• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.61-74
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• 2005

This study is to investigate the effects of driving anger and traffic congestion on drivers' behaviors. Driving anger is the propensity to become angry while driving, and people differ in the tendency to get angry when encountering frustration and provocation on the road. Individual differences of the propensity contribute to anger on the road and aggressive driving leading traffic vaiolations and accidents. In the experiment three traffic conditions (an open road condition, a bumper-to-bumper traffic condition and a being stuck behind a slower driver condition) were simulated and driving behaviors were collected with RTSA-DS(Road Traffic Safety Authority-Driving Simulator). The results were as follows: Most of high anger drives drove at higher speeds in an open road condition, and in the bumper-to-bumper condition they drove faster and had an higher crash rate, which suggests they did aggressive driving, and risky and unsafe behaviors.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.91-101
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• 2003

This study modeled 4-lane highway in three-dimensional virtual reality in order to overcome difficulties of field experiment. and the research subject was placed in a driving simulator. We survey the driver's cognitive characteristics to the alignment changes in the three-dimensional virtual reality highway. Especially, maximizing the identity of driving movements and virtual scenery on the basis of the data obtained by dynamic analysis module. we minimized simulator sickness for the graphic module of driving simulator. And we carried out cognitive evaluation on the basis of adjective words extracted by dictionary and the opinion of specialist. In this study LISREL model was used to detect the causal relation between geometry and safety in cognitive side, and found that geometric change affects the safety of drivers by static and dynamic road safety model in three-dimensional combined alignments. As the result, for constructing safety road. we consider drivers' cognitive characteristics as human factors in road design, and we think that they are very important factors to improve road safety.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.80-89
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• 2000

Driving simulators provide engineers with a power tool in the development and modification stages of vehicle models. One of the most important factors to realistic simulations is the fidelity obtained by a motion bed and a real-time visual image generation algorithm. Virtual reality technology has been widely used to enhance the fidelity of vehicle simulators. This paper develops the virtual environment for such visual system as head-mounted display for a vehicle driving simulator. Virtual vehicle and environment models are constructed using the object-oriented analysis and design approach. Based on the object model, a three-dimensional graphic model is completed with CAD tools such as Rhino and Pro/ENGINEER. For real-time image generation, the optimized IRIS Performer 3D graphics library is embedded with the multi-thread methodology. The developed software for a virtual driving simulator offers an effective interface to virtual reality devices.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.57-66
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• 2005

In this paper, a new rehabilitation training system was developed to improve equilibrium sense by combining virtual reality technology with a fixed exercise bicycle. The subjects consisted of two groups. A group of young people, was compared against a group of elderly. We measured three different running modes of virtual bicycle system with two successive sets. The parameters measured were running time, velocity, the weight movement, the degree of the deviation from the road, and the variables about the center of pressure. The repeated training, our results showed that the running capability of the elderly improve compared. In addition, it was found out that the ability of postural control and the equilibrium sense was improved with the presentation of the visual feedback information of the distribution of weight. From the results of this experiment, we showed that our newly developed system might be useful in the diagnosis of equilibrium sense or in the improvement of the sense of sight and, somatic, and vestibular sense of the elderly in the field of rehabilitation training.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.162-177
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• 2020

The perception of traffic environment based on various sensors in autonomous driving system has a direct relationship with driving safety. Recently, as the perception model based on deep neural network is used due to the development of machine learning/in-depth neural network technology, a the perception model training and high quality of a training dataset are required. However, there are several realistic difficulties to collect data on all situations that may occur in self-driving. The performance of the perception model may be deteriorated due to the difference between the overseas and domestic traffic environments, and data on bad weather where the sensors can not operate normally can not guarantee the qualitative part. Therefore, it is necessary to build a virtual road environment in the simulator rather than the actual road to collect the traning data. In this paper, a training dataset collection process is suggested by diversifying the weather, illumination, sensor position, type and counts of vehicles in the simulator environment that simulates the domestic road situation according to the domestic situation. In order to achieve better performance, the authors changed the domain of image to be closer to due diligence and diversified. And the performance evaluation was conducted on the test data collected in the actual road environment, and the performance was similar to that of the model learned only by the actual environmental data.

