• Asian Journal of Atmospheric Environment
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• v.8 no.2
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• pp.81-88
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• 2014

Noise-barriers on both sides of the roadway (hereafter referred to as double noise-barriers), are a common feature along roads in Korea, and these are expected to have important effects on the near-road air pollution dispersion of vehicle emissions. This study evaluated the double noise-barrier impact on near-road air pollution dispersion, using a FLUENT computational fluid dynamics (CFD) model. The realizable k-${\varepsilon}$ model in FLUENT CFD code was used to simulate vehicle air pollutant dispersion, in around 11 cases of double noise-barriers. The simulated concentration profiles and surface concentrations under no barrier cases were compared with the experimental results. The results of the simulated flows show the following three regimes in this study: isolated roughness (H/W=0.05), wake interface (H/W=0.1), and skimming flow (H/W>0.15). The results also show that the normalized average concentrations at surface (z=1 m) between the barriers increase with increasing double noise-barrier height; however, normalized average concentrations at the top position between the barriers decrease with increasing barrier height. It was found that the double noise-barrier decreases normalized average concentrations of leeward positions, ranging from 0.8 (H/W=0.1, wake interface) to 0.1 (H/W=0.5, skimming flow) times lower than that of the no barrier case, at 10 x/h downwind position; and ranging from 1.0 (H/W=0.1) to 0.4 (H/W=0.5) times lower than that of the no barrier case, at 60 x/h downwind position.

• Spatial Information Research
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• v.19 no.6
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• pp.111-121
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• 2011

In this paper, we proposes a sensor node positioning algorithm that utilizes the geo-spatial elements and considers the factors to represent the propagation loss generated by the various obstacles in the urban wireless environments. First, we measures the propagation loss about the radio frequencies in major road of the urban, and defines the correlation between the measured loss and the environment information for the road and its surrounding get from Urban GIS. Secondly, through the utilization of the loss-environment correlation, we describes the detailed instruction for requiring the radio coverage decision and deploy system implementation for the wireless sensor node in urban. By the consideration of interference factor by the building and the linear structure of road, we can evaluate the path loss below 5dB RMS error. And, we proposes the way to revise the sensor node deployment based on the corelation and the measured path loss.

• Korean Journal of Environment and Ecology
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• v.29 no.2
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• pp.184-191
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• 2015

This study aimed to analyze characteristics of the seasonal habitat use of reintroduced Long-tailed Gorals (n=7) in Woraksan (mountain) National Park. We collected 10,721 goral coordinates in Woraksan (mountain) National Park via transmitters, and analyzed habitat use (e.g., aspect, distance from stream and road) from November 2006 to January 2013. Aspect use was southwest (22.6 %), and seasonal aspect use had a southwestern slope (in the spring, summer, and autumn). A northwestern aspect was detected in winter, but slope of $30^{\circ}{\sim}35^{\circ}$ (19.0 %) was used regardless of the season and mean elevation use was 500 m. Moreover, seasonal use was higher in the summer and lower in the winter and spring. The distance from the stream was mainly 50 m in 17.2 %, except in the winter (distance of 300 m), and it was within 50 m in the spring, summer, and autumn. The distance from the road was 100 m in 25.7 %, and seasonal use was within 100 m except for the winter. Thus, we examined significant differences in the habitat use of reintroduced gorals in Woraksan (mountain), and provide elementary data for habitat stabilization of Woraksan (mountain) National Park where goral restoration has advanced.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.97-110
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• 2020

This study conducted observations at 72 traffic lights and road signs in Sejong-si, Korea from March to June 2019 in order to analyze nest-site, nest-site characteristics and feeding behavior in Tree sparrow (Passeer montanus) in urban. Feeding behavior during breeding season in 2019 was investigated at 10 Town representing traffic facilities installed on the road located in the center of the city and 10 Riverside Geumgang river's riverside road. We fitted both general linear model and regression model to our field data and estimated the spatial variation of initial date of the first feeding (i.e., being date of breeding) and the total number of caterpillar fed by parents per hour. Our results showed that the frequency of nest building on artificial structures, such as traffic lights, was about 26% higher and about 8 days earlier in the riverside. In particular, the first feeding was significantly faster when the nearest distance between nest to green field as foraging site was shorter whereas there was no significant effect of the number of nest within 50 meters on the first feeding. Number of caterpillars fed by parents was higher in the Riverside than in the Urban, and especially the number in the second brood was sharply decreased in the Urban. As we estimated average amount of caterpillars per hour to 446 traffic safety facilities in Sejong-si, it was estimated that Tree sparrows fed 18,742.8 caterpillars per hour during the breeding season. In this study, we showed that characteristics of nests built in artificial structures and feeding behavior in order to analyze effects of environmental condition in urban on life-history traits during the breeding season. Finally, we discussed the conservation of birds in urban and pest control effects.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.6
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• pp.1-13
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• 2009

