• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 춘계학술대회논문집A
• /
• pp.505-510
• /
• 2000

Vehicle performances such as fuel consumption and catalyst-out emissions are affected by a driving pattern, which is defined as a driving cycle with the grade in this study. We developed an algorithm to recognize a current driving pattern by using a neural network. And this algorithm can be used in adapting the driving control strategy to the recognized driving pattern. First, we classified the general driving patterns into 6 representative driving patterns, which are composed of 3 urban driving patterns, 2 suburban driving patterns and 1 expressway driving pattern. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, relative duration spent at stop, average acceleration and average grade are chosen to characterize the driving patterns. Second, we used a neural network (especially the Hamming network) to decide which representative driving pattern is closest to the current driving pattern by comparing the inner products between them. And before calculating inner product, each element of the current and representative driving patterns is transformed into 1 and -1 array as to 4 levels. In the end, we simulated the driving pattern recognition algorithm in a temporary pattern composed of 6 representative driving patterns and, verified the reliable recognition performance.

• 한국자동차공학회논문집
• /
• 제20권4호
• /
• pp.60-67
• /
• 2012

Most of a driving cycle is used to measure fuel consumption (FC) and emissions for a specified vehicle. A driving cycle was reflected geography and traffic characteristics for each country, also, driving pattern is affected these parameters such as vehicle dynamics, FC and emissions. Therefore, this study is an attempt to develop a driving cycle for military operational area. The proposed methodology the driving cycle using micro-trips extracted from real-world data. The methodology is that the driving cycle is constructed considering important parameters to be affected FC. Therefore, this approach is expected to be a better representation of heterogeneous traffic behavior. The driving cycle for the military operational area is constructed using the proposed methodology and is compared with real-world driving data. The running time and total distance of the final cycle is 1461 s, 13.10 km. The average velocity is 32.25 km/h and average grade is 0.43%. The Fuel economy in the final cycle is 5.93 km/l, as opposed to 6.10 km/l for real-world driving. There were about 3% differences in driving pattern between the final driving cycle and real-world driving.

• 대한교통학회지
• /
• 제25권5호
• /
• pp.149-160
• /
• 2007

차량용 블랙박스는 사고 및 평시 주행 정보를 저장 제공한다. 이러한 주행 사고 정보들을 가지고 과학적인 교통사고 데이터베이스를 구축할 수 있으며, 여러 산업 분야에서 활용될 수 있다. 본 연구에서는 주행 데이터 특성 분석과 위험 운전 인지 체계 구축을 목적으로 한다. 위험 운전 유형을 차량의 거동(가속, 감속, 선회)과 교통사고 통계 자료들을 고려하여 4가지 유형으로 분류하였다. 위험 운전 데이터는 차량용 블랙박스를 활용한 실차 실험을 통해 수집하였으며, 위험 운전 분류를 위하여 주행 데이터의 특성을 분석하였다. 위험 운전 인지를 위하여, 기준 임계치를 선정하고 위험 운전 인지 알고리즘을 구성하였다. 개발한 알고리즘을 구현한 차량용 블랙박스 탑재 실차 실험을 통하여 검증하였다. 본 논문에서 제시하는 위험 운전 인지 방안은 온라인/오프라인 운전자 및 차량 관리 등 시스템에 활용할 수 있다.

• 한국ITS학회 논문지
• /
• 제22권6호
• /
• pp.264-283
• /
• 2023

자율주행차량 사고는 일반차량 사고와 다르게 기술적 문제, 환경, 운전자와의 상호작용 등 다양한 요인에 기인한 사고 발생 가능성이 존재한다. 향후 자율주행 기술의 진보로 기존의 사고원인 이외에도 새로운 이슈들이 대두될 것으로 예상되며, 이에 대응하기 위한 다양한 시나리오 기반의 접근법이 필요하다. 본 연구에서는 자율주행 사고 리포트인, CA DMV collision report와 자율주행모드 해제 보고서인 Disengagement report, 자율주행 실제 사고영상을 수집하여 자율주행차량 교통사고 시나리오를 개발하였다. 시나리오는 ISO 26262의 기능안전 시스템 failure mode에 기반하여 도출되었으며, 자율주행 기능의 다양한 이슈를 반영하고자 하였다. 본 연구를 통해 도출된 자율주행차량 시나리오는 향후 다양한 자율주행차량 교통사고 예방과 대비에 기여할 뿐만 아니라 자율주행 기술의 안전성을 향상시키는 데 중요한 역할을 할 것으로 기대한다.

• 한국자동차공학회논문집
• /
• 제13권2호
• /
• pp.149-156
• /
• 2005

In this paper, the VR(Virtual Reality) simulation system is developed to analyze driver's perceptive response on the ASV(Advanced Safety Vehicle). The ASV is the vehicle of next generation equipped with various warning systems. For the purpose, the VR simulation system consists of VR database, vehicle dynamic model, graphic/sound system, and driving system. The VR database which generates 3D graphic and sound information is organized for the driving reality. Mathematical models of vehicle dynamic analysis are constructed to represent the dynamic behavior of a vehicle. The driving system and the graphic/sound system provide a driver with the operation of a vehicle and the feedback of a driving situation. Also, the real-time simulation algorithm synchronizes the vehicle dynamic model with the VR database. To check the validity of the developed system, a simple scenario is applied to investigate driver's perceptive response time and vehicle acceleration on an emergency situation. It is confirmed that the proposed system is useful and helpful to design the FVCWS(Forward Vehicle Collision Warning System).

