• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.335-341
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• 2018

The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.1-10
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• 2007

In this paper, we propose an indexing method for efficiently updating current positions of moving objects on road networks. The existing road network models increase update costs when objects move to adjacent road segments because their connectivity is not preserved. We propose an intersection based network model and a new index structure to solve this problem. The proposed intersection based network model preserves network connectivity through splitting road networks to contain intersection nodes always. The proposed index structure In our experiments, we show that our method is about 3 times faster than an existing index structure in terms of update costs.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.727-742
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• 2020

Point cloud-based 3D maps can obtain many kinds of information for maintenance work on forest road networks. This study was conducted to compare the importance of each factor to select the factors required for the mapping of 3D forest road maps. This can be used as basic data for attribute information required to maintain forest road networks. The results of this study found that out of a total of 30 indexes extracted for mapping 3D forest roads, a total of 21 indexes related to stakeholder groups were significantly different. The importance of the index required by the civil service group was significantly higher than that of the other groups overall. In the case of the academic group, the index importance for cut slope, fill slope, and drainage facility was significantly higher. On the other hand, the index importance for the forestry cooperative and forest professional engineer group was mostly distributed between the civil servants' group and the academic group. In particular, the type of drainage system showed the highest value among the detailed indexes. Overall, drainage related factors in this survey had high coefficient values. The impact of water on forest roads was the most important part in road maintenance. In addition, the soil texture had a high value in relation to slope stability. This is thought to be because the texture of the soil affects the stability of the slope.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.106-118
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• 2019

In recent years, research and development on image object recognition using artificial intelligence have been actively carried out, and it is expected to be used for road maintenance. Among them, artificial intelligence models for object detection of road surface are continuously introduced. In order to develop such object recognition algorithms, a backbone network that extracts feature maps is essential. In this paper, we will discuss how to select the appropriate neural network. To accomplish it, we compared with 4 different deep neural networks using 6,000 road surface damage images. Based on three evaluation methods for analyzing characteristics of neural networks, we propose a method to determine optimal neural networks. In addition, we improved the performance through optimal tuning of hyper-parameters, and finally developed a light backbone network that can achieve 85.9% accuracy of road surface damage classification.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.259-266
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• 2005

Recently data centric routing or application dependent routing protocols are emerged in mobile ad hoc networks. In this paper, we propose a routing method for query processing in MANET(Mobile Ad hoc NETwork) environment, called road-based query routing, with consideration on real time traffic information of large number of vehicles. In particular, we focus on the method that process arrival time dependent shortest path query in MANET without a central server on the road networks. The main idea of our approach lies in a routing message that includes query predicates based on the road connectivity and on data gathering method in real time from vehicles on the road by ad-hoc network. We unify route discovery phase and data delivery(query processing) phase in our mechanism and reduce unnecessary flooding messages by pruning mobile nodes which are not on the same or neighboring road segments. In order to evaluate the performances of the proposed method, we established a model of road networks and mobile nodes which travel along the roads. The measurement factor is the number of nodes to whom route request is propagated according to each pruning strategy. Simulation result shows that road information is a dominant factor to reduce the number of messages.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.109-120
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• 2006

This paper addresses techniques for predicting a future path of an object moving on a road network. Most prior methods for future prediction mainly focus their attention on objects moving in Euclidean space. A variety of applications such as telematics, however, deal with objects that move only over road networks in most cases, thereby requiring an effective method of future prediction of moving objects on road networks. In this paper, we propose a novel method for predicting a future path of an object by analyzing past trajectories whose changing pattern is similar to that of a current trajectory of a query object. We devise a new function that measures a similarity between trajectories by reflecting the characteristics of road networks. By using this function, we predict a future path of a given moving object as follows: First, we search for candidate trajectories that contain subtrajectories similar to a given query trajectory by accessing past trajectories stored in moving object databases. Then, we predict a future path of a query object by analyzing the moving paths along with a current position to a destination of candidate trajectories thus retrieved. Also, we suggest a method that improves the accuracy of path prediction by regarding moving paths that have just small differences as the same group.

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.85-98
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• 2023

Flood is one of the most frequent natural disasters worldwide. In Korea, the probability of urban flooding is greatly increasing due to complex factors such as global warming, an increase in impervious areas, and limitations in expanding water supply facilities in existing urban areas. However, large-scale civil engineering works to prevent urban inundation are socially and economically difficult to obtain national consent. Recently the importance of resilience, which is the ability to return to the original state after a disaster through rapid recovery while preparing for natural disasters to a level that the local community can afford socially and economically, is increasing. Accordingly, various studies on urban resilience have been conducted, but the resilience measurement method related to the lifeline that provides essential services of the city is insufficient. However, among lifelines, road networks are important facilities for the transportation of recovery resources and rapid recovery in the event of a natural disaster, so road networks are a major factor that must be considered when measuring the degree of recovery of a city in the field of natural disasters. Therefore, this study proposes a recovery evaluation method considering the characteristics of resilience and road networks in the urban flooding field and analyzes the effect of road networks on urban resilience.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.1
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• pp.48-55
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• 2009

In order to keep safe driving conditions under road networks, there are several formations such as road structure, road surface condition, traffic occupancy and supplement of an accurate information of traffic status ahead To support safe-driving on each road formation, each formation is supplied with various information to help the driver. However, in some cases like rapid status change at local-scale geography, traffic information systems often displays insufficient information because of the lack of information correlation. In order to accurately aware the driver, all road formation must be in sync. It is important to supply accurate information to the driver because this information directly impacts the drivers on the road. This paper discusses the amber information to keep the least safety driving over road formations including tunnels and bridges. This paper also will propose the informations for safe-driving conditions, information linkage on the road and rule-base safety information, as ITS technology, being displayed for all drivers under the worst weather conditions.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.47-56
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• 2013

The present study proposed a methodology to analyze the networking efficiency of arterial road networks. The methodology was motivated to design three-dimensional networks and to analyze the networking ability quantitatively, which is a novel approach compared to existing methods depending on the two-dimensional network definition and the qualitative analysis for improving arterial road networks. The method considered the interdependence between high-level freeways and low-level highways, the ITS-based information for traffic and road conditions, and the physical networking. These three factors were quantified by a networking index (NI), and the networking efficiency was measured by a networking rate (NR). The present study proved that the networking efficiency (NR) was influenced by travel information sharing (i.e., ITS) and physical factors. This supports the fact that the integrated improvements of physical and ITS factors are necessary for an arterial road. The proposed method was applied for an actual arterial road network. It was found that the nation-wide NR was higher than that for the metropolitan area, which might be due to the difficulty in switching between high- and low-level networks and the lack of ITS functions in the metropolitan area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.18-35
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• 2020

Many human, roadway, and vehicle factors affect vehicle-pedestrian crashes. Especially, the roadway factors are easily defined and suitable for suggesting countermeasures. The characteristics of the road network are one of the roadway factors. The road network significantly influences behaviors and conflicts of drivers and pedestrians. A metropolitan city such as Seoul contains various types of road networks, and crash prevention strategy considering characteristics of the road network is required. In this study, we analyze the effects of road networks on vehicle-pedestrian crashes. In the study, high order road ratio, intersection ratio, high-low intersection ratio are considered as road network variables. Using Geographically Weighted Poisson Regression, crash frequencies in Dongs of Seoul are analyzed based on the road network variable as well as socioeconomic variables. As a result, Dongs are grouped by coefficient signs, and each group is suggested about improvement directions considering conflict situations.