The purpose of this study is to investigate the applicability of the CIE standard on lighting environments to Korea. In the field study, horizontal and the vertical illuminance was measured at the pedestrian road in the central business district of a city, and the questionnaires were conducted to get information regarding pedestrian's satisfaction with lighting environment. Four areas were selected for this survey. That areas have different type of pedestrian roads concerning the lighting conditions and the number of walkers. From the results of the measurements, It is known that the illuminance of pedestrian roads is different according to the lighting conditions and the number of poot passengers. Also the results of questionnaires show that the illuminance of the pedestrian roads affect to the pedestrian's satisfaction. Lastly, the CIE standard on lighting environments is applicable to the central business district of the cities in Korea.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.348-355
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• 2021

Asphalt, widely used for road pavement, has different required physical properties depending on the environment to which the road is exposed. Therefore, it is essential to maximize the life of asphalt roads by evaluating the physical properties of asphalt according to additives and selecting an appropriate formulation considering road traffic and climatic environment. Dynamic shear rheometer(DSR) test is mainly used to measure resistance to rutting among various physical properties of asphalt. However, the DSR test has limitations in that the results are different depending on the experimental setting and can only be measured within a specific temperature range. Therefore, in this study, to overcome the limitations of the DSR test, the rheological characteristics were predicted by learning the images collected from atomic force microscopy. Images and rheology properties were trained through EfficientNet, one of the deep learning architectures, and transfer learning was used to overcome the limitation of the deep learning model, which require many data. The trained model predicted the rheological properties of the asphalt binder with high accuracy even though different types of additives were used. In particular, it was possible to train faster than when transfer learning was not used.

• Journal of Auto-vehicle Safety Association
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• v.10 no.4
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• pp.33-39
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• 2018

Recently, the automobile industry has developed ADAS (Advanced Driver Assistance System) to prevent traffic accidents and reduce driver's driving burden. Among the ADAS, the LKAS (Lane Keeping Assistance System) is a support system for the convenience and safety of the driver, and the main function is to maintain the driving lane of the vehicle. LKAS is a system that uses radar sensor and camera sensor to collect information about the position of the vehicle in the lane and to support keeping the lane through control if necessary. In many countries, LKAS has already been commercialized and the convenience and safety of drivers have been improved. The international LKAS evaluation test procedure is being developed and discussed by standardization committees such as the ISO (International Organization for Standardization) and the Euro NCAP (New Car Assessment Program). In Korean, the LKAS test method is specified in the KNCAP (Korean New Car Assessment Program), but the evaluation method is not defined. Therefore, the LKAS test procedure that meets international standards and is suitable for domestic road environment is necessary. In this paper, development of LKAS test evaluation scenarios that meets international standards and considering domestic road environment, and the formula that can evaluate the result value after control as the relative distance of lane and the front wheel are suggested. And a comparative analysis was conducted to verify the validity of the suggested scenario and formula. The test evaluation was conducted using the vehicle equipped with the LKAS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.865-870
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• 2023

Recently, accidents caused by black ice, a road freezing phenomenon caused by natural power, are increasing. Black ice is difficult to identify directly with the human eye and is more likely to misunderstand it as standing water, so there is a high accident rate caused by car sliding. To solve this problem, this paper presents a method of detecting black ice centered on LiDAR sensors. With a small, inexpensive, and high-accuracy light detection and ranging (LiDAR) sensor, the temperature and inclination angle are set differently to detect black ice and asphalt by setting different reflection angles of asphalt and black ice differently in temperatures and inclinations. The LIDARO carried out in the study points out that additional research and improvement are needed to increase accuracy, and through this, more reliable black ice detection methods can be suggested. This method suggests a method of detecting black ice through early system design research by preventing accidents caused by black ice in advance.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.