• 한국자동차공학회논문집
• /
• 제18권4호
• /
• pp.31-39
• /
• 2010

Although driving patterns strongly influence greenhouse gas and air pollutant emission rate from light duty vehicles, emission measurements have been mainly based on chassis dynamometer testing with one standard driving pattern. And there has been limited work on quantifying the independent effect of driving parameters on emission rate because of multidimensional nature of real-world driving pattern. The objective of this study is to obtain the quantitative effect of relative positive acceleration (RPA) on vehicle emission rate. RPA has been used to define the occurrence of acceleration demanding large amounts of power in certain driving distance and shown to be a significant affecting parameter for real-world emission rate. 40 driving patterns have been developed with fixed driving parameters to investigate independent effect of RPA. For the same values of average vehicle speed and power, the trend in carbon dioxide emission rate and fuel consumption with respect to RPA is very clear. Emission rate of nitrogen oxide and particulate matter also increase with respect to RPA, but the trend is less clear. Carbon dioxide emission from diesel vehicle appear to be more affected by high accelerations compared to that from gasoline vehicle because of high intake air restriction during acceleration caused by turbocharger and intercooler. The results have implications for the possible reduction of environmental effects through better traffic planning and management, driver education and car design.

• 대한토목학회논문집
• /
• 제30권3D호
• /
• pp.303-311
• /
• 2010

현재 사업용 차량의 교통사고 감소 및 안전운전에 대한 사회적 요구에 부흥하기 위하여 디지털 주행기록계, 차량용 블랙박스 등 다양한 형태의 시스템이 사용되고 있으나, 이러한 시스템은 주행 후 저장된 차량데이터를 기반으로 위험 운전 여부를 분석하기 때문에 위험운전을 실시간으로 예방하기에는 큰 한계성을 있는 것이 사실이다. 이에 본 연구의 선행연구에서는 차량 운전자의 운전행태에 따른 차량동역학 데이터를 저장 판단하여 운전자에게 실시간으로 경고정보를 제공하여 운전자의 안전운전을 향상 시킬 수 있는 위험운전 판단장치를 개발하였으나, 이에 대한 성능평가가 이루어 지지 않고 있는 실정이다. 따라서 본 연구에서는 기 개발된 위험운전 판단장치의 성능평가를 위하여 DGPS를 이용한 정밀위치 인식시스템을 구축하였다. 실험 결과 위험운전 판단장치에서 취득되는 차량 동역학 데이터와 DGPS를 통하여 취득되는 데이터가 거의 일치하는 것으로 분석되었다. 따라서 구축된 정밀위치 인식시스템을 통하여 위험운전 판단장치의 성능이 검증되면 차량의 위험운전 관리에 매우 효과가 있을 것으로 판단된다.

• 자동차안전학회지
• /
• 제10권2호
• /
• pp.29-35
• /
• 2018

This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.

• 제어로봇시스템학회논문지
• /
• 제15권8호
• /
• pp.823-830
• /
• 2009

For developing automotive parts and telematics devices the real car test often shows limitation because it needs high cost, much time and has the possibility of the accident. Therefore, a Vehicle Driving Simulator (VDS) instead of the real-car test has been used by some automotive manufactures, research centers, and universities. The VDS is a virtual reality device which makes a human being feel as if one drives a vehicle actually. Unlike actual vehicle, the simulator has limited kinematic workspace and bounded dynamic characteristics. So it is difficult to simulate dynamic motions of a multi-body vehicle model fully. In order to overcome these problems, a washout algorithm which restricts workspace of the simulator within the kinematic limits is needed, and analysis of dynamic characteristics is required also. However, a classical washout algorithm contains several problems such as time delay and generation of wrong motion signal caused by characteristics of filters. Specially, the classical washout algorithm has the simulator sickness when driver hardly turns brakes and accelerates the VDS. In this paper, a new washout algorithm is developed to enhance the motion sensitivity and improve the simulator sickness by using the vehicle tilt signal which is generated in the real time vehicle dynamic model.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2010년도 추계학술대회
• /
• pp.66-69
• /
• 2010

최근 차량에는 차량과 IT와 결합을 차량의 안전성, 편리성을 위해 많은 전자제어장치(ECU)가 장착되어 있고 있다. 이러한 전자제어장치는 각 전자제어장치에 대한 Data는 OBDII 네트워크에 전송을 하고 멀티미디어에 대한 Data 는 MOST 네트워크에 전송을 한다. 본 논문에서는 기존의 블랙박스의 문제점을 보완하기 위해 차량용 네트워크의 새로운 멀티미디어 네트워크인 MOST 차량용 네트워크와 현재 차량에서 표준적으로 쓰이는 OBDII 차량용 네트워크를 이용하여 전자제어장치의 데이터를 이용한 Data들을 취합하여 차량의 현재 상황을 판단하고 정보를 제공함으로써 차량의 안전성 및 블랙박스로써의 역할을 극대화 시킬 수 있는 차량용 블랙박스 시스템을 구현하고자 한다.