• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.91-98
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• 1996

Transportation impact assessment which can take precaution for the traffic problem to control a plan on to expand traffic facilities through these results analyzed with the business for making a big problem of traffic is a very important course on the traffic management system as well as the traffic plan and it is necessary to collect and to edit and to analyze a great deal of data fully in object zone. So it is worth while to treat the collected data on to computer. Therefore Geographic Information System will give a remarkable result to Traffic Influence Evaluation everywhere. GIS not only can join the graphic or attribute data correctly and fast, but can achieve it prominent function for intention decision means. Then total system for Landuse of surrounding district, development-plan state, traffic-facility state, traffic-development public plan state and traffic demand is animated on Traffic Influence Evolution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.345-352
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• 2005

In up-to-date information anger time it is caused by with business of traffic accident control and analysis and two time it accomplishes a business. National Police Office which controls a traffic accident does not execute an up-to-date technique. And, it is working yet by the hand, There is to traffic accident analysis and the research regarding the analysis against the research which it follows in geography element and composition element and an accident cause is weak. Consequently, effectively establishment and it enforces a traffic safety policy and from the hazard which it evaluates traffic accident data the system and scientific analysis against a traffic accident occurrence cause and a feature in basic must become accomplished. The research which it sees constructs a traffic accident data in GIS base. It is like that, it uses the PDA where is not the collection of data of text form in existing and at real-time it converts store and an accident data rightly in standard traffic accident data form and it will be able to manage. It was related with a space data peculiarity and the research regarding the system development with the geography analysis data about an accident cause under manifesting it accomplished.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.29-38
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• 2008

In Seoul, the volume of office market has been expanding rapidly and the currency will be maintained. Many researches have looked at determinants of the office rent, we still cannot have adequate and accurate information of the impacts of traffic congestions around office buildings on the office rents. To gauge the effect of traffic conditions surrounding an office building on the office rent, a hedonic price model was estimated. The regression analysis estimates the values or implicit prices of the individual rent determinants; these parameters in turn allow for a detailed examination of the variables that impact office rents. The result shows that traffic conditions of office buildings play an important role in determining the office rental rate. Since a number of adjacent streets provided excellent opportunities to connect with the neighborhood, it pulls up the rental rate. Similarly, traffic congestions depreciates the value of an office buildings restricting the accessibility to the office building. We also provide evidence of the existence of spatial submarkets and find that market takes different spatial forms depending on the local context.

• Journal of Environmental Health Sciences
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• v.30 no.3
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• pp.293-299
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• 2004

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristics of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends is towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a model of vehicle emission calculation by using real-time traffic data was studied. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It is possible that characteristics of hourly air pollutants emission rates is obtained from hourly traffic volume and speed. An emission rates model is allocated with a high resolution space by using geographic information system (GIS). Vehicle emission model was developed with a high resolution spatial, gridded and hourly emission rates.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.309-321
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• 2005

To analyze travel demand fur transportation policy and transportation planning, it is important to construct realistic and reliable traffic data. And it needs a user friendly system to demonstrate transportation problems in the transportation planning and transportation management aspect. Generally, to construct network for analysis and collection about social and economical data is a core of transportation planning model. However, it takes a lot of time and effect. To overcome this problem GIS is more effective and efficient in data processing, such as selecting, editing and visualizing, etc. However, it is an early stage to use CIS in the transportation problems. This paper shows a new GIS-T system. The system can give traffic information and plan transportation planning using GIS which has ability as spatial representation and spatial analysis. To build this system, we design interfaces that are able to communicate transportation package for analysis with GIS and manage network efficiently, such as editing and examination. And we also develop a module for traffic information processing to handle spatial data and add it on the system. The proposed system shows more realistic transportation network modeling because the system presents more effective conditions to analyze network. And it can be a tool that can analyze various transportation problems.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.257-267
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• 2015

We propose a vehicle-mounted, location-aware mobile digital signage system that can be used for public transportation through mobile communication. This paper proposes the installations of the LED display panels at the backside of the bus., which display traffic information to cars behind the bus. Information to be displayed would include, but is not limited to, road information, public commercials and private commercials. We propose the system architecture and further implement the prototype of mobile digital signage system for demonstration. The system is based on the Client-Server system. Each bus has a client terminal which detects the current location by a GPS receiver and sends its location information to the server using mobile communication function. The terminal device receives advertisements and traffic information from the server and displays it to the large LCD or LED panel installed at the inside and outside of the bus. We use the Android smartphone as a client system, which inherently equipped with GPS and mobile communication function. GPS detects the location of bus and reports its geo-location data to the traffic information center server via a wireless communication network. On the server side, we developed a specially designed control server, where it communicates with the other traffic information center and updates and manages the databases contents being displayed by each position. The server contains location dependent variable information and returns selected information back to the vehicle in real time. Spatial database is used to process location based data. Server system periodically receives the real time traffic information from the road information center database. And it process the information by bus location and bus line number. In this paper, we propose a mobile digital signage service and explain the system implementation of this service.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.182-193
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• 2018

Purpose: The purpose of the study is to analyze the relationship between travel behavior and urban spatial characteristics in a hierarchical manner. Method: This study analyzed the relationship between traffic patterns and urban spatial characteristics for 83 cities in Korea by using a hierarchical linear model. Results: It was found that the urban spatial characteristics influenced the choice of transportation mode and travel time with personal attributes. However, the degree of influence on the choice of the means and the time required is relatively low through the policy of changing the city attribute, so the policy effect of mobilizing the land use policy for the traffic is theoretically, but the scale is not bigger than expected. Conclusion: In high density or the bigger scale of the city, the mass transportation system is widely supplied and used, but it does not overcome the drawback that it takes more time than the autos.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.220-233
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• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2804-2823
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• 2013

Wireless sensor network (WSN) is a promising technology for monitoring physical phenomena at fine-grained spatial and temporal resolution. However, the typical approach of sending each sensed measurement out of the network for detailed spatial analysis of transient physical phenomena may not be an efficient or scalable solution. This paper focuses on in-network physical phenomena detection schemes, particularly the distributed computation of the boundary of physical phenomena (i.e. event), to support energy efficient spatial analysis in wireless sensor networks. In-network processing approach reduces the amount of network traffic and thus achieves network scalability and lifetime longevity. This study investigates the recent advances in distributed event detection based on in-network processing and includes a concise comparison of various existing schemes. These boundary detection schemes identify not only those sensor nodes that lie on the boundary of the physical phenomena but also the interior nodes. This constitutes an event geometry which is a basic building block of many spatial queries. In this paper, we introduce the challenges and opportunities for research in the field of in-network distributed event geometry boundary detection as well as illustrate the current status of research in this field. We also present new areas where the event geometry boundary detection can be of significant importance.