• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.21-29
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• 2015

The purpose of this paper was to investigate various factors influencing the intentions of drink-driving from multiple perspectives, in order to uncover ways to reduce the number of motor accidents caused by drink-driving. We examined sociopsychological aspects as well as driver's life styles such as smoking habit and exercise habit. Perception of behaviour controls among drink-driver' sociopsychological characteristics had the highest influence on the intentions of drink-driving, followed by influence of smoking and exercise on the intentions of drink-driving. This finding indicates that driver' life style such as smoking habit or exercise habit influences more on the intentions of drink-driving than attitude toward drink-driving or subjective regulations, which affirms that driver' life style such as smoking habit or exercise habit has significant effects on the intentions of drink-driving. Therefore, it is concluded that rehabilitative curriculum for drink-drivers should include a program to diminish drink-driving through nonsmoking and exercise habit.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06b
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• pp.455-459
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• 2010

본 논문에서는 운전자의 운전 패턴에 따른 연료 소비량을 감소하는 ECO_Driving에서 효율적으로 방법을 제안하였다. 이 ECO-Driving 시스템은 차량의 정확한 상태 정보를 바탕으로 운전 상태를 운전자에게 제공하여 경제운전 행동으로 배기가스 감축, 에너지절약을 유도하였다. 차량의 상태정보를 추출하기 위해서 차량 네트워크인 CAN 버스를 사용하였으며, 이를 하드웨어로 구현하였다. 효율적인 ECO_Driving을 위한 차량 데이터들을 추출하여 분석하였으며, 이들 데이터를 바탕으로 운전자에게 에코여부를 제공하는 프로그램을 구현하였다. 제한적인 실험이었지만 연비를 감소하는 것을 확인할 수 있었다.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.747-752
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• 1997

고리 3,4호기 및 영광 1,2호기 PSA Ⅰ단계 수행 결과 ATWT에 대한 노심 손상 확률은 다른 사건에 비해 상대적으로 적어 소홀히 취급될 수 있으나 전체적인 노심 손상 확률 저감을 위해 본 연구에서는 ATWT 사건 중 터빈 정지시 원자로 정지불능을 선정하여 HRA를 수행하였다. HRA 수행의 첫째 과정은 위에서 선정한 사건에 대해 시나리오를 가정하고 이를 4개 그룹의 주제어실 운전원들에게 적용하여 모의 제어반을 이용한 훈련을 실시하였으며 운전원 조치 과정중의 행동관찰, 훈련결과, 개별 면담 등을 통해 국내 운전원 특성에 맞는 HRA의 기초자료를 얻었다. 두 번째 과정은 위의 결과 및 절차서에 근거하여 PSF 고려 유무에 따라 실패 확률의 정량적 평가와 불확실성 분석을 수행하여 ATWT에 대한 HRA 수행 자료로 활용 가능하도록 하였으며, 끝으로 ATWT 영향 완화를 위한 대안을 제시함으로서 노심 손상 확률을 감소시키기 위한 기초가 되도록 하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.120-131
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• 2017

Recent studies have suggested that providing in-vehicle feedback on various driving behaviors promote eco-friendly driving behaviors. However, there was relatively little interest in cognitive overload that can be caused by the provision of information. Thus, the goal of this study was to investigate the relative effects of two types of feedback(visual feedback vs. visual-auditory feedback) to increase eco-driving performance while minimizing driving workload. Also, in this study, the complexity of the driving task was distinguished (secondary vs. tertiary task) in order to reflect the actual driving situation. The study adopted a counterbalancing design in which the two feedback types were delivered in a different order under the two different task conditions. Results showed that providing the visual-auditory feedback was more effective than the visual only feedback in both promoting eco-friendly driving behaviors and minimizing driving workload under both task conditions.

• Journal of the Korea Computer Graphics Society
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• v.3 no.1
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• pp.37-47
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• 1997

This paper presents the algorithms for generating ambient traffic in driving simulation. Each ambient car is modeled as an autonomous agent that obeys the traffic rules by sensing the traffic lights, road signs, lanes, and other cars around. The algorithm is localized to the area where the car driven by the participant is currently located. Therefore the complexity of the algorithm does not depend on the size of the road network, allowing a huge environment to be simulated with no extra overhead. To avoid monotony, we produce artificial fluctuations in the behavior by employing various forms of probability distribution functions. The resulting behavior of the ambient cars is quite realistic. Experiments indicate that it is hard to tell whether an ambient car is computer-controlled or human-controlled.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.330-332
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• 2017