• Information and Communications Magazine
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• v.29 no.2
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• pp.39-45
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• 2012

V2X 차량 안전 시스템은 ITS 환경에서 주행하는 모든 차량들이 V2V 혹은 V2I 기반의 협력통신을 통해 안전 서비스를 제공하는 기술이다. 이는 실제 도로환경에서의 실험, 즉 Field Operational Tests(FOTs)를 통한 검증과 평가 수행이 요구된다. 그러나, 일반적으로 실 도로환경에서 시스템 및 서비스에 대한 검증과 평가는 많은 시간과 비용을 필요로 한다. 따라서 실제 도로 주행 테스트 전에 V2X 안전 서비스의 기본적인 성능을 검증할 V2X 시뮬레이션 방안이 필요하다. 본 논문에서는 국외의 V2X 시뮬레이터 기술 개발 동향과 함께 차량 간 통신 시뮬레이션 분야에서 연구되고 있는 주요 이슈들을 알아보고 이를 극복하기 위한 연구 방호별 제시한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.10-24
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• 2014

In-vehicle warning information systems(IWIS) is an effective countermeasure for preventing traffic crashes. It provides drivers with warnng messages about upcoming hazards to draw proper evasive maneuvering. This study developed a methodology for evaluating the effectiveness of IWIS based on an integrated index to identify driver's responsive behavior. The proposed index consists of characteristics of longitudinal and lateral behavior of vehicle maneuverings. Also, a method to assign mixed-weights in the context of multi-criteria decision making framework was adopted to develop the evaluation method. It is expected that the outcome of this study is useful in designing more effective in-vehicle warning information systems.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.19-19
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• 2017

자율주행 트랙터를 위한 트랙터 조향제어는 일반적으로 전자모터를 이용한 EPS(Electric Power Steering) 시스템을 스티어링 휠에 연결하여 회전변위를 변경하고 그 결과 오비트롤(Orbitrol) 밸브의 토출유량을 바꾸고 호스로 연결된 조향실린더의 변위를 조절하여 최종적으로 전방 타이어의 방향각을 변경하면서 이루어진다. 이러한 조향방식은 시스템 구조상 조향실린더와 오비트롤 밸브가 상대적으로 멀리 떨어져 있으며, 밸브 특성상 약 ${\pm}5^{\circ}$의 오버랩이 포함되어 있다. 또한, EPS의 전자모터는 관성력, 마찰, 백래시 등의 영향을 가진다. 이와 같은 복합적인 영향은 조향 응답을 느리게 만들어 상대적으로 빠른 속도에서 주행에서 추종성능이 떨어지는 문제가 발생한다. 본 연구에서는 자율주행 트랙터의 조향성능 개선 연구의 일환으로 조향 HILS 시뮬레이터를 설계제작하여 조향 성능의 요인을 실험적으로 구명하고자 하였으며 이를 바탕으로 조향 시스템의 설계개선 방안을 수립하고자 하였다. 시뮬레이터는 동양물산 80 마력급 TX803 트랙터에 사용되는 오픈센터방식의 오비트롤 유압회로 시스템을 기어펌프가 장착된 AC모터로 구동되게 구성하였으며, 유량은 모터의 주파수를 조절 회전속도를 조절 변경하였다. 추가적으로 EPS와 오비트롤 조합의 조향성능을 비교 및 개선하기 위해 비례제어밸브(PVG 32, Danfoss)를 추가 장착하였다. 실제 트랙터 조향 시 나타나는 마찰저항을 모사하기 위해 부하 실린더를 구성하였으며, 조향 실린더의 부하의 크기는 부하 실린더를 폐회로를 구성하고 유량비례제어밸브를 이용한 유로의 개구량 조절을 통해 부하의 크기를 약 4000 N 까지 증가시킬 수 있도록 하였다. EPS와 비례제어밸브를 제어하기 위해 CANoe 8.0 소프트웨어를 이용하여 CAN통신 기반 가상 조향ECU를 구성하였으며 오비트롤의 기본 성능을 확인하기 위해 조향휠에 따른 실린더 동특성 및 계단 추종성능을 비례제어밸브와 비교하였다. 오비트롤 밸브는 약 ${\pm}5^{\circ}$이상 동작 시 실린더 압력이 상승하기 시작하였으며, 이후 약 ${\pm}10^{\circ}$이상 동작 시 조향실린더가 동작하기 시작하였다. 계단 추종성능실험에서는 비례제어밸브가 약 2배 이상의 응답개선을 나타냈다. 자율주행 경로추종 성능을 향상시키기 위해서는 순간적인 출력밀도가 높은 비례제어밸브를 통해 응답개선이 필요한 것으로 나타났다.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.109-123
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• 2024

