• Journal of Korean Society of Transportation
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• v.6 no.1
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• pp.43-53
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• 1988

This study is to find the proper method of estimating urban road traffic capacity. To estimate road traffic capacity, the following methods are chosen ; 1) crossing point of Q-V and S-V, 2) critical velocity and density of Q-V-K model, 3) V-K model with density parameter. The density estimated through S-V relation is 174 veh./km. The methods used in this paper yields more stable values with 2286 veh./h/ in average. The estimated average capacity by three methods are 2272 veh./h. in multilane road. 2411 veh./h in three lane road and 2185 veh./h. in two lane road.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1996.09a
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• pp.31-36
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• 1996

It is important to measure the vehicle flow in controlling the traffic system. This report deals with a traffic flow measurement system using the differential spatial filters. This system can measure the velocity the length and height profile of the vehicle. The detector is located above the traffic lane. This provides the system with the following advantages : one is that each lane can be monitored without an influence of the other lanes the other is that the system construction is simple and can be set easily.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.303-304
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• 2006

This paper proposes detection method of vehicles using camera for auto-vehicle-system. Detection method is based on shadow detection and symmetric feature of vehicle. This method consists of three part. First is lane detection. By lane detection, we can reduce the area for vehicle detection. Second part is shadow detection. Shadow has information of vehicle width and position. Third part is symmetry. This feature is helpful for confirming the vehicle.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.687-690
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• 2000

Lately, many studies have been progressed for the protection human's lives and property as holding in check accidents happened by human's carelessness or mistakes. One part of these is the development of an autonomouse vehicle. General control method of vision-based autonomous vehicle system is to determine the navigation direction by analyzing lane images from a camera, and to navigate using proper control algorithm. In this paper, characteristic points are abstracted from lane images using lane recognition algorithm with sobel operator. And then the vehicle is controlled using two proposed auto-steering algorithms. Two steering control algorithms are introduced in this paper. First method is to use the geometric relation of a camera. After transforming from an image coordinate to a vehicle coordinate, a steering angle is calculated using Ackermann angle. Second one is using a neural network algorithm. It doesn't need to use the geometric relation of a camera and is easy to apply a steering algorithm. In addition, It is a nearest algorithm for the driving style of human driver. Proposed controller is a multilayer neural network using Levenberg-Marquardt backpropagation learning algorithm which was estimated much better than other methods, i.e. Conjugate Gradient or Gradient Decent ones.

• Journal of the Korean Institute of Gas
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• v.26 no.5
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• pp.58-65
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• 2022

Gas explosion accidents could cause a catastrophe. we need specialized and systematic accident investigation techniques to shed light on the cause and prevent similar accidents. In this study, we had performed LPG explosion simulation using AUTODYN which is the commercial explosion program and predicted the damage characteristics of the structures by LNG explosive power. In the first step, we could get LPG's physical and chemical explosion properties by calculation using TNT equivalency method. And then, by applying TNT equivalency value about the explosion limit concentration of LPG on the 2D-AUTODYN simulation, we could get the explosion pressure wave profiles (explosion pressure, explosion velocity, etc.). In the last step, we performed LPG explosion simulation by applying to the explosion pressure wave profiles as the input data on the 3D-AUTODYN simulation. As a result, we had performed analyzing of the explosion characteristics of LPG in accordance with concentration through the 3D-AUTODYN simulation in terms of the explosion pressure behavior and structure destruction and damage behavior. The analyses showed that the generated stresses of the structures were lower than the compressive strengths in cases 1(two lane) and 2(four lane), while the generated stress in case 3(six lane) was 8.68e3 kPa, which exceeded the compressive strength of 5.89e3 kPa.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1101-1108
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• 2012

In this paper, we proposed an algorithm for real-time lane detecting against luminance variation using morphological image processing and edge-based region segmentation. In order to apply the most appropriate threshold value, the adaptive threshold was used in every frame, and perspective transform was applied to correct image distortion. After that, we designated ROI for detecting the only lane and established standard to limit region of ROI. We compared performance about the accuracy and speed when we used morphological method and do not used. Experimental result showed that the proposed algorithm improved the accuracy to 98.8% of detection rate and speed of 36.72ms per frame with the morphological method.

• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.7-18
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• 2004

To solve the urban traffic congestion problem, Seoul and other major cities have operated the reversible lanes as Transportation Systems Manage-ment(TSM) method since 1981. However, few studies have been conducted to measure the effectiveness of reversible lane implementation and operation, and the reversible lanes have been implemented based on the experiential warrants rather than the study-based warrants. In this Paper the effect of reversible lanes operation has been analyzed by using the average delay and the fuel consumption. Four factors such as in and out flow of directional v/c, the ratio of directional volume, the number of reversible lanes and left-turn treatment(prohibition of LTs or protected LTs) were used to estimate the implementation effect of reversible lane operation by using TRANSYT-7F simulation package. In the case of six-lane urban arterial, the lower ratio of directional volume was found to warrant the reversible lanes when the simulation-based method was applied compared with the current experiential warrants.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.31-39
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• 2010

The paper proposes the median filter based Retinex algorithm to detect the lanes in a foggy image. Whether an input image is foggy or not is determined by analyzing the histogram in the pre-defined ROI(Region of Interest). If the image is determined as a foggy one, then it is improved by the median filter based Retinex algorithm. By replacing the Gaussian filter by the median filter in the Retinex algorithm, the processing time can be reduced and the lane features can be detected more robustly. Once the enhanced image is acquired, the binarization based on multi-threshold and the labeling operations are applied. Finally, it detects the lane information using the size and direction parameters of the detected lane features. The proposed algorithm has been evaluated by using various foggy images collected on different road conditions to prove that it detects lanes more robustly in most cases than the conventional methods.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1171-1181
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• 2018

Most simulated shooting systems are TDM based method and dot type laser has been used. The proposed laser pattern based simulated shooting system is a new approach. It can distinguish shooters by calculating the angle of bar shaped laser pattern by each shooter. Unlike the existing TDM method, it is possible to distinguish shooters and lanes by patterns so that there is no time division restriction like TDM method. It is also possible to recognize overlapped impact points of laser patterns launched by multiple shooters. After the laser pattern based simulated shooting system was implemented, general shot and overlapped shot were tested for each lane. Through experiments, we confirmed the possibility of continuous shooting. In addition, it is possible to separate the pattern by each lane, and 100% recognition result was obtained even if impact points overlapped.