• International Journal of Railway
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• v.3 no.3
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• pp.106-112
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• 2010

Accidents at level crossing have large portion on train accidents, and causes economical loss by train delay and operational interruption. Various safety equipments are employed to reduce the accident at level crossing, but existing warning device, and crossing barrier are simple train-oriented protection equipments. In this paper, intelligent railway level crossing system is proposed to prevent and reduce accidents. For train driver's prompt action, image of level crossing and obstacle warning message are continuously provided to train driver through wireless communication in level crossing control zone. Obstacle warning messages, which are extracted by computer vision processing of captured image at level crossing, are recognized by train driver through message color, flickering and warning sound. It helps train driver to decide how to take an action. Meanwhile, for vehicle driver's attention, location and speed of approaching train are given to roadside equipments. We identified the effect of proposed system through test installation at Sea train and Airport level crossing of Yeong-dong line.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1732-1750
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• 2010

Operation of KORAIL's level crossing is in charge of KORAIL. As taking over existing level crossing to KORAIL, they do not conduct risk assessments, so we do not know about any possibilities of inner risk. And present operation of safety of the level crossing is just regular checking of reaction and functions of safety equipments physically, we need to react to the changes of what's going on around of level crossing and incestigation of traffic flow and surrounding conditions more spontaneously. So, we have to prepare the strategies against accidents of level crossing cost-effectively based on regular risk assessments for sustainable safety improvements and overcome operational problems of present level crossing's safety. Here, we're going to investigate the level of safety level and present risk factors of the level crossing using risk assessments for accidents/error of the equipments to show operational strategies of level crossing based on risk assessments.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1025-1026
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• 2008

The level crossing collision accident which comprises more than 90 percent of all level crossing accidents is one of the most serious safety problems. There is a critical need for providing safe strategy and is focusing on the level crossing information rather than measures at a grade crossing. This study is intended to develop technology for accident prevention and damage reduction based on accident cases analysis result and improvement direction to complement shortcomings of safety equipment of conventional level crossing and to establish safety of travelers(train, motor vehicle, person).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2220-2227
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• 2008

The safety equipments of railway level crossing which are installed at intersections between roads and railway lines prevent level crossing accidents by informing all of the vehicles and pedestrians of approaching trains. The intelligent safety system for level crossing which employs information and communication technology has been developed in USA and Japan, etc. But, in Korea, the relevant research has not been performed. In this paper, we analyze the cause of railway level crossing accidents and the inherent problem of the existing safety equipments. Based on analyzed results, we design the intelligent safety system which prevent collision between a train and a vehicle. This system displays train approaching information in real-time at roadside warning devices, informs approaching train of the detected obstacle in crossing areas, and is interconnected with traffic signal to empty the crossing area before train comes. Especially, we present the video based obstacle detection algorithm and verify its performance with prototype H/W since the abrupt obstacles in crossing areas are the main cause of level crossing accidents. We identify that the presented scheme detects both pedestrian and vehicle with good performance.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.286-288
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• 2003

Accidents at level crossing where railways and roads cross cause many casualties because of collision of cars etc and it also has a risk of the 2nd accident of trains. it is the most vulnerable point in the railway safety. Fundamental solution for accidents at level crossing is making the crossings cubic. but it can't be easily progressed because of environmental and financial difficulties. every kind of anti-accident measures are being strived for. one of the strived results is level crossing obstacle detector which automatically detects obstacles like defected cars etc in the middle of level crossing and transmits the information of obstacles to the approaching train. However present level crossing obstacle auto detector needs high expenses to be installed and has difficulties that lenses of beam transmitter, beam receiver should be cleaned in snowing winter. this document reviews level crossing obstacle auto detector using ultrasonic sensor to measure these difficulties.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1112-1117
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• 2010

The intelligent safety system for level crossing which employs information and communication technology has been developed in USA and Japan, etc. But, in Korea, the relevant research has not been performed. In this paper, we analyze the cause of railway level crossing accidents and the inherent problem of the existing safety equipments. Based on analyzed results, we design the intelligent safety system which prevent collision between a train and a vehicle. This system displays train approaching information in real-time at roadside warning devices, informs approaching train of the detected obstacle in crossing areas, and is interconnected with traffic signal to empty the crossing area before train comes. Especially, we present the video based obstacle detection algorithm and verify its performance with prototype H/W since the abrupt obstacles in crossing areas are the main cause of level crossing accidents. We identify that the presented scheme detects both pedestrian and vehicle with good performance. Currently, we demonstrate developed railway crossing intelligence system at one crossing of Young-dong-seon line of Korail with Sea Train cockpit.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1813-1819
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• 2013

Existing level crossing obstacle detecting system was installed using a laser beam. Level crossing obstacle detecting system using a laser beam that has been a problem in relation to safety and maintainability failure according to weather conditions. We proposed laser radar level crossing obstacle detecting system as a way to overcome problem, and we developed an algorithm for this. Level crossing obstacle detecting system using a laser radar sensor algorithm is robust to external environment and a shadow zone does not exist. Sensor part of the laser radar level crossing obstacle detecting system of these is made up by the image processing unit and laser radar sensor, it operations by receiving train entering information from the control unit. In this paper, we proposed a detecting algorithm with calculation of the size of the laser radar sensor. Based on this, we were performance test on the basis of the scenario by making a prototype. In the future, laser radar level crossing obstacle detecting system to ensure the safety and reliability through the field test.

• Journal of the Korean Society of Safety
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• v.29 no.2
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• pp.76-81
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• 2014

Railroad traffic accident consists of train accident, level-crossing accident, traffic death and injury accident caused by train or vehicle, and it is showing a continuous downward trend over a long period of time. As a result of the frequency comparison of train accidents and level-crossing accidents using the railway accident statistics data of Railway Industry Information Center, the share of train accident is over 90% in the 1990s and 80% in the 2000s more than the one of level-crossing accidents. In this study, we investigated time series characteristic and short-term prediction of railroad crossing, as well as seasonal characteristic. The analysis data has been accumulated over the past 20 years by using the frequency data of level-crossing accident, and was used as a frequency data per month and year. As a result of the analysis, the frequency of accident has the characteristics of the seasonal occurrence, and it doesn't show the significant decreasing trend in a short-term.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.175-177
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• 2008

The level crossing collision accident which comprises more than 90 percent of all level crossing accidents is one of the most serious safety problems. There is a critical need for providing safe strategy and is focusing on the level crossing information rather than measures at a grade crossing. This study is intended to develop technology for accident prevention and damage reduction based on accident cases analysis result and improvement direction to complement shortcomings of safety equipment of conventional level crossing and to establish safety of travelers(train, motor vehicle, person).

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.225-227
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• 1995

An object detection algorithm using a modified IDM(Image Differential Method) is proposed for detecting an object in a level crossing area. The conventional object detection method using LASER light has the deadzone that it cannot detect small objects, while the object detection method using image data in a level crossing area can detect such small objects. But the image data in a level crossing area can be changeable easily because the data is outdoor and sensitive to such surrounding environments as the change of the sun beam, the shadow of cars, and so on. So we resolve these problems by adding the normalization and the process for shadow of the image data in a level crossing area to the basic IDM(Image Differential Method).