• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.32-45
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• 2013

Globally, intelligent vehicles and telematics research and development through the integration of IT technology in the vehicle are significant increasing. Real-time data communication for intelligent transportation system (ITS) is very important. It collects real-time data from the vehicle and provides the information collected from ITS center. We propose an effective and secure communication scheme for these communication procedures. In particular, our proposed SIP-based MVPN reduces signaling cost and has many advantages in security aspects. In addition, our proposed scheme performs the mobility management applying NEMO (Network Mobility) for the communication between the vehicles. In other words, we propose an ITS communication mechanism of SIP-based mobile VPN and V2V NEMO. Finally, our performance analysis show that the ITS of SIP-based MVPN is significantly reducing the handoff signaling cost.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.203-211
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• 2006

Today, Internet covers a world wide range and most appliances of our life are linked to network from enterprise server to household electric appliance. Therefore, the importances of administrable framework that can grasp network state by real-time is increasing day by day. Our objective in this paper is to describe a network weather report framework that monitors network traffic and performance state to report a network situation including traffic status in real-time. We also describe a mobile agent architecture that collects state information in each network segment. The framework could inform a network manager of the network situation. Through the framework. network manager accumulates network data and increases network operating efficiency.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.29-41
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• 2013

This study set out to developing data exchange standard between roadside device and traffic information center fitted in a domestic environment by applying international standard ISO 15784. First, we defined message basic concept of 'Dialog' and essential elements should be defined to define the standard message for securing system compatibility by reference ISO 14817 and ISO 14827 Part 1. For defining standard message items exchanged between AVI and traffic information center, we formed Working Group under ITS Standards Technical Committee and analyzed data flow for ITS National Architecture, Standard messages of existing standards, and AVI operation messages actually operated on roadside now. So, we extracted 14 functionally needed messages and defined 28 standard messages adopting 'Dialog' concept. In case of the application protocol for data exchange standards, we defined basic requirements for securing interoperability and interchangeability considering domestic environment by analyzing reference standard of ISO 15784.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.3-9
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• 2005

The extraction of traffic information based on image processing is under broad research recently because the method based on image processing takes less cost and effort than the traditional method based on physical equipment. The main purpose of the algorithm based on image processing is to extract vehicles from an image correctly. Before the extraction, the algorithm needs the pre-processing such as background subtraction and binary image thresholding. During the pre-processing much noise is brought about because roadside tree and passengers in the sidewalk as well as vehicles are extracted as traffic flow. The noise undermines the overall accuracy of the algorithm. In this research, most of the noise could be removed by extracting the exact road area which does not include sidewalk or roadside tree. To extract the exact road area, traffic lanes in the image were used. Algorithm speed also increased. In addition, with the ratio between the sequential images, the problem caused by vehicles' shadow was minimized.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.63-70
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• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.81-94
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• 2007

In order to solve the traffic problem which comes to be serious at day, the impotance of Intelligent Transport Systems(ITS) that accomplish information gathering, information processing, information offering with up-to-date scientific techniques is coming to be high. But many local self-government group want to solve the traffic problems with introduction of ITS, however, it is a actual condition where the systematic effective analysis is insufficient. This study establishes the methodology of effective analysis as introduction of ITS, which refers to the inside and outside of the country instance. And then, this research accomplishes direct and indirect effective analysis with the case study. As a result of SUWON ITS introduction effect analysis, the travel speed of TRC mode is increased 31%, and the delay of TRC mode is diminished 43.9% than before introducing case. Most of the citizen felt the improvement effect of ITS system operation, and the majority wanted the expansion of the ITS system in survey. The analysis of economic result that B/C ratio is 5.12. So, The the effect and economic propriety of the ITS enterprise appeared with the fact that it is sufficient.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.889-899
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• 2021

This paper proposes a reliable data sharing scheme on the internet of vehicles (IoV) by utilizing blockchain technology for constructing a decentralized system approach. In our model, to maintain the credibility of the information messages sent by the vehicles to the system, we propose a reputation rating mechanism, in which neighboring vehicles validate every received information message. Furthermore, we incorporate an incentive mechanism based on smart contracts, so that vehicles will get certain rewards from the system when they share correct traffic information messages. We simulated the IoV network using a discrete event simulator to analyze network performance, whereas the incentive model is designed by leveraging the smart contract available in the Ethereum platform.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.101-110
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• 2006

ADevelopment of various geographic observations, GPS, and Wireless Communication technologies make it easy to control many moving objects and to build an intelligent transport system and transport vehicle management system. However it is difficult to make a suitable system in the real world with a variety of tests to evaluate the performance fairly because real vehicle data are not enough as evaluating and testing the transport plan in the system. Therefore some moving object data generator would be used in most researches. However they can not generate vehicle trajectory according to a user scenario defined to be applied to transport plan, because the existing data generators consider only a gauss distribution, road network. In this paper we design and implement a vehicle data generator for creating vehicle trajectory data based on the user-defined scenario. The designed data generator could make the vehicle location depending on user's transport plan. Besides we store the scenario as patterns and reutilize the used scenario.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.390-392
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• 2001

This paper presents an intersection of technologies of ITS (intelligent transport systems) and CBTC(communication based train control) in urban transit system. ITS is based on Information and communication technologies. And also these techniques are fundamental for railway system. ITS has some technologies useful in railways such as traveler information service, public transportation information service, and advanced vehicle control Systems. Therefore, both systems need to technological cooperation. In this paper, we proposed useful an cooperation method for both systems.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.213-222
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• 2019

Determining the meaning of a keyword in a speech dialogue system is an important technology for the future implementation of an intelligent speech dialogue interface. After extracting keywords to grasp intention from user's utterance, the intention of utterance is determined by using the semantic mark of keyword. One keyword can have several semantic marks, and we regard the task of attaching the correct semantic mark to the user's intentions on these keyword as a problem of word sense disambiguation. In this study, about 23% of all keywords in the corpus is manually tagged to build a semantic mark dictionary, a synonym dictionary, and a context vector dictionary, and then the remaining 77% of all keywords is automatically tagged. The semantic mark of a keyword is determined by calculating the context vector similarity from the context vector dictionary. For an unregistered keyword, the semantic mark of the most similar keyword is attached using a synonym dictionary. We compare the performance of the system with manually constructed training set and semi-automatically expanded training set by selecting 3 high-frequency keywords and 3 low-frequency keywords in the corpus. In experiments, we obtained accuracy of 54.4% with manually constructed training set and 50.0% with semi-automatically expanded training set.