• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.133-144
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• 2017

Recently, weather information is getting closer to our real life, and it is a very important factor especially in the transportation field. Although the damage caused by the abnormal climate changes around the world has been gradually increased and the correlation between the road risk and the possibility of traffic accidents is very high, the domestic research has been performed at the level of basic research. The Purpose of this study is to develop a risk map for the road hazard forecasting service of weather situation by linking real - time weather information and traffic information based on accident analysis data by weather factors. So, we have developed a collection and analysis about related data, processing, applying prediction models in various weather conditions and a method to provide the road hazard map for national highways and provincial roads on a web map. As a result, the road hazard map proposed in this study can be expected to be useful for road managers and users through online and mobile services in the future. In addition, information that can support safe autonomous driving by continuously archiving and providing a risk map database so as to anticipate and preemptively prepare for the risk due to meteorological factors in the autonomous driving vehicle, which is a key factor of the 4th Industrial Revolution, and this map can be expected to be fully utilized.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.141-146
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• 1999

본 연구는 평면곡선부의 차량속도변화와 교통사고에 대한 영향을 분석하기 위해 수행되었으며, 이를 위해 곡선반경별로 진입부 직선도로 - 곡선부 - 이탈부 직선도로로 구분하여 각 주행속도를 산정하였다. 본 연구에서는 선행차량에 의해 영향을 받지 않는 속도를 이용하여 평면곡선부 기하구조의 영향을 분석하였다. 이러한 곡선부의 주행 속도를 분석한 결과, 곡선반경별 최저속도와 그 속도가 나타나는 위치를 분석하였고, 해당 도로구간의 교통사고자료를 분석하여 평면곡선부의 차량주행속도변화와 교통사고 발생간의 관계를 규명하였다. 연구 결과는 다음과 같다. 첫째, 운전자들은 곡선시작지점에 도착하기 전에 충분히 속도를 줄이고, 곡선부에서 가장 낮은 속도가 나타나는 위치는 곡선시점의 후방에서 나타나고 이는 운전자의 시거에 의한 영향이다. 둘째, 곡선부에서의 속도변화폭이 클수록 사고위험성은 크고 실제 교통사고의 발생건수는 높다. 본 연구의 결과에 의해 도로 주행의 안전성을 고려한 평가지표를 개발할 수 있으며, 이에 의한 일관성 있는 도로설계를 유도할 수 있다.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.864-867
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• 2009

고속도로를 주행하는 차량에 작용하는 순간적인 강풍은 차량의 주행경로이탈, 차체의 수평회전 과다와 전도를 발생시키는 원인이 되며, 이로 인한 교통사고는 치명적인 대형사고로 이어질 가능성이 높다. 최근에 건설되거나 추진중인 고속도로는 고속운행에 필요한 도로선형을 확보하기 위해 계곡부를 통과하는 높은 위치에 교량을 건설하거나 산악터널을 내는 경우가 많으며, 지형적인 특성으로 발생하는 국지적인 강풍의 영향이 매우 크기 때문에 적극적인 강풍저감대책이 필요하다. 본 연구에서는 강풍 발생지역을 주행중인 차량의 안전성 및 쾌적성확보를 위하여 차량의 동역학적 거동을 규명하고 차종별 주행속도와 순간풍속의 상관관계를 정립하였다. 또한 차량사고의 영향인자별 분석을 통하여 기존에 제시된 연구결과와 기준안에 대한 고찰을 실시하였고, 강풍발생 지역을 통과하는 차량에 대한 규제와 운영방법에 대해 위험풍속을 정의하고 차량속도규제(안)을 제시하였다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.1
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• pp.11-22
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• 2018

The safety of tunnels is quantified by quantitative risk assessment when planning the disaster prevention facilities of railway tunnels, and it is decided whether they are appropriate. The purpose of this study is to estimate the probability of the train stopping in the tunnels at train fire, which has a significant effect on the results of quantitative risk assessment for tunnel fires. For this purpose, a model was developed to calculate the coasting distance of the train considering the coefficient of train running resistance. The probability of stopping in case of train fire in the tunnel is predicted by the Monte Carlo simulation method with the coasting distance and the emergency braking distance as parameters of the tunnel lengths and slopes, train initial driving speeds. The kinetic equations for predicting the coasting distance were analyzed by reflecting the coefficient train running resistance of KTX II. In the case of KTX II trains, the coasting distance is reduced as the slope increases in a tunnel with an upward slope, but it is possible to continue driving without stopping in a slope downward. The probability of the train stopping in the case of train fire in tunnel decreases as the train speed increases and the slope of the tunnel decreases. If human error is not taken into account, the probability that a high-speed train traveling at a speed of 250 km/h or above will stop in a tunnel due to a fire is 0% when the slope of the tunnel is 0.5% or less, and the probability of stopping increases rapidly as the tunnel slope increases and the tunnel length increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1693-1700
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• 2012

