• Journal of the Korean Institute of Telematics and Electronics
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• v.10 no.5
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• pp.16-20
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• 1973

The most important thing in locating disturbances in optimal rapid traffic singnal control is to collect information cocerning toraffit flow by means of a detection method. In order to set up an optimal traffic singnal period, the analysis of a delay time phenomena in the signal period must also be considered. In fact, each of the distributed traffic quantities on the road are not similar factors in view of speeds and distances of succeeding cars. The causing factors are analyzed by the method of control engineering analysis, and they are coincident with disturbance. Thus distubances cause errors. Distubances are fuctions of time, and are classified into three conditions: Natural road state and weather are the first. The second is structures and function of vehicles, and the third is inducedbydrivers. This thesis deals with the last two cases except the first one for maximum utilization of the existing road state and weather conditions. The first condition remains constant, and then there exist some relations between vehicles and drivers. In the long run, it can be shown that the scheme for minimizing whole errors in the optimal traffic signal time setting is definitely presented.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• Fire Science and Engineering
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• v.23 no.3
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• pp.79-84
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• 2009

The smoke control system plays the most important role in securing evacuation environment when a fire occurs in road tunnels. Smoke control methods in road tunnels are classified into two categories which are longitudinal ventilation system and transverse ventilation system. In this study it is intended to review the characteristics of smoke behavior by performing numerical analysis for calculating the optimal smoke exhaust air volume when a fire occurs in tunnels in which transverse ventilation is applied, and for obtaining the basic data required for the design of smoke exhaust systems by deriving optimal smoke exhaust operational conditions for various conditions. As a result of this study, when the critical velocity in the tunnel is 1.75m/s and 2.5m/s, the optimal smoke exhaust air volume has to be more than $173m^3/s$, $236m^3/s$ for the distance of the smoke moving which can limit the distance to 250m. In addition, in case of uniform exhaust the generated smoke is effectively taken away if the two exhaust holes near the fire region are opened at the same time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.53-64
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• 2013

The car-following model is one of core models in Advanced Vehicle & Highway Systems (AVHS). The car-following model has been developed in aspects such as human factor and reduction error rates. However, the consideration of safety depending on weather condition has not been completed yet. In this paper, therefore, changes of driving condition for car-following due to different road condition were dealt with, and optimal safety distance corresponding to road condition such as dry, wet and snowy were computed. The GMIT(GM Model with Instantaneous T) model was picked over for simulation of adaptive cruise control applied the suggested optimal safety distance. As the results, the 1.7 times longer safety distance was required for wet road condition than dry road condition, and the 5.6 times longer safety distance was required for snowy road condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.299-310
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• 2022

The ability of an automated driving system is based on vehicle sensors, judgment and control algorithms, etc. The safety of automated driving system is highly related to the operational status of the road network and compliant road infrastructure. The safe operation of automated driving necessitates continuous monitoring to determine if the road and traffic conditions are suitable and safe. This paper presents a node and link system to build a road monitoring system by considering the ODD(Operational Design Domain) characteristics. Considering scalability, the design is based on the existing ITS standard node-link system, and a method for expressing the monitoring target as a node and a link is presented. We further present a technique to classify and manage hazard risk into five levels, and a method to utilize node and link information when searching for and controlling the optimal route. Furthermore, we introduce an example of system implementation based on the proposed node and link system for Sejong City.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.367-374
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• 2004

Roads which were not considered conditions such as capacity of the traffic have made seriously traffic problems and complex road lines. Construction of new roads have to make efficiently for solving the above problems and gain benefits. Simulation using 3D-GIS help find a matter of the design and do understanding users who work In the practical businesses. This study is showed selection of the optimal road line based on 3D-GIS through the traffic modeling.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.425-431
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• 2006

Recently, the government has adjusted the 4th National Master Plan in an effect to achieve balanced national land development. However, the current traffic accident index ranks among the lowest in OECD countries, ranking 25th out of 29 countries. Therefore, this study is aimed at indicating problems with National Expressway and local roads developing a solution by analyzing the problems and suggesting the most appropriate design speed for inter-changes where the traffic accidents occur frequently. With the results, it is to obtain a design speed decision formula at interchange branch points to prevent traffic accidents, secure safe and optimal road conditions and maximize traffic load capability.

• International Journal of Internet, Broadcasting and Communication
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• v.6 no.2
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• pp.20-24
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• 2014

These days the large-scale car accidents have often been occurred by overspeeding in disregard of sharp curve, foggy and freezing regions. This paper has proposed the algorithm to calculate the safety speed in real time that can protect the car accidents under these weather and road conditions using Fuzzy reasoning theory. Under raining and snowing, drivers have to slow down the traffic safety speed by 1/3 of the traffic safety speed indicated on the existing speed sign plate based on their decision. So it is difficult to calculate and then observe the safety speed. This paper has performed the simulation that provides the deivers with the optimal safety speed considering the road and weather conditions in real time to improve these problems. We have proved this method can improve more 25% than the existing one.

• Journal of Korean Society of Forest Science
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• v.90 no.3
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• pp.324-330
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• 2001

This study was carried out to develop prediction model for fill slope failure of forest road in igneous rock area using fuzzy theory which is non-linear model. The results were summarized as follows. The importance weight of factors on fill slope failure was ranked in the order of fill slope length, fill slope gradient, soil type, aspect, road position and longitudinal slope form. The degree of potential slope failure was high mainly under the such conditions as fill slope length greater than 8m, fill slope gradients steeper than $40^{\circ}$, constituent material with weathered rock, aspect of NE and road on ridge position. The optimal prediction model was developed with 0.15 of optimal coefficient(c) and 3.1165 of ${\lambda}$-value when fuzzy integral value of slope failure possibility is more than 0.5. And the discriminant accuracy was 86.8%, which shows the high availability for discrimination.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.47-54
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• 2006

In order to reduce traffic accidents, many researchers studied a traffic accident model. The Cause of traffic accidents is usually the mis calculation of traffic signals or bad traffic intersection design. Therefore, to analyse the cause of traffic accidents, it takes effort. This paper, it calculates the optimal safe car speed considering intersection conditions and weather conditions. It will recommend calculation of 1/3 in vehicle speed when there are rainy days and snow days. But the problem is that it will always display the same speed limit when whether conditions change. In order to solve these problems, in this paper, it is proposed the calculation of optimal safety speed algorithm uses weather conditions and road conditions. Computer simulations is prove that it computes the traffic speed limit correctly, which proposed considering intelligent traffic accident prediction algorithms.