• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.405-416
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• 2015

This paper developed a method analyze drivers' response characteristics using spectral analysis with car following data. Cross-correlation function and cross spectrum are produced by Fourier transform from speed fluctuations of leading vehicle and following vehicle during the designated time ${\tau}$. Based on the analysis data, a process to calculate the reaction time and stimulus-adaption index of following vehicle was developed and 170 cases of field data was applied. It was reported average of 0.654 and 2.091 seconds of stimulus-adaption index and reaction time respectively. In conclusion, the developed indexes might contribute to enhance vehicle control of autonomous vehicle more efficient and safer.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.74-84
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• 2022

Vehicle average speed information which measured at a point or a short section has a problem in that it cannot accurately provide the speed changes on an actual highway. In this study, segment separation method based on vehicle big data for accurate micro-speed estimation is proposed. In this study, to find the point where the speed deviation occurs using location-based individual vehicle big data, time and space mean speed functions were used. Next, points being changed micro-scale speed are classified through gradual segment separation based on geohash. By the comparative evaluation for the results, this study presents that the link-based speed is could not represent accurate speed for micro-scale segments.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.1
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• pp.43-52
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• 2018

In recent years, the need of high accuracy navigation for vehicles has increased due to the development of autonomous driving vehicles and increase in land transportation convenience. This study is performed for vehicle users to achieve a performance of centimeter-level positioning accuracy by utilizing Compact Network Real-time Kinematic (RTK) that is applicable as a national-level infrastructure. To this end, medium-baseline RTK was implemented in real time to estimate accurate integer ambiguities between reference stations for reliable generation of Network RTK correction using the linear combination of carrier-phase observations and L1/L2 pseudo-range measurements. The residual tropospheric error was estimated in real time to improve the accuracy of double-differenced integer ambiguity resolution between network configuration reference stations that have at least 30 km or longer baseline distance. In addition, C++ based software was developed to enable real-time generation and broadcasting of Compact Network RTK correction information by utilizing an accurately estimated double-differenced integer ambiguity values. As a result, the horizontal and vertical 95% accuracy was 2.5cm and 5.2cm, respectively, without performance degradation due to user's position change within the network.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.254-260
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• 2023

A sensor system has been developed that uses an ultrasonic sensor to detect the downhill slope on the side of a forest road and prevents a vehicle-type forest machine from rolling down a mountainside. A specular reflection of ultrasonic wave might cause severe issues in measuring distances to targets. By investigating the installation angle of the sensor to minimize the negative effects of specular reflection, the installation angle of lateral monitoring ultrasonic sensor could be determined based on the width of road shoulder. Obstacles such as small rocks or piece of log in a forest road may cause the forest machine to be overturned while the machine riding over due to excessive its posture change. It was determined that the laser sensor could be a part of a sensor system capable of specifying the location and size of small obstacles. Not only this sensor system including ultrasonic and laser sensors can issue a warning of dangerous sections to drivers in forest forwarders currently in use, but also it can be used as a driving safety sensor in autonomous forest machine or remote-control forest machine in the future.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.508-510
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• 2004

In this paper, we proposed the GPS position data correction method for autonomous land navigation using vanishing point property and a monocular vision system. Simulations are carried out over driving distances of approximately 60 km on the basis of realistic road data. In straight road, the proposed method reduces GPS position error to minimum more than 63% and positioning errors within less than 0.5m are observed. However, the average accuracy of the method is not presented. because it is difficult to estimate it in curve road or other road environments.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.17-18
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• 2017

본 논문은 스마트 팩토리의 중요 요소인 무인반송차(AGV)를 자율 주행시키기 위해 오픈 소스 자율 주행차 시뮬레이터인 udacity를 이용해 머신 러닝시키는 시스템을 개발하였다. 공장의 운행 루트를 자율주행 시뮬레이터의 전경으로 가공하고, 3개의 카메라를 부착시킨 AGV를 운행시키면서 머신 러닝시킨다. AGV를 주행하여 얻어진 여러 학습 데이터를 통해 도출된 결과들을 각각 비교하여 우수한 모델을 선정하고 운행시킨 결과 AGV가 정해진 운행 루트를 정확하게 주행하는 것을 확인하였다. 이를 통해, 가상 운행 환경에서 저비용으로 AGV 운행 학습이 가능하다는 것을 보였다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2572-2574
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• 2000

In this paper, cell-mediated immune algorithm(CMIA) controller was proposed and applied for the autonomous guided vehicle(AGV) driving. It was based on specific immune response of the biological immune system which is the cell-mediated immunity. To verify the performance of the designed CMIA controller, some experiments were performed for the control of steering and speed of AGV. And then the displacement and speed tracking error of the AGV was mainly investigated. As results, the capability of realization and reliableness were proved by comparing the response characteristics of the classical controller with the proposed CMIA controller.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.1-11
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• 2021

In this study, we analyze the automotive chip ecosystem that recently caused the global supply shortage, and attempt to derive policy implications for us from the conclusion. Automotive chips are critical parts that control various systems so that a vehicle can drive itself or operate with electricity. The current shortage in supply and demand for automotive chips is due to the inconsistency between supply and demand between automotive chip companies and car manufacturers. To promote the automotive chip industry, new investment incentives, tax cuts, and human resource training are needed.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.681-683
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• 2009

기존 첨단안전차량의 개발시 실제 자동차를 활용하여 주행제어시스템을 개발을 하고 있다. 본 논문에서는 임베디드지능형자동차를 활용하여 자율주행제어시스템을 설계하고 테스트하여 개발에 소모되는 에너지와 비용을 절약할 수 있는 방식을 제안 한다. 본 논문에서 설계한 제어시스템은 임베디드 지능형 자동차에 설치되어 실제 도로와 유사한 환경으로 구축된 테스트베드에서 영상을 통해 감지한 차선정보와 적외선 거리 센서를 통한 장애물 정보를 통합하여 주변 상황을 판단, 적절한 주행 시나리오를 선택하는가를 테스트 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.637-639
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• 2021

As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.