• 한국도로학회:학술대회논문집
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• 2005.11a
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• pp.311-316
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• 2005

• Journal of the korean Society of Automotive Engineers
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• v.23 no.6
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• pp.21-25
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• 2001

• Proceedings of the Korean Vacuum Society Conference
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• 1992.07a
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• pp.16-16
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• 1992

• Journal of the korean veterinary medical association
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• v.33 no.1
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• pp.8-13
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• 1997

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.115-120
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• 2015

Recently, in automotive technology area, intelligent safety systems have been actively accomplished for drivers, passengers, and pedestrians. Also, many researches are focused on development of autonomous vehicles. This paper propose the application of LiDAR sensors, which takes major role in perceiving environment, terrain classification, obstacle data clustering method, and local map building for autonomous driving. Finally, based on these results, planning for lane change path that vehicle tracking possible were created and the reliability of path generation were experimented.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.4
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• pp.244-250
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• 2008

This paper describes the design and implementation of an unmanned ground vehicle (UGV) and also estimates how well autonomous navigation and remote control of UGV can be performed through the optimized arbitration of several sensor data, which are acquired from vision, obstacle detection, positioning system, etc. For the autonomous navigation, lane detection and tracing, global positioning, and obstacle avoidance are necessarily required. In addition, for the remote control, two types of experimental environments are established. One is to use a commercial racing wheel module, and the other is to use a haptic device that is useful for a user application based on virtual reality. Experimental results show that autonomous navigation and remote control of the designed UGV can be achieved with more effectiveness and accuracy using the proper arbitration of sensor data and navigation plan.

• Journal of Drive and Control
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• v.17 no.1
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• Journal of Korean Society of Transportation
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• v.6 no.1
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• pp.17-31
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• 1988

In this research, the behavior of weaving traffic is studied in terms of lane-changing behavior and gap acceptance characteristics. General trends in lane-changing behavior and gap acceptance characteristics are investigated by analyzing descriptive statistics and the factors affecting weaving behavior are determined by means of the multiple linear regression analysis. The results of analysis show that the behavior of weaving traffic is generally similar to that in a basic freeway section and an on- or of- ramp section. Traffic density and speed appear to be better parameters than traffic volume for explaining the behavior of weaving traffic. For the same purpose, using the traffic conditions of the origin and the destination lanes are found to be more effective than using the average traffic conditions of the freeway. A detailed analysis of the gap acceptance characteristics of late merging vehicles shows that there is no significant difference between the size of gaps accepted by late merging vehicles and that accepted by early merging vehicles.

• Journal of Korean Society of Transportation
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• v.8 no.2
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• pp.109-118
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• 1990

본 고는 도로선형 설계에 확율 및 경제요소를 반영시키는 방법과 그에 따른 효과를 파악하는데 목적을 두고 있다. 접근방법은 도로사용자 비용과 도로시공 및 유지관리 비용 등을 포함하는 총비용을 예상비용함수로 나타내어 이 비용함수를 최소화함으로써 최적 도로선형 설계방법을 찾는 것이다. 이와 더불어 본 고는 이 개념에 의한 최적 설계방법을 등반차선(Climbing lane)의 설계에 적용하였다. 즉, 오르막길의 경사 및 거리에 따른 등반차선의 최적 위치를 찾기 위해 우선 오르막길에서의 승용차와 트럭의 속도분포를 찾아내고 예상예비함수를 등식화하여 그 최적해를 구함으로써 등반차선의 최적 위치를 구하였다. 현재 등반차선의 설계과정(AASHTO, 1984)은 트럭 주행능력에 따른 가정과 트럭과 승용차의 최대 속도 차이를 임의로 선택하여 등반차선의 최적 위치를 찾고 있다. 따라서 본 고에서는 기존 등반차선 설계방법과 새로운 설계방법을 상호 비교하면서 새로운 방법의 타당성과 그에 따른 설계이점들을 증명하였다.