• 전기학회논문지
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• 제61권5호
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• pp.735-743
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• 2012

In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.525-528
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• 2008

The research was conducted to investigate the characteristics of lateral wheel path distributions (wandering) in different traffic lanes. The Wandering may affect pavement life and various distress types. To achieve results presented that the normal distribution curve with symmetry was observed in the 3-lane roads. In the case of the 3-lane road (on one direction), 50-60cm, 65-85cm, and 80-95cm for the 1st, 2nd, and 3rd lanes, respectively. In addition, the 1st lane vehicles tended to pass on the right side to avoid th opposite side vehicles, while the outside lane vehicles tended to pass on the left side to avoid the walkway.

• 한국자동차공학회논문집
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• 제13권4호
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• pp.19-25
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• 2005

This paper presents a lateral control system for the autonomous navigation vehicle that was developed and tested by Robotics Centre of Ecole des Mines do Paris in France. A robust lane detection algorithm was developed for detecting different types of lane marker in the images taken by a CCD camera mounted on the vehicle. $^{RT}Maps$ that is a software framework far developing vision and data fusion applications, especially in a car was used for implementing lane detection and lateral control. The lateral control has been tested on the urban road in Paris and the demonstration has been shown to the public during IEEE Intelligent Vehicle Symposium 2002. Over 100 people experienced the automatic lateral control. The demo vehicle could run at a speed of 130km1h in the straight road and 50km/h in high curvature road stably.

• 한국안전학회지
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• 제26권5호
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• pp.130-135
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• 2011

This study deals with the accident models of arterial road sections. The objectives is to develop the models by number of lane. In pursuing the above, this study gives particular emphasis to dividing the 474 small link sections, collecting the accident data of 2007, and applying the statistical programs of SPSS17.0 and NLOGIT4.0. The main results are as follows. First, the number of accidents of two-lane roads were analyzed to be 59.9% of totals and to be the most of all. Second, one Poisson and two negative binomial regression models which were all statistically significant were developed. Finally, the common variables of all models were evaluated to be ADT and number of exit/entry which were all positive to the accidents.

• 대한교통학회지
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• 제7권2호
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• pp.5-15
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• 1989

The Provision of a Passing lane is strongly recommended When adeguate Passing Sight distance cannot be acguired at a Section of two-lane highway. Passing lanes are usually installed at two-lane highways along the shoulder area to minimize the impact of slow-moving heavy vehicles. The design concepts and specific dimension associated with the Passing lane construction are investigated in This research. In addition a case study was made using the field study data. Currently the level of service at the case study area was analyzed to be "F" based on 1985 Highway Capacity Manual procedure. With the installation of passing lanes, the level of service was improved into "C". A computer Simulation program developed by Australian Road Research Boand was utilized to analyze the effect of passing lanes.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.896-897
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• 2014

스마트 내비게이션을 위해 차량의 차선 위치를 인식할 필요가 있다. 본 논문에서는 이를 위한 선행 연구로 다중차선 검출 기법을 제안한다. 기존 Box filter, Step filter가 클러터에 취약한 부분을 보완하기 위해 Three Point Laplacian Filter (TPLF)를 제안하고 실험적으로 그 가능성을 검증한다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.210-218
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• 2021

CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2008년도 제7회 추계학술대회 및 정기총회
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• pp.309-310
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• 2008

• 한국도로학회:학술대회논문집
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• 한국도로학회 2009년도 추계학술대회 논문집
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• pp.697-701
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• 2009

• 한국산업정보학회논문지
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• 제18권5호
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• pp.25-32
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• 2013

고속 저전력 모바일 응용분야를 위한 1.8V 2-Gb/s scalable low voltage signaling (SLVS) 송신단을 제안한다. 제안하는 송신단은 데이터 전송을 위한 4-lane 송신단, 소스 동기 클록 방식을 위한 1-lane 송신단, 그리고 8-phase 클록 발생기로 구성된다. 제안하는 SLVS 송신단은 50 mV에서 650 mV의 출력 전압 범위를 가지며 고속 동작 모드와 저전력 모드를 제공한다. 또한, signal integrity를 개선하기 위한 출력 드라이버의 임피던스 교정 기법이 제안된다. 제안하는 SLVS 송신단은 1.8 V의 공급 전압을 가지는 0.18-${\mu}m$ 1-poly 6-metal CMOS 공정을 이용하여 구현된다. 구현된 SLVS 송신단의 데이터 jitter의 시뮬레이션 결과는 2-Gb/s의 데이터 전송속도에서 8.04 ps이다. 1-lane을 위한 SLVS 송신단의 면적과 전력소모는 각각 $422{\times}474{\mu}m^2$와 5.35 mW/Gb/s이다.