Research into vision-based end-to-end autonomous driving systems utilizing deep learning and reinforcement learning has been steadily increasing. These systems typically encode continuous and high-dimensional vehicle states, such as location, velocity, orientation, and sensor data, into latent features, which are then decoded into a vehicular control policy. The complexity of urban driving environments necessitates the use of state representation learning through networks like Variational Autoencoders (VAEs) or Convolutional Neural Networks (CNNs). This paper analyzes the impact of different image state encoding methods on reinforcement learning performance in autonomous driving. Experiments were conducted in the CARLA simulator using RGB images and semantically segmented images captured by the vehicle's front camera. These images were encoded using VAE and Vision Transformer (ViT) networks. The study examines how these networks influence the agents' learning outcomes and experimentally demonstrates the role of each state representation technique in enhancing the learning efficiency and decision- making capabilities of autonomous driving systems.

• Review of KIISC
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• v.33 no.4
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• pp.23-29
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• 2023

대부분의 임베디드 시스템은 기계장치와 전자기기 장치가 함께 작동되는 물리 장치로써, 이기종 네트워크, 복잡한 보안체계 등을 고려하여 가상화 기반 사이버훈련 환경이 구성되어야 한다. 또한, 차량을 대상으로 물리적인 실험환경에서 모의침투 등 사이버훈련을 수행한다는 것은 교통사고를 비롯한 안전사고 발생에 있어 위험이 존재한다. 본 논문에서는 가상 개발환경에서의 공격 기반 차량용 사이버훈련 프레임워크를 제안하고자 한다. 먼저, 공격 기반 차량용 사이버훈련 프레임워크의 작동은 자동 활성화되는 가상의 CAN 네트워크 인터페이스로 시작된다. 가상의 CAN 네트워크 인터페이스는 가상 머신에서 간단한 부트스트랩 명령어 실행을 통해 파이썬 패키지와 Ubuntu 서비스 목록 설치 명령이 자동으로 실행되면서 설치된다. 이후 내부 네트워크 시뮬레이터와 공격모듈과 관련된 UI가 자동으로 Ubuntu Systemd에 의해 백그라운드에서 실행되어 시작과 동시에 준비 상태를 유지하게 된다. 사이버훈련 UI 내 공격 모듈은 사용자에 의한 공격 선택 및 파라미터 셋팅 이후 차량의 이상 상태를 사이버훈련 UI에 다시 출력되게 된다. 본 논문에서 제안하는 가상 개발환경 기반의 차량용 사이버훈련 프레임워크는 자율주행 차량 사고의 위험이나 다른 특수한 제약 없이 사용자의 학습 경험을 확장시킬 수 있다. 또한, 기존의 가상화 기반 사이버훈련 교육 콘텐츠와는 달리 일반 사용자들이 접근하기 쉬운 형태로 확장 개발이 가능하다.