• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2338-2356
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• 2019

Vehicular ad-hoc network (VANET) is the name of technology, which uses 'mobile internet' to facilitate communication between vehicles. The aim is to ensure road safety and achieve secure communication. Therefore, the reliability of this type of networks is a serious concern. The reliability of VANET is dependent upon proper communication between vehicles within a given amount of time. Therefore a new formula is introduced, the terms of the new formula correspond 1 by 1 to a class special ST route (SRORT). The new formula terms are much lesser than the Inclusion-Exclusion principle. An algorithm for the Source-to-Terminal reliability was presented, the algorithm produced Source-to-Terminal reliability or computed a Source-to-Terminal reliability expression by calculating a class of special networks of the given network. Since the architecture of this class of networks which need to be computed was comparatively trivial, the performance of the new algorithm was superior to the Inclusion-Exclusion principle. Also, we introduce a mobility metric called universal speed factor (USF) which is the extension of the existing speed factor, that suppose same speed of all vehicles at every time. The USF describes an exact relation between the relative speed of consecutive vehicles and the headway distance. The connectivity of vehicles in different mobile situations is analyzed using USF i.e., slow mobility connectivity, static connectivity, and high mobility connectivity. It is observed that $p_c$ probability of connectivity is directly proportional to the mean speed ${\mu}_{\nu}$ till specified threshold ${\mu}_{\tau}$, and decreases after ${\mu}_{\tau}$. Finally, the congested network is connected strongly as compared to the sparse network as shown in the simulation results.

• 대한임베디드공학회논문지
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• 제5권4호
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• pp.243-253
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• 2010

Multihop data delivery in vehicular ad hoc networks (VANETs) suffers from the fact that vehicles are highly mobile and inter-vehicle links are frequently disconnected. In such networks, for efficient multihop routing of road safety information (e.g. road accident and emergency message) to the area of interest, reliable communication and fast delivery with minimum delay are mandatory. In this paper, we propose a multihop vehicle-to-infrastructure routing protocol named Vertex-Based Predictive Greedy Routing (VPGR), which predicts a sequence of valid vertices (or junctions) from a source vehicle to fixed infrastructure (or a roadside unit) in the area of interest and, then, forwards data to the fixed infrastructure through the sequence of vertices in urban environments. The well known predictive directional greedy routing mechanism is used for data forwarding phase in VPGR. The proposed VPGR leverages the geographic position, velocity, direction and acceleration of vehicles for both the calculation of a sequence of valid vertices and the predictive directional greedy routing. Simulation results show significant performance improvement compared to conventional routing protocols in terms of packet delivery ratio, end-to-end delay and routing overhead.

• 한국대기환경학회지
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• 제28권3호
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• pp.233-248
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• 2012

The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

• 대한교통학회지
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• 제35권1호
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• pp.37-49
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• 2017

본 연구에서는 도로이동오염원을 대상으로 추진하는 교통환경정책의 대기질 개선효과 분석 방법론을 제시하였으며, 해당 방법론은 정책 추진에 따른 도로이동오염원의 통행량과 대기오염물질 배출량 변화, 대기오염물질의 공간적 확산과 이로 인한 노출인구의 건강영향을 순차적으로 고려한다. 특히 도로이동오염원의 통행량 변화는 정책 효과와 직접적인 연관이 있기 때문에 대기질 개선효과 분석시 반드시 고려되어야 하며, 본 연구에서는 교통수요모형 기반의 상향식 방법을 적용하여 기존 하향식 방법 대비 정책 추진에 따른 통행자의 통행행태 변화를 상세하게 반영하고자 하였다. 정책 시나리오 분석을 통하여 본 연구에서 제시한 분석 방법론의 활용가능성을 검토하였으며, 통행자의 통행행태 변화가 예상되는 정책의 대기질 개선효과 분석은 본 연구의 분석 방법론 적용이 필요한 것으로 판단된다.

• 대한교통학회지
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• 제34권2호
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• pp.107-122
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• 2016

이 연구는 교통수요모형에 기반한 자동차 배출량 산정 시 존내 배출량이 누락되는 문제를 보완하기 위해, 교통수요모형과 결합하여 활용될 수 있는 존내 배출량 산정 모형을 정립하는데 목적이 있다. 특히 "도시-교통의 상호작용에 기안하여, 도시공간구조는 접근도에 영향을 미치고, 이는 사람들의 통행행태에 영향을 미친다."는 이론에 근거하여, 본 연구는 도시 도로의 구조적인 특성을 정량화할 수 있는 공간 구문론(Space Syntax) 이론 등을 활용하여 존내 통행거리, 존내 통행량, 존내 평균 통행속도, 그리고 이들을 조합한 존내 배출량 추정 모형을 구축하였다. 연구 결과, 도시 공간 구조는 존내 배출 특성에도 영향을 미치는 것으로 나타났으며, 특히 압축도시이고, 대지 면적이 좁고, 난개발 지수가 낮고, 격자형 도시일수록, 존내 자동차 배출량은 적게 배출되는 것으로 나타났다. 지역의 공간적 특성을 반영하여 구축된 본 연구 모형은 기존 모형에 비해 약 44-46% 높은 설명력을 보였다. 이를 수원시 자전거 도로 개선사업에 적용하여 배출 저감량을 산정한 결과, 존간 배출 저감량만 고려한 기존 결과와 비교해 약 2배 높은 배출 저감량이 산정되었다. 본 연구결과는 국가 배출량 산정에의 활용 및 다양한 교통-환경 정책의 효과 평가에도 유용하게 활용될 수 있을 것으로 기대된다.

