• Journal of the Economic Geographical Society of Korea
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• v.16 no.2
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• pp.262-274
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• 2013

Heavy rain and heavy snow as representative extreme weather are recently an issue in urban area. The paper aims at modeling the scenarios of evacuation that minimizes economic loss of the designated urban area with improving travel efficiency by providing road closure information facing an extremely heavy rainfall. The paper develops a model by using a NetLogo toolkit applied to the study area of Seocho-dong, Seocho-gu, Seoul. The model conducts a simulation of travel time under different scenarios of information provision. The simulation results show that it is efficient to provide the information of road closure to 20~40% of the drivers under the scenario of humid road or rainfall less than 20mm, whereas to 40~60% of the drivers under the scenario of heavy rainfall more than 20mm.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.87-94
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• 2005

3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.193-202
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• 2021

The update of a high-precision map was carried out by modifying the geometric information using ortho-images or point-cloud data as the source data and then reconstructing the relationship between the spatial objects. These series of processes take considerable time to process the geometric information, making it difficult to apply real-time route planning to a vehicle quickly. Therefore, this study proposed a method to update the road network for route planning using a graph data structure and storage type of graph data structure considering the characteristics of the road network. The proposed method was also reviewed to assess the feasibility of real-time route information transmission by applying it to actual road data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4419-4441
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• 2016

A cause of vehicle accidents is the reduced visibility due to bad weather conditions such as fog. Therefore, an onboard vision system should take visibility detection into account. In this paper, we propose a simple and effective approach for measuring the visibility distance using a single camera placed onboard a moving vehicle. The proposed algorithm is controlled by a few parameters and mainly includes camera parameter estimation, region of interest (ROI) estimation and visibility computation. Thanks to the ROI extraction, the position of the inflection point may be measured in practice. Thus, combined with the estimated camera parameters, the visibility distance of the input foggy image can be computed with a single camera and just the presence of road and sky in the scene. To assess the accuracy of the proposed approach, a reference target based visibility detection method is also introduced. The comparative study and quantitative evaluation show that the proposed method can obtain good visibility detection results with relatively fast speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1842-1847
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• 2006

This paper is the environmental impact assessment of at road design in the light of the sense for the real from the virtual reality. For In this papers, This study developed 3D-model and virtual reality contents by suggesting the environmental impact assessment based on GIS in the road design. Ant through this process, it's possible to visualize the environmental impact assessment by constructing the 3D-model and simulation. The 3D-model can be a method to show the road effectively by maximizing the road's shape visually after the construction. The main construction which composes polyhedron model that is generated from digital map and aerial photo is built by mapping the real texture, so the Sense for the Real was more heightened. Through this study, it must be made to shorten a long time exhausting period of conference and construct more real road after due scene consideration by specific and various low-cost strategy in the environmental impact assessment afterwards.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.327-330
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• 2016

In the road environment with lots of vehicles, we can increase the number of vehicles on the road (i.e., road capacity) and enhance the comfortability of drivers if vehicles are organized into platoons. In the traditional vehicle platooning mechanisms, a pre-determined set of vehicles are allowed to form a platoon and, among them, a specific vehicle is designated as the platoon leader. In this type of platoon mechanisms, platoon is limited in improving the road capacity because the vehicles allowed to involve into platooning are restricted. Therefore, in this paper, we propose an adaptive platoon formation mechanism that allows any vehicle to be a platoon leader from which a platoon is formed. In the proposed mechanism, a platoon leader is elected based on the relative velocity and location information of neighboring vehicles obtained through the periodic exchange of beacon messages among vehicles. Through the NS-3 based simulations, we show the performance of our proposed mechanism in terms of road capacity improvement.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.195-204
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• 2008

When the drivers try to read an information on road signs, they can reach their destinations successfully. In this situation, human factors, road signs and geometric condition regarded as the most important factors for a safe driving should be a well-balanced relationship mutually. This research aims to prove the factors obstructing a safe driving, while drivers try to read an information on road signs for the next destination. For this sake, driving simulator was used and human factors, road signs etc. were considered in this experiment. The statistical analysis indicated what factors disturb a safe driving. The probability function using a Logistic Model was presented in this study. This result and experience will be used as a basic data in designing better road signs.

• Spatial Information Research
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• v.17 no.2
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• pp.213-222
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• 2009

Finding exclusive closest pairs in road network is very useful to real applications such as, for example, finding a closest pair between a passenger and a nearby taxi in a road network. Few studies, however, have been interested in this problem. To match two close moving objects exclusively, one object must belong to only one result pair. Because moving objects in a road network change their position continuously, it is necessary to monitor closest pair results. In this paper, we propose a methodology to monitor k exclusive closest pairs via a road network. Proposed method only updates the results which are influenced by objects' movement. We evaluated the performance of the proposed method with various real road network data. The results show that our method produces better accuracy than normal batch processing methods.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.123-131
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• 2011

This study proposes a model for road surface temperature prediction on basis of the heat-energy balance equation between atmosphere and road surface. The overall model is consisted of two types of modules: 1) Canopy 1 is used to describe heat transfer between soil surface and atmosphere; and 2) Canopy 2 can reflect the characteristics of pavement type. Input data used in the model run is obtained from the Korea Meteorological For model validation, the observed and predicted surface temperature data are compared using data collected on MoonEui Bridge along CheongWon-Sangju Expressway, and the comparison is made on winter and other seasons separately. Analysis results show that average difference between two temperatures lies within ${\pm}2^{\circ}C$ which is considered as appropriate from a micrometeorology point of view. The model proposed in this paper can be adopted as a useful tool in practical applications for winter maintenance. This study being a fundamental research is anticipated to be a starting point for further development of robust surface road temperature prediction algorithms.