• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.177-185
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• 2005

The accuracy of a video image detector(VID) is gradually reduced due to the various environmental and mechanical factors. But there has been no systematic research about this VID accuracy decreasing. To maintain a proper level of VID accuracy for the advanced traffic management. a regular VID calibration process needs to be introduced. Because of its cost, however. the calibration cannot be performed frequently. Therefore, the method to decide the optimal calibration interval should be studied in details. This study presents two different calibration interval decision methods. Using the invented data collection equipment. some data in the field were collected and analyzed. which were used for the adaptability checking. Although the data were limited. the result is pretty promising. More data needs to be investigated later and this study will help to maintain the data quality of the ITS center.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.19-30
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• 2006

This study deals with the optimized detector location considering the traffic characteristics in National Highway. Although there ave many construction works for ITS in National Highway, there is not specific criteria for detector location which can effect the accuracy of traffic information. This study. therefore. aims to Provide the optimized detector location criteria which can represent the traffic characteristics of National Highway. It collects traffic factors of study area by GPS Probe-car and defector, and Presents the optimized detector location by the correlation analysis between spot-speed and link-travel-time. The main results of this study are as followings ; First, the correlation between the spot-speed and link-travel-time Presents the opposite bell shape of the graph (U-type owe) which is increased it?on the upstream then, declined through some unspecified Point of the link. Second, the optimized detector location usually distributes around midstream of link, even though it does not have a consistency. Third, therefore, the optimized detector location generally should be located between $55{\sim}60%$ of total link length. Forth. high level of vertical slope is one of the most important factors of detector location, so it should be excluded for determination of optimized detector location. Finally, expecting that the results of this study would improve the accuracy of travel time estimation and forecasting.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.146-157
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• 2016

The objective of this study is to actualize a statistical model of the 3-detector simplification model, which was proposed to detect outbreak situations by Daganzo in 1997 and to verify the statistical appropriacy thereof. This study presents the calculation process of the 3-detector simplification model and realizes the process using a statistics program. Firstly, the model was applied using data on detector of the main highways on which there is no entrances or exits. Moreover, in order to statistically verify the 3-detector simplification model, accumulative traffics for 30 seconds period, which reflects the dynamic changes of traffics due to shock wave, were estimated for outbreak traffics and steady flow, and the error of acquired data was statistically compared with that of the actual accumulative traffics. As a result, the error ratio between steady and incident cumulative flows has reached its maximum after 2-3 hours from an accident. Moreover, the incident traffic flows by accidents and the stade flows are heterogeneous in terms of their dispersion and means.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.103-108
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• 2008

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.198-201
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• 2004

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.119-129
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• 2004

This paper is designed to report the results of development and validation procedures in relation to the Freeway Incident Management System (FIMS) prototype development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but the integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Korean freeway system. After through review and analysis of vehicle detection data, the pilot site led to the utilization of different technologies in relation to the specific needs and character of the implementation. This meant that the existing system was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The system validation specifications have identified two component data collection and analysis patterns which were outlined in the validation specifications; the on-line and off-line testing procedural frameworks. The off-line testing was achieved using asynchronous analysis, commonly in conjunction with simulation of device input data to take full advantage of the opportunity to test and calibrate the incident detection algorithms focused on APID, DES, DELOS and McMaster. The simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.70-73
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• 2003

기존의 영상검지기는 한정된 구간에서 차량을 추출, 추적하는데 본 논문에서 제안한 카메라간 연계 추적 방법은 두 대의 카메라를 서로 연계하여 차량을 추적함으로써 넓은 구간에서도 효과적으로 차량을 추적할 수 있다. 한 대의 카메라는 전방을 검지하고 다른 카메라는 후방을 검지하여 전방 검지영역에서 추적한 차량을 후방 검지영역에서도 연계하여 추적하게 된다. 연계 추적을 위해 전방 카메라에서 취득한 차량의 차선정보와 차량의 대표 gray level 정보를 후방 카메라로부터의 영상 분석시 이용하여 차량 연계 추적을 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.367-374
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• 2006

This research revealed the operation problems of the current crossing control systems through inspecting and testing the obstacle detection systems and gate control systems for the crossings. To resolve the problems of the crossing control systems, this research developed new algorithms of four-quadrant gate system and obstacle detection systems combing the functions of rasar sensors and magnetic sensors and tested the reliability of the systems. Currently, the obstacle detection systems and gate control systems controls approaching and departing traffic by simply detecting vehicles and obstacles but do not consider traffic movements at the crossings. In addition, they do not make signal cooperation for gate controls. As a result, such inefficient crossing controls result in unsafe gate controls for drivers. Therefore, the newly developed crossing control systems through this study will provide more effective crossing control services with more strengthen information cooperation within control systems. Besides they will help to reduce train crashes at the crossings by gate control systems considering various driving behaviors.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.369-380
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• 1996

Inductive Loop Detector(ILD) has been commonly used in collecting traffic data such as occupancy time and non-occupancy time. From the data, the traffic volume and type of passing vehicle is calculated. To provide reliable data for traffic control and plan, accuracy is required in type recognition which can be utilized to determine split of traffic signal and to provide forecasting data of queue-length for over-saturation control. In this research, a new recognition model issuggested for recognizing typeof vehicle from thecollected data obtained through ILD systems. Two clustering methods, based on statistical algorithms, and one neural network clustering method were employed to test the reliability and occuracy for the methods. In a series of experiments, it was found that the new model can greatly enhance the reliability and accuracy of type recongition rate, much higher than conventional approa-ches. The model modifies the neural network clustering method and enhances the recongition accuracy by iteratively applying the algorithm until no more unclustered data remains.