Recently, the warning system to aid drivers for safe driving is being developed. The system estimates the distance between the driver's car and the car before it and informs him of safety distance. In this paper, we designed and implemented the collision warning system which detects the car in front on the actual road situation and measures the distance between the cars in order to detect the risk situation for collision and inform the driver of the risk of collision. First of all, using the forward-looking camera, it extracts the interest area corresponding to the road and the cars from the image photographed from the road. From the interest area, it extracts the object of the car in front through the analysis on the critical value of the shadow of the car in front and then alerts the driver about the risk of collision by calculating the distance from the car in front. Based on the results of detecting driving cars and measuring the distance between cars, the collision warning system was designed and realized. According to the result of applying it in the actual road situation and testing it, it showed very high accuracy; thus, it has been verified that it can cope with safe driving.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.475-478
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• 2009

안개가 교통사고를 유발시키는 원인을 살펴보면 운전자의 시거와 밀접한 관련이 있다. 짙은 안개가 발생하게 되면 돌발상황이 발생하였을 때 도로를 주행하던 차량이 안전하게 정지하기 위해서 필요한 최소 정지거리가 증가하게 되나 안개로 인한 시정이 나빠지게 되어서 사고발생확률이 높은 것이다. 또한 안전한 시거가 확보되지 않기 때문에 단독사고 발생 후 뒤따르던 차량이 전방을 확인하지 못한 상황에서 연쇄 충돌하게 되어 사고가 대형화된다. 이에 본 연구에서는 IT기술인 RFID와 USN을 이용하여 안개로 인한 시정거리에 따라 도로에 있는 과속카메라가 도로주행 한계속도를 자기 스스로 판단하여 자동조절하게 만들고 변경된 한계속도를 그 도로를 이용하는 차량운전자 휴대폰에 문자로 전송해주고 도로전광판에서도 정확하게 주행속도정보를 볼 수 있게 한다. 그리하여 도로주행 한계속도를 어기는 차량에는 범칙금을 부과하게 만든다. 본 연구를 통해 안개에 대한 교통사고의 위험을 줄이고 사회적 경제적으로 이익이 되도록 하기위해 기상상태 변화에 따른 USN 기반의 도로주행 한계속도 지능적 조정 관리시스템을 제안하고자 한다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1896-1897
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• 2011

본 논문에서는 동적환경의 잠재적 위험 정의와 안전한 전역경로 계획 알고리즘을 제안 하였다. 대부분의 전역경로계획 연구는 시간과 거리의 비용을 최적화 시키는데 집중하고 있다. 하지만 동적환경으로 우리 주변에 많은 위험요소가 작용하고 있다. 본 논문에서 안전한 자율주행을 위한 경로계획방법으로 위험지역에 의해 정의 된 반발력과 S*알고리즘을 이용하여 안전하고 빠른 최적의 경로계획을 이루었다.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.85-95
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle accidents explains 3.5 percent of the total number of traffic accidents of the year. Compared to other types of vehicles commercial vehicles may provide more serious damages to both driver himself and passengers. Thus, they generate more serious social and economic problems. There have been various forms of systems such as a digital speedometer or a black box to meet the social requirement for reducing traffic accidents and improving safe driving. However, since the current systems are based on the data often accidents happened, there are lots of limitations to control drivers in real-time. Also, the current speedometers provide drivers with only speeds of vehicles and RPM information regardless of actual dangerous drive behaviors. Therefor, they lack of the effectiveness in terms of safety. In this research, real-time information systems for improving driver safety based on automatic risky driving behaviors, and thresholds to determine risky driving patterns were studied.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.361-369
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• 2019

With the commercialization of the ADAS functions, the need for the experience of the autonomous driving system is increasing, and the role of the artificial intelligence agent is attracting attention. This study is an autonomous driving experience experiment that verifies the effect of self-efficacy and agent embodiment. Through a simulator experiment, we measured the effect of existence of self-efficacy and agent embodiment on social presence, perceived risk, and perceived ease of use. Results show that self-efficacy had a positive effect on social presence and perceived risk, and agent embodiment negatively affected perceived ease of use. Based on the results of the study, we proposed guidelines for agent design that can increase the acceptance of the semi-autonomous driving system.