• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.116-125
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• 2014

Road conditions can provide important information for driving safety in driving assistance systems. The input images usually include unnecessary information and they need to be analyzed only in a region of interest (ROI) to reduce the amount of computation. In this paper, a vision-based road ROI determination algorithm is proposed to detect the road region using the positional information of a vanishing point and line segments. The line segments are detected using Canny's edge detection and Hough transform. The vanishing point is traced by a Kalman filter to reduce the false detection due to noises. The road ROI can be determined automatically and adaptively in every frame after initialization. The proposed method is implemented using C++ and the OpenCV library, and the road ROIs are obtained from various video images of black boxes. The results show that the proposed algorithm is robust.

• Journal of the Korean Society of Safety
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• v.21 no.5 s.77
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• pp.1-5
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• 2006

This study provides a basic data necessary to design a facility of smoke management after calculating the critical velocity of the gradient scale model tunnel and reviewing its adequacy to establish an optimum disaster prevention system for a road tunnel at fire. The experiment is carried out by using Froude scaling to a scale model which is about 1/29 as big as the real tunnel, and its critical velocity calculation is calculated to the 0-2% gradient of the tunnel. The result shows that the higher the gradient is, the stronger the critical velocity, but that it doesn't affect the critical velocity so much when the gradient is less 2%. In addition, this result is studied in comparison with the results done by other researchers to review the adequacy of the critical velocity.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.232-237
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• 2009

Active safety vehicle devices are getting more attention recently. To prevent traffic accidents, the environment in front and even around the vehicle must be checked and monitored. In the present applications, mainly camera and radar based systems are used as sensing devices. Laser scanner, one of the sensing devices, has the advantage of obtaining accurate measurement of the distance and the geometric information about the objects in the field of view of the laser scanner. However, there is a problem that detecting object occluded by a foreground one is difficult. In this paper, criterions are proposed to manage this problem. Simulation is conducted by vehicle mounted the laser scanner and multiple-hypothesis algorithm tracks the candidate objects. We compare the running times as multi-hypothesis algorithm parameter varies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2007.11a
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• pp.369-374
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• 2007

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2007.11a
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• pp.375-380
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• 2007

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.489-498
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• 2016

The objective of this study is to develop road traffic accident model involving child pedestrian especially at school zones and its surrounding area. The analysis is based upon traffic accident data collected near sixty elementary schools in City of Cheongju during 2012 and 2014. This study results in two statistical models ; one is to predict the number of road traffic accidents involving children, and the other is to predict EPDO(Equivalent Prperty Damage Only). These models are represented as Poisson models. which are statistically significant with the likelihood ratios of 0.533 and 0.273. The common explanatory variables of these models are the ratio of road section with more than 4 lanes, the number of entrance and exit, the number of signalized crosswalk in school zone, the number of school zone signage including road surface marking, and the number of speed limit signs. The specific variables are the length of road stretch in school zone, the number of reflector mirrors, and the number of signalized crosswalk outside school zone. It is concluded that these types of road safety facilities can reduce the number of traffic accidents involving children at school zones and its surrounding area.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.130-135
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• 2017

This study deal with the traffic accident. The purpose of this study is to develop the accident density models reflecting the transportation and socioeconomic characteristics based on 230 zones of Korea. In this study, The models which are tested to be statistically significant are developed through multiple linear regression analysis. The main research results are as follows. First, in the transportation-based model, road length, avenue ratio, number of intersections and tunnels are analyzed to be positive to the model, however, school zone is analyzed to be negative to the model. Second, in the socioeconomic-based model, population density, transportation vulnerable ratio, children and truck ratio are analyzed to be positive to the model. Finally, in the integrated models, road ratio, population density, transportation vulnerable ratio, children ratio, truck ratio and number of companies are analyzed to be positive, however, school zone is analyzed to be negative to the model. This results could be expected to give good implications to accident-reduction policy-making.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.385-391
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• 2013

As a solution for environmental problems caused by increasing number of vehicles, it is encouraged to use a bicycle as an environment-friendly transportation method. To vitalize the bicycle usage, it is a necessary to construct bicycle roads that are safe and suitable for users. Based on the previous research results, we assume the main purposes of bicycle usages are mainly local leisure activity and school commuting. Thus, the proposed method finds the shortest link between the existing bicycle road network and bicycle usage facilities such as leisure activity places or schools over public road network. Then, we carry out the RTK DGPS survey for the candidate links, and analyze the slopes of them. When the slope of a found link is larger than a threshold, an alternative link is re-found for the safety and convenience of a bicycle user. The proposed method is applied to the real bicycle road network in Mokpo, Chunnam and the results are discussed.

• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.90-98
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• 2008

Presently, pedestrian's signal time models in korea are not considering Vulnerable-Pedestrian. So, the safety of Vulnerable-Pedestrian is being threatener and the number of accidents is increasing. Besides, the existing operational system for pedestrians can't offer the cross signal time in road corresponded the changing environment when the school zone is revitalized and the Silver zone is introduced for Vulnerable-Pedestrian. Conclusively, Vulnerable-Pedestrian's signal time models which are able to consider classified Vulnerable-Pedestrian speed, Vulnerable-Pedestrian perception-reaction time, Vulnerable-Pedestrian Spare(congestion-delay) time are suggested by the result of experiment in virtual crosswalk. the application of suggested models in this study to the site. It is possible to use as a basic stuff on study of pedestrian's signal time and expected to contribute the safety and mobility in future.