• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.687-690
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• 2015

Forward collision warning systems(FCWS) and lane change assist systems(LCAS) need regions of interest for detecting lanes and objects as road regions. Watershed segmentation is effective algorithm that classify the road. That algorithm is split results appear differently depending on Watershed line with local minimum in the early part of the seed. If not road regions or vehicles combined the road's seed, It segment road with the others. For compensate the that defect, It has to adaptive change by road environment. The method is that image segmentate the several of regions of interest. Then It is set in a straight line that is detected in regions of interest. If It was detected cars on seed, seed is adjusted the location. And If It wasn't include the line, seed is adjusted the length for final decision the seed. We can detect the road region using the final seed that selected according to the road environment.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.258-267
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• 2022

Weak over-the-horizon perception and blind spot are the main problems in intelligent connected vehicles (ICVs). In this paper, a V2V image transmission-based road condition warning method is proposed to solve them. The encoded road emergency images which are collected by the ICV are transmitted to the on-board unit (OBU) through Ethernet. The OBU broadcasts the fragmented image information including location and clock of the vehicle to other OBUs. To satisfy the channel quality of the V2X communication in different times, the optimal fragment length is selected by the OBU to process the image information. Then, according to the position and clock information of the remote vehicles, OBU of the receiver selects valid messages to decode the image information which will help the receiver to extend the perceptual field. The experimental results show that our method has an average packet loss rate of 0.5%. The transmission delay is about 51.59 ms in low-speed driving scenarios, which can provide drivers with timely and reliable warnings of the road conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4208-4215
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• 2015

Most of the administrative works are executed based on the address. Therefore, spatial information is an essential factor for administrative works. So far, many systems, which apply spatial information to administrative works, have been implemented. However, there is little approach to apply spatial information to road occupation permit works. In this paper, we introduce system implementation plan for applying spatial information to road occupation permit administrative works. System implementation plan includes work analysis, applying scenarios extraction, system function extraction, and datamart construction plans. First, work processes and activities are defined based on the analysis of work handbook. Also, activities are displayed in diagram. Second, scenarios applying spatial information to road occupation permit works are extracted. Third, we derive service functions for system, which realize work processes and applying scenarios. Finally, spatial information datamart construction plan is established. Proposed system implementation plan in this research includes application architecture and part of data architecture. For implementing the system, plan for hardware and software architecture should be studied.

• 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.

• Journal of Environmental Science International
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• v.13 no.6
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• pp.505-512
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• 2004

This study was attempted to review the information data for minimizing the destruction of environmental naturalness and the visual damage of landscape from road construction by establishing a model of environmental naturalness for national roads in the suburb areas to suggest an answer to a research question, ' hat does decide the environmental naturalness of roadscape?'. We found that 1) The road-side slope showed no statistical significance in the description of environmental naturalness of roadscape, but the fact that the road-side slope from road construction is the destruction of natural topography cannot be overlooked. 2) In terms of the direction of value variations for independent variables, signboard and telegraph post, soundproofing and protection wall, structure, and building acted toward negative (-) direction, while mountains, sky, road trees, fields, and surrounding green including the road-side slope acted toward positive(+) direction. 3) The variable with highest relative contribution to dependent variables among independent variables is building, which has importance as many as 148 times of road-side slope, while the variable road-side slope has the least importance. Building has the importance of 7.22 times, mountains 5.51 times, road trees 2.59 times, surrounding green 2.54 times, structure 2.41 times, signboard and telegraph post 2.37 times, soundproofing and protection wall 2.20 times, and sky 1.32 times of the fields as a standard criterion values 1.

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.427-429
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• 2009

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.291-303
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• 2012

In order to lead safe driving, it is better to provide dynamic and detailed information on how the driver using the relevant road should behave as concerning movements of individual car rather than providing monotone and static information of reducing of speed to unspecified drivers. Assuming road and communication of highway where real-time collection and transfer of information on vehicles and road traffic status is possible, the purpose of this study was to provide real-time safe distance by considering road traffic condition such as road condition and driving condition, travel speed and distance between preceding/following vehicles. We intended to provide basic information about dangerous situation by defining different values of condition based column ($C_{condition}$) in accordance with the road surface condition, based on which Real-time Safety Distance Index(RSDI) is to be calculated comprehensively reflecting speed of preceding and following vehicles, distance between vehicles, vertical alignment and road surface condition on the scope of expression column ($C_n$). We intended to enable the driver to secure safety by providing the calculated Real-time Safety Distance Index (RSDI) so that the driver can intuitively sense and sufficiently cope with a dangerous situation where collision of vehicles may occur. The calculated RSDI value is comprised of 30 unit columns and will be provided to the driver being divided into risk evaluation grades of 3 predetermined steps, 'warning', 'dangerous' and 'normal'.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.245-253
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• 2009

Road facility is the most fundamental infrastructure for traffic and various information for smooth traffic is included in road surfaces. Various information included in road surfaces should be often removed and reinstalled by partial damage and aging. In addition, the existing road surface information should be removed in order to mark new information as traffic information changes. The existing road surface removal method suing grinders and torches had problems such as dangerous working equipment and workers' direct exposure to cars. In addition, although water-jet system using super high-pressure water was used to remove road surface in order of improvement of traditional method, there are another problems such as limitations according to water-tanks and water frost on the road surfaces after work. Therefore, this study analyzes and suggests systems to develop prototype after analyzing dry ice blaster in order to improve the current road surface removal methods. In addition, the study analyzes the possibility of introduction of dry ice blaster through a test for proposing an automatized equipment for new road surface mark removal considering environment and work efficiency, and compare traditional method with introduced dry ice blaster for operating cost.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5987-5992
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• 2013

The authors suggest the extension IFC schema of drainage facilities for the purpose of establishment the information model standard for the roads. IFC entities, types and properties for drainage facilities are defined by the analysis of road design documents for extraction physical component and design information IFC schema is able to be extended through the result of this research. Futhermore, IFC for additional road facilities is able to be used as construction process control, quantity take off, and simulation applications with the interoperability of the IFC.