• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1234-1239
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• 2006

신속하고 정확한 교통정보 서비스의 제공은 원활한 교통소통을 위하여 필수적인 요소이다. 특히, 교통사고, 도로보수 그리고 자연재해와 같은 유고가 발생할 경우, 운전자에게 즉시 통보해주어 우회할 수 있도록 조치하는 것이 필요하다. 이를 위하여 다양한 교통정보 수집기에서 수집된 교통정보를 바탕으로 실시간으로 유고상황을 판별하는 연구가 많이 진행되고 있다. 유고상황 분석은 다양한 환경요인으로 인해 판별이 어렵고, 최근에 활용되고 있는 인공지능 기법은 검지에 드는 시간 비용이 많다는 문제를 가지고 있다. 본 연구에서는 과거에 발생한 각종 돌발 상황을 분석하여 실시간으로 유고상황을 검지하는 것이 목적이다. 유고검지를 위해 GPS를 탑재한 probe car에서 수집된 차량속도와 온라인으로 제보된 유고정보를 ANFIS를 이용하여 분석 후 유고상태를 판별한다. 본 연구를 통해 실시간 도로 이용자들이 유고 발생 지역의 정보를 제공받고 그 상황에 신속하게 대처하게 함으로써 교통 혼잡 완화에 기여할 것으로 기대한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.623-631
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• 2011

In this study, a new method which can detect incidents in interrupted traffic flow was suggested. The applied method of detecting the incident is the Latin Square Analysis Method by using traffic traits. In the Latin Square Analysis, unlike other previously tried methods, the traffic situation was analyzed, this time considering the changes in traffic traits for each lane and for each time period. The data used in this study were the data observed in the actual field with fine weather. The traffic volumes, the vehicle speed and the occupancy rate were collected on the interrupted flow road. The data were collected in normal and incident situations. The incidents occurred on the second lane, the time of persistent incidents was set to 10 minutes. The Latin Square Analyses were performed using the collected data with the traffic volume, with the vehicle speed or with the occupancy rate. As a result in this study, in case of detecting the traffic situations with Latin Square Analysis, it will be more successful to apply traffic volume to detect the traffic situations than to apply other factors.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.425-428
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• 2012

본 논문에서는 터널 내 유고 상황을 실시간으로 빠르게 감지하여 터널 관리자에게 상황을 전달하여 터널의 안전한 운영에 도움을 줄 수 있는 컴퓨터 비전을 이용한 터널 유고감지 시스템을 제안하였다. 제안한 시스템은 관리자, 서버, 영상 검지기로 구성되며 영상 검지기의 경우 객체를 추출하기 위하여 배경차이법을 사용하였으며, 터널 내에서 발생하는 조명의 변화, 입 출입구의 조명의 영향, 카메라의 프리컬링 잡음의 영향을 최소화하였으며, 터널 내에서 발생할 수 있는 정지물체, 차량 외 통행, 연기, 역주행, 정체 지체의 유고 상황을 감지하는 방법을 개발하였다. 제안한 시스템을 전남 여수의 마래터널 및 엑스포터널, 전북 임실의 운암터널에서 실험한 결과 터널 내에서 발생하는 유고 상황을 감지하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.9-18
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• 2010

Our country has so large mountain area that the tunnel construction is inevitable and the need of incident detection that provides safe management of tunnels is increasing. In this paper, we suggest a tunnel incident detection system using computer vision techniques, which can detect the incidents in a tunnel and provides the information to the tunnel administrative office in order to help safe tunnel operation. The suggested system enhances the processing speed by using simple processing algorithm such as image subtraction, and ensures the accuracy of the system by focused on the incident detection itself rather than its classification. The system is also cost effective because the video data from 4 cameras can be simultaneously analyzed in a single PC-based system. Our system can be easily extended because the PC-based analyzer can be increased according to the number of cameras in a tunnel. Also our web-based structure is useful to connect the other remotely located tunnel incident systems to obtain interoperability between tunnels. Through the experiments the system has successfully detected the incidents in real time including dropped luggage, stoped car, traffic congestion, man walker or bicycle, smoke or fire, reverse driving, etc.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.341-344
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• 2006

