• 로봇학회논문지
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• 제9권4호
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• pp.206-215
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• 2014

Acoustic signal is crucial for the autonomous navigation of underwater vehicles. For this purpose, this paper presents a method of acoustic source localization. The proposed method is based on the probabilistic estimation of time delay of acoustic signals received by two hydrophones. Using Bayesian update process, the proposed method can provide reliable estimation of direction angle of the acoustic source. The acquired direction information is used to estimate the location of the acoustic source. By accumulating direction information from various vehicle locations, the acoustic source localization is achieved using extended Kalman filter. The proposed method can provide a reliable estimation of the direction and location of the acoustic source, even under for a noisy acoustic signal. Experimental results demonstrate the performance of the proposed acoustic source localization method in a real sea environment.

• 대한원격탐사학회지
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• 제38권1호
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Journal of Biosystems Engineering
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• 제26권6호
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• pp.503-508
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• 2001

In this paper, time-fiequency analysis and multi-dimensional spectral analysis methods are applied for source identification and diagnosis of non-stationary sound/vibration signals. Sound or vibration problems of general vehicle and agricultural machinary are under 500 Hz. So We used linearly increased chirp signals under 500 Hz. By checking the coherences on concerned time, fur time-variant non-stationary signals, this simulation it very well coincident to expected results.

• 한국자동차공학회논문집
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• 제15권2호
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• pp.58-64
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• 2007

As the concerns regarding global worming were increased, the pressure of greenhouse gas(GHG) emission reduction on mobile source was also increased. Carbon dioxides contribute over 90% of total GHG emission and the mobile source occupies about 20% of this $CO_2$ emission. Therefore automotive exhaust is suspected to be one of the major reasons of the rapid increase in greenhouse effect gases in ambient air. In this study, in order to investigate $CO_2$ emission characteristics from gasoline passenger cars(PC), which is the most dominant vehicle type in Korea, 106 vehicles were tested on the chassis dynamometer. $CO_2$ emissions and fuel efficiency were measured. The emission characteristics by displacement, gross vehicle weight, vehicle speed and CVS-75/vehicle speed mode were discussed. Test modes were vehicle speed modes and CVS-75 mode that have been used to develop emission factors and to regulate for light-duty vehicle in Korea. It was found that $CO_2$ emissions showed higher large displacement, heavy gross vehicle weight, low vehicle speed and CVS-75 mode than small displacement, light gross vehicle weight, high vehicle speed and vehicle speed mode, respectively. From these results, correlation between $CO_2$ emission and fuel efficiency was also determined. The results of this study will contribute to domestic greenhouse gas emissions calculation and making the national policy for climate change.

• 한국환경과학회지
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• 제14권6호
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• pp.543-553
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• 2005

In recent days, photochemical smog due to the rapid industry development and vehicle increasement has become a critical pollutant in the metropolitan area and the number of ozone alarm signal has increased every year. This research was performed to evaluate VOCs emission source characteristics and concentration of VOCs in Daegu. The site average concentration was observed in the following order: industrial area > commercial area > residential area. Most of the VOCs species except toluene showed variations with higher concentration during nighttime, and lower concentration during the daytime. The major VOCs of stationary emission source were BTEX(benzene, toluene, ethylbenzene. xylene) and methylene chloride, trichloroethene and styrene. Also, those of automobile exhaust were toluene and benzene. Also, the major VOCs concentration emited by the vehicle fuel was observed in the following order: gasoline > light oil > liquefied petroleum gas (L.P.G). Correlation coefficients values were estimated between major VOCs such as toluene, ethylbenzene, m,p-xylene, o-xylene. Results showed that correlation coefficient values were significant magnitude above 0.76. Also, there showed highly significant correlations among ethyl benzene, m,p-xylene, and o-xylene concentration(Pearson correlation coefficients, r=0.868-0.982). Calculated correlation coefficients among commercial area,industrial area and residential area were 0.934-0.981, they showed high correlation. There showed highly correlation between stationary emission source and industrial area, compared with commercial area and residential area. Also, calculated correlation coefficients among commercial area, industrial area, residential area and automobile exhaust were 0.732, 0.725, 0.777, respectively.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.365-370
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• 2011

