• Journal of Veterinary Clinics
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• v.31 no.4
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• pp.282-287
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• 2014

The negative impacts of roads on wildlife mortality have been well documented, and one of the most significant impact is wildlife-vehicle collisions (WVCs) in most countries throughout the world. While road impacts on wildlife are a truly global concern with a large socio-economic cost, few researches in Korea have been quantified road-kill occurrence on highways or identified extensively seasonal and geographic patterns of this phenomenon. Therefore, we analyzed highway mortality of wild mammals in Korea using database from five years of nation-wide data on WVCs, and estimated road-kill density by standardizing on per km and per $10^3$ vehicle basis. During 2008 through 2012, a total of 10,940 wildlifes were reported killed on highways, with an average of 2,188 cases per year. There were 2,376 road-kills in 2012, and this equates to 0.01 road-kills per km per week or one road-kill every 88.5 km per week. For time of day, road-kills occurred more frequently in the early morning (05:00-08:00, 38.3%), and day of week did not have a significant influence in any individual year. The road-kill was highest in the spring (March- May, 33.0%) and least in the winter (December-February, 16.1%), and the most frequently killed native species were of Korean water deer (79.7%), raccoon dog (12.7%), Korean hare (3.1%), and leopard cat (1.2%). The overall standardized kill-rate (number/10 km/1,000 vehicles/month) in 2012 was 0.057 with highest on Dangjinyeongdeok highway (0.476), followed by Yeongdong (0.274), Sooncheonwanju (0.233), Iksanpohang (0.187), and Joongang (0.150). This study highlights that the frequency of WVCs are prevalent throughout the highways in Korea. Further work is needed to determine whether such a level of mortality is sustainable from an ecological point of view.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.19-28
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• 2015

In this paper, we proposed an algorithm for the identification of relieving or worsening current traffic congestion using historic traffic congestion patterns. Historical congestion patterns were placed in an adjacency list. The patterns were constructed to represent spatial and temporal length for status of a congested road. Then, we found information about historical traffic congestions that were similar to today's traffic congestion and will use that information to show how to change traffic congestion in the future. The most similar pattern to current traffic status among the historical patterns corresponded to starting section of current traffic congestion. One of our experiment results had average error when we compared identified changes of the congestion for one of the sections in the congestion road by using our proposal and real traffic status. The average error was 15 minutes. Another result was for the long congestion road consisting of several sections. The average error for this result was within 10 minutes.

• Journal of the Korean Institute of Rural Architecture
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• v.10 no.2
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• pp.45-52
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• 2008

The purpose of this study is to clarify the actual condition of the road station in japan. The thorough investigation and observation works were made from the view points of the location and service facilities of the road station in kanto area. This article discusses about the basic characteristics of the road stations and actual condition of service facilities of 126 road stations in kanto area. The results of this study are summarized as follows; The main patterns of the site by locational conditions are classified in five types. Those are mountain district type, traffic point type, urban district type, riverside type and seaside type. In planning of road stations, locational condition and regional difference of public facilities are crucial factors.

• International Journal of Highway Engineering
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• v.19 no.3
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• pp.19-30
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• 2017

PURPOSES : This study proposes the road asset valuation approach using alternative depreciation methods. It has become necessary to have asset management system according to the adoption of accrual basis accounting for governmental financial reporting and the amendment of the road act. Therefore, it is very important to analyze the effect of depreciation methods on road asset value as a basic research for road asset management system. METHODS : The Ministry of Strategy and Finance (MOSF) has mainly performed road asset valuation based on Write down Replacement Cost and Straight Line depreciation method. This study suggests some appropriate asset valuation methods for road assets through case analysis using three depreciation methods: Consumption-based depreciation method, Condition-based depreciation method, and Straight Line depreciation method. A road asset valuation data of national highway route 1 (year 2014) is used to analyze the effect of three depreciation methods on the road asset value. Road assets include land and structures (pavement, bridge, and tunnel). This study mainly focuses on structures such as bridges and tunnels, because according to governmental accounting standards, land and road pavement assets do not depreciate. RESULTS : The main results of this study are as follows. Firstly, overall asset value of national highway route 1 was estimated at 6.97 trillion KRW when MOSF's method (straight-line depreciation method) is applied. Secondly, asset value was estimated at 4.85 trillion KRW on application of consumption-based depreciation method. Thirdly, asset value was estimated at 4.37 trillion KRW when condition-based depreciation method is applied. Therefore, either consumption-based or condition-based depreciation methods would be more appropriate than straight-line depreciation method if we can use the condition data of road assets including land that are available in real time. CONCLUSIONS : Since road assets such as pavements, bridges, and tunnels have various patterns of deterioration and condition monitoring period, it is necessary to consider a specific valuation method according to the condition of each road asset. Firstly, even though road pavements do not depreciate, asset valuation through condition-based depreciation method would be more appropriate when requirements for application of non-depreciation approach are not satisfied. Since bridge and tunnel facilities show various patterns of deterioration and condition monitoring period by type and condition level, consumption-based depreciation method based on deterioration model would be appropriate. Therefore, it is necessary to have a reasonable asset management system to apply condition-based depreciation method and a periodic condition investigation to manage road assets well.

• International Journal of Automotive Technology
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• v.7 no.3
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• pp.269-276
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• 2006

Running tests on roads were conducted to clarify the influences of road infrastructure, traffic condition and vehicle's emission level to the amount of emission at local roadsides, and to reveal the operation patterns which can reduce the emission peaks. NOx emission peaks of two light duty freight diesel vehicles which have different emission levels were evaluated by using an on-board measurement system. Tests were carried out with various payload conditions and road conditions. As a result many NOx emission peaks were observed when the vehicles were starting or accelerating at intersections. The test vehicle which has higher emission level caused higher frequency and level of NOx emission peaks. Shifting up at lower engine speed in combination with lower acceleration brought out not only reduction of NOx emission peaks level but also of $CO_2$ mass emission.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.2
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• pp.1-15
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• 1995

The driving patterns in Seoul metropolitan area were surveyed in an experiment involving 1,212km of driving along seventeen representative routes. The speed and fuel consumption data were recorded and the influence of driving patterns on vehicle fuel economy was analyzed by statistical techniques. The results showed that characteristics of driving in Seoul metropolitan area are far different from that of CVS-75 mode and then on-road fuel economy in Seoul may be small as compared with that of CVS-75 mode. Finally, it was proposed that CVS-75 mode fuel economy should be modified by applying adjustment factor to represent actual on-road fuel economy.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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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.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.145-154
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• 2006

Each part of drum brake system is loaded by continual mechanical force and thermal force every time of braking, so enough strength and stability are required. Thermal characteristic is one of the important factors in drum brake systems design. This paper presents the thermal performance such as temperature distribution and thermal contact stress of drum brake system considering several braking patterns; 80th heat braking test mode, heat fade braking test mode, general road mode, steep slope road mode and off road mode. Transient heat transfer analysis and Thermo elastic contact analysis is executed to obtain the temperature distribution, and to evaluate thermal stress of drum brake by using ABAQUS/Standard code. This procedure of analysis can effectively be used to improve the quality problem of brake system and to get design guideline of the new product.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.