• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.343-348
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• 2007

Development of autonomous vehicle system that use magnetic position meter research of intelligence transportation system is progressed worldwide active by fast increase of vehicles. Among them, research about autonomous of vehicles occupies field. And autonomous of vehicles is element that path recognition is basic. Existent magnetic base autonomous system analyzes three-dimensional data of magnet marker to 3 axises magnetic sensor and recognized route. But because using Magnetic Wire and Magnetic Position Meter in treatise that see, measure side lateral error and propose system that driving. And system that compare with system of autonomous vehicles and propose wishes to verify by hardware of that specification and simple algorithm through an experiment that autonomous is available.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.7-11
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• 2008

This paper presents the experimental results on the oil leakage characteristics of stem seals depending on the driving distance in LPG vehicle. The increased speeds of the camshaft and oil temperatures do not affect to the oil leakage of the seals because of the low level of driving distances less than 40,000 km. But the increased driving distance over 50,000 km to 100,000 km shows a rapid deteriorating the sealing performance, which may increase the oil leakage through the rubbing surfaces between the poppet valves and stem seals. In this result, the stem seal may be exchanged about the driving distance of 50,000 km to 60,000 km with a currently used stem seal in LPG car. Thus, the stem seal for a poppet valve should be resigned for the increased durability and long life.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1307-1312
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• 2023

In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1071-1078
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• 2018

In this paper, we implemented community driving system for auto-vehicles as a preceding research of drone's community flight. We used ultrasonic sensors in order to measure the distance between vehicles, and designed each vehicles to maintain specific distance to each other, by making the following vehicle to stop moving when the distance is closed to less than 20cm, to start moving when the distance increases to more than 30cm. We have also designed vehicle to accelerate until the distance is closed to 30cm when they are apart for more than 40cm due to contingencies during driving.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.3-6
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• 2007

전 세계적으로 차량의 급속한 증가로 인해 지능형교통시스템에 대한 연구가 활발히 진행 되고있다. 그중 차량의 자율주행에 관한 연구가 한 분야를 차지한다. 그리고 차량의 자율주행은 경로 인식이 기본적인 요소이다. 기존의 경로인식은 3축 자계 센서로 자석마커의 3차원의 데이터를 분석하여 인식하였다. 그러나 본 논문에서는 Magnetic Wire와 자기거리계를 이용하여 측면 이탈거리를 계측하여 주행하는 시스템을 제안한다. 그리고 기존 자율주행 차량의 시스템과 비교하고 제안하는 시스템이 저사양의 하드웨어와 간단한 알고리즘으로 자율주행이 가능함을 실험을 통해 검증하고자 한다.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.170-175
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• 2016

An internal combustion engine is the most widely used power source for an automobile. In order to resolve environmental problems resulting from the use of internal combustion engines, environmentally friendly automobiles such as hybrid, electric, and air-engine vehicles are being developed. The share of hybrid vehicles using battery or pure electric vehicles, which are not popular, is gradually increasing. Compared to an electric vehicle, which uses an electric motor, air-engine vehicles, which use compressed air, have hardly been developed. In this study, a compressed air engine with a scroll expander is introduced, and the potential mileage of an automobile utilizing this engine is theoretically calculated.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.433-434
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• 2008

이 논문은 실내에서 로봇의 주행 시 생기는 오차를 수정하는 것이다. 실내에 있는 장애물(문턱)을 넘을 경우 슬립에 의하여 주행거리와 실제거리의 오차가 생기고 또한 헤드 앵글 값이 변화함에 따라서 차후 엄청난 주행 오차를 발생시키게 된다. 그에 따라 PSD 센서를 이용하여 장애물을 감지하고 감지 후 장애물을 넘을 수 있도록 모터를 제어한다. 또한 PSD를 이용하여 장애물의 크기를 계산한 후 로봇이 장애물을 넘는 동안에 엔코더 값을 받아 들여서 장애물을 넘는 동안에 로봇이 실제 이동한 거리를 측정한다. 그리고 장애물을 넘은 후에 PSD로 계산한 장애물의 크기 값과 엔코더에서 받아들인 값을 비교하여 거리오차를 수정한다. 또한 전자컴퍼스를 이용하여 장애물을 넘기 전에 로봇의 헤드 앵글 값을 구하고, 장애물을 넘은 후에 로봇의 헤드 앵글 값을 구하여 두 개의 값을 비교한다. 두 개의 값의 차이를 측정하여 수정함으로써 헤드 앵글을 오차를 수정할 수 있다.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.1-12
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• 2014

The tier 3 methodology used in estimation of greenhouse gas emissions from road sectors is based on mileage data. However, such data can neither accurately represent the mileage of regional unit nor have sufficient integrated data reflecting the characteristics by region, vehicle type, fuel type and road type. Such estimation of greenhouse gas emissions is not reliable. Accordingly, the purpose of this study is, firstly to accumulate activity data based on distance traveled which enables us to accurately estimate the amount of green gas emitted by regional unit(emission point), and secondly, to develop a methodology for estimation of greenhouse gas emissions using these data. To do this, the study utilizes the mileage data of Korea Transportation Safety Authority(TS), statistics of registered motor vehicles, statistical yearbook of traffic volume from the Ministry of Land, Infrastructure and Transport(MLIT), the Korea Transport Database of the Korea Transport Institute(KOTI), and average road speed by local government. Methodology for estimation by local government level(emission point) is meaningful, because it reflects traffic pattern data including flow in and out and internal traffics. Finally, to verify the methodology presented in this study, it is applied to Seoul. Both greenhouse gas estimates, one by multiplying the average mileage and the number of registered vehicles and the other by multiplying traffic volume and road extension, are less than the amount estimated by the methodology presented in this study.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.81-84
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• 2004

본 논문에서는 1대의 CCD카메라로 주행 중 차선과 선행차량을 인식하고 선행차량까지의 거리를 실시간으로 계측하는 알고리즘을 제시하였다. 도로와 카메라간의 기하구조를 분석하여 사영행렬을 추출하였고, 주행 중 차간 거리를 실시간으로 계측하는데 이용하였다. 또한 차선 인식을 위해서 Hough Transform을 적용하여 처리시간을 단축하였다. 도로상의 장애물은 인식된 주행차선 내로 한정하였고 도로 영상에서 수평에지성분을 구한 후 히스토그램 투영을 적용하여 장애물을 검출하였다. 거리가 점차 멀어질수록 계측오차가 증가함을 볼 수 있었으나 기존의 방법에 비하여 주행 중에 운전자가 장애물을 판단하여 제동을 취할 수 있는 정도의 유효한 오차특성을 보였다.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.143-144
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• 2000

급증하는 자동차 수요로 인해 발생되는 배출량 증가는 자동차 운행의 특성상 대도시 대기오염의 주원인으로 작용하고 있다. 자동차 배출오염물질의 배출량 추정에 있어 국내 차량의 배출계수 개발도 시급하지만 우리 나라 자동차 운행패턴에 관한 연구도 같이 병행되어야 한다. 본 연구에서는 Cold start emission과 Evaporative VOC emission의 산정에 있어서 국내 승용차의 1회 주행거리(Trip length)를 이용하여 승용차 부문 배출량 영향정도와 계절별 배출량 변화를 추정하여 보았다. (중략)