• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.581-586
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• 2006

Incidents, which is unexpected unusual events such as traffic accidents, have increased on the most roads in Korea. The obstruction of a fluent traffic flow occurred by incidents causes the traffic congestion and decreases the capacity. The Wavelet technique was applied to detect the road section and the happening time of incidents on urban freeways in this study, and this technique has been widely used in many engineering fields such as an electrical engineering, etc. The availability and validity of the Wavelet technique to the detection of incidents was examined by the occupancy rate, the important element of traffic flows, which is extracted from the data of detectors installed on Seoul Urban freeways. Then, this result is compared to the California Algorithm and the Low-Pass Filtering Algorithm among basic present detection algorithms, which are based on the occupancy rate. As a result, the false alarm rate of this method was similar as that of the California algorithm and the Low-Pass Filtering algorithm, but the detection rate is higher.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.36-44
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• 2009

In this paper, we suggest a system of detecting a vehicle with lane violation, which can detect the vehicle with lane violation, by using the feature point tracking. The whole algorithm in the suggested system of detecting a vehicle with lane violation is composed of three stages such as feature extraction, register and tracking in feature for the tracking-targeted vehicle, and detecting a vehicle with lane violation. In the stage of feature extraction, the feature is extracted from the inputted image by sing the feature-extraction algorithm available for the real-time processing. The extracted features are again selected the racking-targeted feature. The registered feature is tracked by using NCC(normalized cross correlation). Finally, whether or not lane violation is finally detected by using information on the tracked features. As a result of experimenting the suggested system by using the acquired image in the section with a ban on intervention, the excellent performance was shown with 99.09% for positive recognition ratio and 0.9% for error ratio. The fast processing speed could be obtained in 34.48 frames per second available for real-time processing.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.77-88
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• 2004

This study aims at developing the model that is able to detect the compression wave, which is included as a similar situation in incidents, that causes false applicable to the similar character such as incidents in the incident detection model for expressways. In this study, it has been checked whether the number of false alarms is decreased or not by modularizing this model for being able to applicable to other models such as DES and DELOS, etc. which do not perform the compression wave test based on the compression wave test process of APID model which has been being used in the expressway traffic management system currently. The evaluation in this study focuses on the sensitivity of the model and the results analysis is performed classified by each polling cycle. And how well these models are working is evaluated by each polling cycle. In addition to this, the detection rate, the false alarm rate and the average detection time in both the existing models and the model in this study are calcuated. As a result of appling the model in this study, it is found that the false alarm rate is improved through the reasonable decrease in the number of false alarm frequencies and there are not remarkable changes concerning the detection rate and the average detection time. To sum up, it is expected that a good number of improvement effects will be occurred when this model is applied to the actual expressway traffic management system.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.489-498
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• 2006

In this paper, we suggested a vehicle classification algorithm using pattern recognition method. At present, Inductive Loop Detector is rarely used for vehicle classification because of its low accuracy. To improve the accuracy, we suggest a new algorithm for Loop Detector using neural networks. In the developed algorithm, the inputs to the neural networks are the variation rate of frequency and occupancy-time. The output is classified vehicles. The developed algorithm was assessed at test sites and the recognition rate was 91.3percent. The results verified that the proposed algorithm improves the vehicle classification accuracy compared to the conventional method based on Loop Detector.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.79-90
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• 2007

In this paper we proposed and implemented an incident detection model which combines fuzzy algorithm and traffic pattern in order to enhance the efficiency of incident detection for the highways with lamps. Most of the existing algorithms dealt with highways without lamps and can not be used for detecting incidents in the highways with lamps. The data used for model building are traffic volume, occupancy, and speed data. They have been collected by a loop sensor at 5 minutes interval at a point in the Internal Circular Highway of Seoul for the period of 3 months. In this model, the three parameters collected by sensor were fuzzified and combined with the daily traffic pattern of the link. The test of efficiency of the propsed model was performed by comparing the result of proposed model with traditional APID algorithm and fuzzy algorithm without the pattern data respectively. The result showed significant amount of improvement in reducing the false incident detection rate by 18%.

• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.19-24
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• 2005

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.30 no.6
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• pp.55-64
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• 2001

전기적 스윗치 기능을 갖는 신기술의 개방검지형 자동스프링클러헤드의 구조, 원리 및 특성과 이를 설치하는 습식 스프링크러시스템의 구성방식 및 그 실효성에 대해 소개한다.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.604-605
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• 2010

산업이 고도화 됨에 따라 박막 코팅에 대한 수요가 점차 증가하고 있으며 이에 따라 플라즈마를 이용한 마그네트론 스퍼터 시스템에 대한 수요 역시 증가하고 있다. 코팅 공정에서 가장 문제가 되는 것은 고압의 플라즈마 발생장치를 사용함으로써 야기되는 아크현상이라 할 수 있다. 따라서, 플라즈마 전원 장치의 핵심 기능 중의 하나는 아크 차단 성능이라 할 수 있으며 가능한 한 최소의 아크 에너지를 유지할 필요가 있다. 아크를 억제하는 방법은 최단 기간 내에 아크를 검지하여 출력을 차단함으로써 아크 발생에 필요한 에너지의 유입을 감소시키는 방법이 사용되고 있다. 본 연구에서는 아크를 검지하는 기존의 방식을 살펴보고 최단기간에 아크를 검지할 수 있는 새로운 형태의 검지 방식을 제안한다.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.81-94
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• 2016

The Korean real-time traffic responsive control systems, Cycle Offset Split Model of Seoul (COSMOS), employs a single theoretical model to estimate the degree-of-saturation (DS) on approaches. However, the deployment of the system has been accomplished without practical consideration of its field performance. This paper delivers a diagnosis study performed to find the relationships yet known on the DS values against the operational conditions unproved in theory but ordinarily observed in field practice. Based on the analysis of the historical log data (476,505 cycles) obtained from the COSMOS server, it was found; (1) full coverage of lane detections should perform better than the sample coverage of detection in ordinary conditions, (2) the sample coverage of detection perform better than the other case with an exclusive bus lane, (3) detection in which a shared lane is involved provide poor estimation of DS, (4) poor DS estimation when a detection lane is adjacent to a shared lane, and (5) the DS values obtained during a day can hardly be stable all time. The findings suggest traffic engineers a progressive direction to move forward for the next real-time traffic control systems.