the drivers on the road. This paper discusses the amber information to keep the least safety driving over road formations including tunnels and bridges. This paper also will propose the informations for safe-driving conditions, information linkage on the road and rule-base safety information, as ITS technology, being displayed for all drivers under the worst weather conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.133-146
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• 2021

Providing weather information on roads today means that the road weather conditions near weather observation points are presented to road managers and road users. These weather observation points are managed by the Korea Meteorological Administration. However, it is difficult to provide accurate weather information due to physical limitations such as the presence of precipitation collection points, distance to weather information provision roads, and the presence of mountains. Therefore, this study intends to perform a comparative analysis by time zone and administrative dong provided by the Meteorological Administration using the wiper information among the information contained in the PVD(Probe Vehicle Data) collected from the highway C-ITS project. As a result of the analysis it was possible to detect rainfall even in the event of local rainfall and rainfall over a long period of time and the higher the cumulative precipitation per hour, the higher the probability of coincidence. This study is meaningful because it used PVD to solve the limitations of the existing road weather information provision method and suggested utilization plan for PVD.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1076-1079
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• 2000

In this paper, a simplified visualization method is proposed for an urban space in consideration of weather and sun moving. In the proposed method, buildings and roads with shadows are visualized by the ray tracing algorithm. Also sky, snow, and rain are visualized by textures. Some textures such as snow and rain are generated in advance by the ray casting algorithm. Then we can obtain images with weather condition and shadows of sunlight by buildings along the road in relatively low computational cost

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.661-668
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• 2015

Them traffic accidents have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. The carelessness of drivers, many road weather factors have a great influence on the traffic accidents. Especially, the number of traffic accident is governed by precipitation, visibility, humidity, cloud amounts and temperature. The purpose of this paper is to analyse the effect of road weather factors on traffic accident. We use the data of traffic accident, AWS weather factors (precipitation, existence of rainfall, temperature, wind speed), time zone and day of the week in 2013. We did statistical analysis using logistic regression analysis and decision tree analysis. These prediction models may be used to predict the traffic accident according to the weather condition.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.177-185
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• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.20-29
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• 2022

This study intends to present a traffic node-based and link-based accident prediction models using XGBoost which is very excellent in performance among machine learning models, and to develop those models with sustainability and scalability. Also, we intend to present those models which predict the number of annual traffic accidents based on road types, weather conditions, and traffic information using XGBoost. To this end, data sets were constructed by collecting and preprocessing traffic accident information, road information, weather information, and traffic information. The SHAP method was used to identify the variables affecting the number of traffic accidents. The five main variables of the traffic node-based accident prediction model were snow cover, precipitation, the number of entering lanes and connected links, and slow speed. Otherwise, those of the traffic link-based accident prediction model were snow cover, precipitation, the number of lanes, road length, and slow speed. As the evaluation results of those models, the RMSE values of those models were each 0.2035 and 0.2107. In this study, only data from Sejong City were used to our models, but ours can be applied to all regions where traffic nodes and links are constructed. Therefore, our prediction models can be extended to a wider range.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.221-229
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• 2010

In recent studies, many methods have been studied for mobile robot using magnetic markers on its pathway. This is not influenced by the weather conditions, and makes possible to develop controller with low level processors and simple algorithms. However, the interval between magnets is restricted by the magnetic field intensity and it is impossible to get road information ahead. This paper suggests a method of widening markers and expressing the road information ahead using magnetic markers, and explains a sensor arrangement considering suggested methods. Also, magnetic field analysis was done to investigate the effects of widening magnetic markers with various environments. A small mobile robot was made to figure out the performance of suggested methods, and driving experiments were performed on the straight and curved road with magnetic markers. The results show that the robot moved the prearranged pathway with 0.5 cm lateral displacements and stopped at a stop line using magnetic information on the road.