• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.125-138
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• 2011

The highway visibility reduction caused by fog is one of the major elements of traffic accidents. Though the fog warning systems can lead drivers into safe driving by letting them aware dangerous situations in advance, the optical sensors, such as fog sensor, has been extremely costly. Through recent studies, it is delivered that visibility measurements have become obtainable with relatively cheap cameras and their functionality is as similar as a driver' visual sense. Those measurements however require additional signs or ROI, so it is still costly and unable to utilize the conventional images from the existing systems. This study proposes a new method to detect the visibility in real time based on the conventional images from the existing CCTV cameras. The proposed method builds a road model and extracts and applies vehicle movements and visible lines - those highlight easy and quick visibility measurements. The proposed method has advantages of both (1) having possible day and night visibility measurements similar to drivers' visual sense and (2) being easily applied to the existing CCTV system without additional devices. This paper presents field experiments using images acquired from the Central Inland Expressway and discusses future research directions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.385-392
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• 2013

A key element of the fog warning system to prevent large traffic accidents is a visibility measurement device. Recently, the need for it that is similar to the human visual sense and cheap and accurate than expensive fog sensors is increasing. In this paper, we present the performance evaluation and the economic analysis of the Road Visibility Measurement System (RVMS), which is developed for measuring the road visibility through a CCTV camera. For experiments, we have installed a CCTV camera, a fog sensor, and visibility signs at the Yeo-ju Test Road on the Central Inland Expressway. We evaluated the measurements from RVMS and the fog sensor based on observations. The result shows RVMS outperforms the fog sensor with respect to measurement stability and correctness. We also show RVMS has higher economic feasibility and various applications. RVMS can prevent the traffic accidents caused by severe fog and enhance the process of the wide-area visibility information system significantly.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.295-300
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• 2012

Various forward collision warning algorithms have studied in order to protect a car accident. For this, in general, algorithms using an external device such as a camera and sensor generate a forward collision warning. However, if using the external device, it can occur errors due to device characteristics when there is rain or fog. Also, the prevention of a chain-reaction collision is insufficient because the system generates a warning in case of only vehicle having a forward collision danger. If it combines the vehicle safety communications, the method becomes a solution to protect a chain-reaction collision. So, In this paper, we proposes a improved forward collision warning algorithm using the wireless communication technique, driver's information, breaking distance, and velocity. And we compare and analyze our algorithm and previous algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.6
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• pp.665-671
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• 2014

Recent researches show that the traffic fatality rate in fog is higher than that in rain and snow. In that sense, methods to measure visibility accurately and to notify the measured visibility information to drivers are required. We thus developed a system for measuring the road visibility in realtime by employing CCTV cameras. In this paper, we also propose a wide-area visibility information system through measuring the visibility of every highway by using the developed system. The proposed wide-area visibility information system uses the video clips from the CCTV camera instead of the output from the expensive fog sensor. Hence, we expect that it can reduce the cost of installation and operation dramatically and the measured visibility information has a number of applications.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.709-712
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• 2009

대부분의 고속도로 안개경고시스템은 시정측정을 위해 고가의 광학센서를 사용하고 있으나 운전자의 시정감각과 유사하면서도 비교적 저가인 CCTV를 이용한 시정측정에 관한 연구가 활발히 이루어지고 있다. 그러나 대부분의 CCTV를 이용한 시정측정 방법은 ROI를 기반으로 하고 있어 설치가 까다롭고 기존 CCTV를 활용하기 어렵다는 문제점을 가지고 있다. 본 논문에서는 고속도로상의 안개경고는 약 1~2Km이내의 시정일 때 발생되며, 눈으로 물체를 식별할 수 있는 최대거리가 시정이라는 기초적인 개념에 근거하여 고속도로 안개경고시스템에 사용될 수 있는 Non-ROI 기반의 실시간 CCTV 시정측정 방법을 제안한다. 이를 위해 본 논문에서는 고속도로상에 주행중인 차량의 실시간 이동영역과 가시선을 검출하고 카메라와 도로간의 상관관계를 나타내는 도로모델을 이용하여 시정측정을 수행하는 방법을 제시한다. 제안된 방법은 1~2Km 이내의 시정측정을 위한 방법으로 ROI가 필요없고 직관적이고 현실적인 주야간 시정측정이 가능하며 기존의 고속도로 CCTV에 바로 적용할 수 있다는 장점이 있다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.1
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• pp.18-28
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• 2008

The purpose of this study is leading to prevent the major causes of commercial-aviation fatalities about controlled-flight-into-terrain(CFIT) in approach-and-landing accidents. The paper of major analysis for controlled flight into terrain(CFIT) was Guam accident, Mokpo accident and Gimhae accident in commercial transport-aircraft accidents from 1993 through 2002. CFIT occurs when an airworthy aircraft under the control of the flight crew is flown unintentionally into terrain, obstacles or water, usually with no prior awareness by the crew. This type of accident can occur during most phases of flight, but CFIT is more common during the approach-and-landing phase. Ninety-five percent of the Guam accident, Mokpo accident, and Gimhae accident where weather was known involved IMC, fog, and rain. The paper believed that prevention for CFIT accident was education and training for flying crew and upgrade for equipment such as EGPWS, and need more research for professional organizations of airlines, and accomplishing precision approaches should be a high priority.

• Journal of the Society of Disaster Information
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• v.10 no.1
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• pp.105-115
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• 2014

In this research, we developed video analytic algorithms to detect water-level automatically and a system for proactive alarming using intelligent CCTV cameras. We applied these algorithms and a system to test-beds and verified for practical use. We made camera-selection policies and operation plans to keep the detection accuracy high and to optimize the suitability for the ever-changing weather condition, while the environmental factors such as camera shaking and weather condition can affect to detection accuracy. The estimation result of algorithms showed 90% detection accuracy for all CCTV camera types. For water level detection, NIR camera performed great. NIR camera performed over 95% accuracy in day or night, suitable in natural weather condition such as shaking condition, fog, and low light, needs similar installment skills with common cameras, and spends only 15% high cost. As a result, we practically tested water level detection algorithms and operation system based on intelligent CCTV camera. Furthermore, we expect the positive evidences when it is applied for public use.