유고란 도로상에서 교통량의 주기적인 집중에 의한 혼잡과는 구별되는 개념으로 교통사고, 도로보수 그리고 자연재해와 같은 비 반복적인 정체의 상황을 일컫는다. 이러한 유고는 막대한 통행시간이 추가로 발생하고 연료소모, 환경피해 등의 문제가 발생하므로 이러한 교통손실을 최소화하기 위하여 자동유고감지 알고리즘의 개발이 필수적이다. 이를 위하여 현재 다양한 검지기에서 수집된 교통 데이터를 바탕으로 유고를 감지하는 연구가 많이 진행되고 있다. 본 논문에서는 각종 유고 상황을 인지하여 제2의 사고를 예방할 수 있는 효율적인 유고감지 알고리즘을 개발하기 위하여 퍼지논리와 패턴을 함께 사용하였다. 먼저 퍼지논리와 패턴에 사용되는 데이터는 루프 검지기에서 5분 마다 수집된 교통정보(교통량, 점유율, 속도)를 이용하였다. 교통정보를 이용하여 구축된 요일 및 시간대별 패턴과 함께 퍼지논리를 이용하여 도출된 유고 소속도를 가지고 유고를 감지하였다.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2010.10a
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• pp.155-158
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• 2010

본 연구에서는 최근 도심지 대심도 지하도로 및 침매터널등에서 중요성이 부각되고 있는 터널내 화재안전 설계를 위한 영상유고감지시스템의 성능평가를 수행하였다. 영상유고감지시스템(VIDS)의 성능 평가를 위하여 터널 내부에서 발생할 수 있는 유고상황을 5가지로 구분하여 보행자, 낙하물, 정지차량, 역주행, 연기발생등의 상황을 인위적으로 발생시켰으며 이에 따른 감지 능력을 평가하였다. 실험결과 2, 3회 걸친 지속적인 교정과 세부조정을 거친 후에는 보행자 98.3%, 낙하물 96.7%, 정지차량 100%, 역주행 100%, 연기감지 100%의 감지율을 나타내었으며 카메라의 설치거리 100m 이내에서 비교적 높은 감지율을 나타내었다. 영상유고감지기의 적용 신뢰도는 터널내 조도, 카메라의 설치 위치에 따른 영상 변화등에 의존적이었으나 대심도 터널등의 신속한 화재감지를 위한 대안으로 적용될 수 있을 것으로 판단되었다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.262-274
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• 2019

The purpose of this study is to estimate the minimum proportion of probe vehicles for obtaining expressway traffic information using VISSIM, a micro traffic simulation model, between Yongin IC and Yangji IC on Yeongdong Expressway. 7,200 scenarios were created for the experiment, and 40 scenarios were adopted using the Latin hypercube sampling method because it was difficult to perform all the scenarios through experiments. The reliability of the experiment was improved by adding a situation when the general situation and the accident situation exist. In the experiments, the average travel time of probe vehicles at different market penetration rates were compared with the average travel time of the entire vehicles. As a result, the minimum market penetration rate of probe vehicles for obtaining expressway traffic information was found to be 45%. In addition, it is estimated that 25% market penetration rate of probe vehicle can meet 70% of traffic situations in accident scenario.

• Journal of Urban Science
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• v.10 no.1
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• pp.49-60
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• 2021

The purpose of this study is to analysis the impact on the inside of the new city when an incidents occurs on the Songdo International City connecting road, which has a limited access. The analysis data used KTDB's O/D and network data of the Seoul metropolitan area. In addition, the scenario composition applied a method of reducing the number of lanes on the road according to the situation of incidents, targeting bridges advancing from Songdo International City to the outside in the morning peak hours. The analysis method analyzed the traffic volume, total travel time, total travel kilometer, and route change in the new city based on the results of the traffic allocation model. As a result of the analysis, the range of influence was shown to two types. First, of the seven bridges, Aam 3, Aam 2, and Aam 1 were analyzed to have an impact only in some areas of the northwestern part of the new city. On the other hand, the remaining bridges were analyzed to affect the new city as a whole. The analysis results of this study are expected to be used as basic data to establish the scope of internal road network management when similar cases occur in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.