최근 차량사고는 운전자의 운전 행동이 많은 비중을 차지하며 행동이 올바르지 못했을 경우 주의가 분산되어 사고가 발생하고 있다. 자동차 업계에서는 자율주행 기술의 출현으로 운전자의 운전환경이 변화되고 있다. 차량 서비스들은 차량에 부착된 센서들을 이용한 다양한 차량 서비스가 개발되고 있으며 차량 서비스는 도로주변 환경과 운전자의 안전에 집중된 서비스가 대부분이다. 하지만 차량에 부착된 센서들의 성능문제로 인한 기능적 문제점으로 상용화가 늦어지고 있다. 본 논문에서는 사용자에게 효율적인 차량 서비스를 제공하기 위해 사용자의 음성을 활용한 상품구매 시스템을 제안한다. 본 시스템은 딥 러닝 기술이 적용된 DB를 통해 사용자의 음성데이터 분류를 통해 상품을 검색 및 구매할 수 있는 시스템이다. 제안된 시스템은 음성인식을 활용하여 별도의 과정 없이 간편하게 상품을 구매할 수 있으며, 사고의 위험으로부터 벗어날 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.1090-1093
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• 2020

운전자가 아닌 자율주행 시스템이 운전을 주도하기 위한 기술의 상용화를 위해 많은 기업이 노력 중이다. 특히 운전자의 안전을 보장하기 위한 운전자와 자율주행 시스템 간의 제어권전환이 중요하다. 운전자의 주행과 관련 없는 행동은 제어권전환 상황에서 운전자를 위험에 빠뜨릴 수 있으므로 제어권전환을 돕기 위한 운전자 모니터링 기술에 관한 많은 연구가 진행되고 있다. 운전자 모니터링 기술은 주로 생체 정보, 차량 정보, 영상을 사용하여 운전자의 상태와 부주의 행동 등을 감지하는 기술이다. 최근 머신 러닝, 딥 러닝을 사용한 영상처리 및 인식 기술 등의 발전으로 영상을 사용한 운전자 모니터링 기술이 활발하게 연구되고 있다. 따라서 본 논문에서는 영상기반 운전자 모니터링 기술 동향에 대해 상세히 기술하였다. 특히 운전자의 부주의 행동 중 졸음은 운전자가 주행 상황을 전혀 인지하지 못하게 할 수 있어 더욱 위험한 행동이다. 따라서 영상기반 운전자 모니터링 기술을 졸음 인식과 그 외의 행동 인식으로 분류하여 동향을 정리하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.49-59
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• 2012

Recently, various alternatives for safety and efficiency of commercial vehicles have been considered, and one of the new alternatives is the application of a digital tachograph. In Korea, the installation of a digital tachograph to commercial vehicles was regulated from 2011 and Korea Transportation Safety Authority developed e-TAS to analyze the monitoring data from digital tachographs installed in the order of 100 commercial vehicles. This study performs the potential impact analysis of the DTG installation, which includes a trend of dangerous driving, a trend of traffic accidents and cost-effective analysis, a trend of fuel consumption and cost-effective analysis, a cost-effective analysis of social benefits using e-TAS data. Depending on the frequency of dangerous driving, the participants are divided into three groups; high-dangerous group, average-dangerous group and low-dangerous group. The high-dangerous driving group shows lower km/liter than the low-dangerous driving group by 15% for buses and taxis and by 30% for trucks. About $CO_2$ emission, the difference becomes bigger; 25%, 25% and 42% for buses, taxis and trucks, respectively. Although this study is a short-term period analysis, the methodology will be applicable for the long-term period analysis with larger data.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.9-20
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• 2009

Navigation system providing route-guidance and traffic information is one of the most widely used driver-support system these days. Most of the navigation system is based on the 2D map paradigm so the information is ed and encoded from the real world. As a result it imposes a cognitive burden to the driver to interpret and translate the ed information to real world information. As a new concept of navigation system, augmented-reality navigation system (AR navigation) is suggested recently. It provides navigational guidance by imposing graphical information on real image captured by camera mounted on a vehicle in real-time. The ultimate goal of navigation system is to assist the driving task with least driving workload whether it is based on the abstracted graphic paradigm or realistic image paradigm. In this paper, we describe the comparative studies on how map navigation and AR navigation affect for driving tasks by experimental research. From the result of this research we obtained a basic knowledge about the two paradigms of navigation systems. On the basis of this knowledge, we are going to find the optimal design of navigation system supporting driving task most effectively, by analyzing characteristics of driving tasks and navigational information from the human-vehicle interface point of view.