Structure-bone noise is an important aspect to consider during the design and development of a vehicle. Reduction of structure-bone noise of the compartment in a vehicle is an important task in automotive engineering. Many methods which analyze transfer path of noise have been used for structure-bone noise. The existing method to measure of frequency response function of transfer path has been tested by removing a source. This Paper presents an experimental analysis about Transfer Path Analysis of the vehicle interior noise according to Excitation or not. To identify these points of difference, experiment were conducted through an experimental test using simulation vehicle.

• 한국산학기술학회논문지
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• 제10권7호
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• pp.1735-1739
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• 2009

지상무인 전투체계에서 요구되는 원천, 핵심기술은 해외 선진 국가들과의 치열한 경쟁이 예상된다. 따라서 주요 국가의 무인체계 기술개발현황을 분석하였으며, 분석 대상은 1998년부터 2008년까지 미국, 일본, 유럽, 캐나다, 이스라엘 등에 출원된 현황을 기준하였다. 주요 선진국의 특허맵과 전문가 의견을 수렴하여 국가별 기술 수준, 역점분야와 공백기술, 시장력 등을 분석하였으며, 앞으로 발전 가능성이 예상되는 기술과 우리나라가 중점 개발하여야할 분야 등을 제시하였다.

• 한국산업융합학회 논문집
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• 제13권2호
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• pp.85-92
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• 2010

This study shows the path generation algorithm for an UGV (Unmanned Ground Vehicle). The developed UGV frame which has a 4-wheel driven mechanism and diesel source is applied. Proposed vehicle system in this research is aimed to military purpose. To achieve the unmanned autonomous driving, following two main issues are considered. First, behavior module for positioning and posture of vehicle system and second, cognition module to receive the information from environment are proposed and verified. To do this, rover which can acquire the positioning information from earth coordinate and IMU (Inertial Measurement Unit) which can measure the posture are combined to design the path planning algorithm.

• 한국환경과학회:학술대회논문집
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• 한국환경과학회 2003년도 International Symposium on Clean Environment
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• pp.216-225
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• 2003

Fine particles with aerodynamic diameter less than 2.5 ${\mu}m$ (PM2.5) were collected from three sites in Beijing during April, August, and November 2000 and January 2001. After chemical components in samples are analyzed, a chemical mass balance (CMB) receptor model using PARs as tracers is applied to quantify the source contributions to PM2.5 in Beijing. The results show that the major sources are coal combustion, fugitive dust, vehicle exhaust, secondary sulfate and nitrate, and organic matter while biomass burning and construction dust contribute only a small fraction. In addition, source inventory in Beijing is used to determine the primary source contributions. The two methods result in comparable results. Source apportionment at three sampling sites presents similar contributions to PM2.5 although the sites are far away from each other. However, distinct seasonal pattern is presented for the source contributions from coal combustion, fugitive dust, biomass burning, secondary sulfate and nitrate.

• 한국멀티미디어학회논문지
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• 제19권12호
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• pp.1909-1918
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• 2016

This paper presents a unified framework for joint Convolutional Neural Network (CNN) based vehicle detection by leveraging multi-spectral image pairs. With the observation that under challenging environments such as night vision and limited light source, vehicle detection in a single color image can be more tractable by using additional far-infrared (FIR) image, we design joint CNN architecture for both RGB and FIR image pairs. We assume that a score map from joint CNN applied to overall image can be considered as confidence of vehicle existence. To deal with various scale ratios of vehicle candidates, multi-scale images are first generated scaling an image according to possible scale ratio of vehicles. The vehicle candidates are then detected on local maximal on each score maps. The generation of overlapped candidates is prevented with non-maximal suppression on multi-scale score maps. The experimental results show that our framework have superior performance than conventional methods with a joint framework of multi-spectral image pairs reducing false positive generated by conventional vehicle detection framework using only single color image.