• 한국대기환경학회지
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• 제25권3호
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• pp.219-236
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• 2009

Particle-phase organic tracers (molecular markers) have been shown to be an effective method to assess and quantify the impact of sources of carbonaceous aerosols. These molecular markers have been used in chemical mass balance (CMB) models to apportion primary sources of organic aerosols in regions where the major organic aerosol source categories have been identified. As in the case of all CMB models, all important sources of the tracer compounds must be included in a Molecular Marker CMB (MM-CMB) model or the MMCMB model can be subject to biases. To this end, the application of the MM-CMB models to locations where reasonably accurate emissions inventory of organic aerosols are not available, should be performed with extreme caution. Of great concern is the potential presence of industrial point sources that emit carbonaceous aerosols and have not been well characterized or inventoried. The current study demonstrates that emissions from industrial point sources in the St. Louis, Missouri area can greatly bias molecular marker CMB models if their emissions are not correctly addressed. At a sampling site in the greater St. Louis Area, carbonaceous aerosols from industrial point sources were found to be important source of carbonaceous aerosols during specific time periods in addition to common urban sources (i.e. mobile sources, wood burning, and road dust). Since source profiles for these industrial sources have not been properly characterized, method to identify time periods when point sources are impacting a sampling site, needs to avoid obtaining biases source apportionment results. The use of real time air pollution measurements, along with molecular marker measurements, as a screening tool to identify when point sources are impacting a receptor site is presented.

• 한국대기환경학회지
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• 제19권6호
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• pp.805-810
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• 2003

The annual air pollution emissions from construction and agricultural equipments were estimated from 1987 through 2000. The annual numbers and operation hours of 5 major construction equipments (Excavator, Bulldozer, Loader, Fork lift, Crane) and 3 major agricultural equipments (Power Tiller, Agricultural Tractor, Combine) were investigated for emission estimation. And monthly variation factors of operation hours of construction equipment were investigated too. The NO$_{x}$ emission from construction equipment have been gradually increased since 1987 to 1997, but sharply decreased as -45％ in 1998 due to economic crisis in Korea. The NO$_{x}$ emission was estimated as 64,300 ton/year from construction equipment, and as 23,300 ton/year from agricultural equipment in 2000.000.

• 도시과학
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• 제11권2호
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• pp.45-54
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• 2022

Recently, regulations on automobile exhaust gas emission are being strengthened. Accordingly, automobile exhaust gas emissions are expected to decrease and continue to decrease. On the other hand, many countries do not yet consider the emission of non-exhaust air pollutants from automobiles as important. Automobile non-exhaust substances are classified into three categories: tire dust emissions, brake wear emissions, and road scattering dust. In particular, in the case of tire dust, research results exist that pollutant emissions increase as the weight of a vehicle increases. Since the weight of trucks varies according to the load and the load along the axles is also different, it can be expected that the emission of PM10 from the tire dust will be different depending on the loading method. Therefore, this study was conducted on the amount of PM10 generated in tire dust considering the axle load of the truck according to the loading method. However, it was confirmed that the total amount of PM10 was less than that all loads are loaded in the front or rear when the load was evenly distributed in the front and rear of the cargo compartment. In particular, if the load is distributed evenly in the front and back of the cargo compartment and the load in the front part is divided into 2 to 6 and loaded, as the number of divided loading increases the amount of PM10 generated decreases. And when the load is divided into 6 pieces, the total amount of PM10 generated is 0.3952g, the minimum value. If the load is divided into 6 or more and loaded evenly, the total PM10 generated continuously increases and converges to about 0.3964g.

• 한국분무공학회지
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• 제23권2호
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• pp.81-89
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• 2018

The objective of this study is to estimate the level of exposure of traffic-related air pollutants (TRAPs) on the pedestrians in Seoul area. The road network's link-based pollutant emission was calculated by using a set of mobile source emission factor package and associated activity information. The population information, which is the number of pedestrian, was analyzed in conjunction with the link-based traffic emissions in order to quantify exposure level by selected 23 spots. We proposed the Exposure Intensity, which is defined by the amount of traffic emission and the population, to quantify the probability of exposure of pedestrian. Link-based traffic NOx and PM emissions vary by up to four times depending on the location of each spot. The Hot-spots is estimated to be around 1.8 times higher Exposure Intensity than the average of the 23 selected spots. The information of Exposure Intensity of each spot allows us to develop localized policies for air quality and health. Even in the same area, the Exposure Intensity over time also shows a large fluctuation, which gives suggestions for establishing site-specific counter-measures.