• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.317-319
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• 2021

In Korea, an intelligent transportation system(ITS) is established to efficiently operate traffic congestion on roads and is being used for traffic information collection and speed control systems. Currently, designated and dedicated lanes are in place to ensure traffic circulation and traffic safety, and systematic and accurate illegal vehicle crackdown systems with artificial intelligence technology are needed. In this study, we propose a vehicle number recognition model that can improve the efficiency of the traffic of designated vehicles. By applying computer vision technology, we are going to identify three-lane and four-lane multi-lane roads in real time and detect vehicle numbers by car to suggest ways to crack down on vehicles that violate the designated lane system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.87-92
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• 2013

This study is to analyze the impacts of different High-Pass lane speed limits. Paramics, microscopic simulation software, was used to perform microscopic simulations. For the simulations, Incheon toll gate traffic count data was used. The Paramics simulation results show that higher High-Pass speed limit (70Km/h) produced better traffic flow condition and less air pollution cost compared to existing High-Pass speed limit (30Km/h).

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.100-109
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• 2022

Large-scale urban concentration of population and vehicles due to economic growth in Korea has been causing serious urban transport problems. Although the collection of congestion pricing has been evaluated as the most effective transportation policy to alleviate traffic demand, its effectiveness is very limited as it was just executed around congested points or along main arterial roads. This study derived dynamic congestion zones with the average travel speed of 206 traffic analysis zones in Busan Metropolitan City to propose a dynamic congestion pricing collection system by employing Space-Time Cube Analysis and Emerging Hot Spot Analysis. As a result, dynamic hot spots were formed from 7h to 24h and particularly, traffic congestion was severely deteriorated from 18h to 20h around Seomyeon and Gwangbok-dong. Therefore, it is expected that the effect of dynamic congestion pricing will be maximized in managing traffic demand in the city center.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.107-117
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• 2008

OBE(On Board Equipment) of IR(Infrared)/RF(Radio Frequence)-DSRC(Dedicated Short Range Communication) are set up 1.25 million cars because Korea Highway Cooperation supplied in HiPass(Domestic Electronic Toll Collection System). But this DSRC system has strength and weakness of service for BIS(Bus Information System) or UTIS(Urban Traffic Information System) because BIS and UTIS are required vary high communication's performance and management. In this paper, Efficiency of IR/RF-DSRC is analyzed performance of MAC(Medium Access Control) by computer simulation for services of BIS or UTIS, so Suggested to be commensurated with medium of there service. Specially, DSRC is needed high mobility and throughput in the vary short communication range, so Analysed the transmission rate of data in each communication medium over the specific character of the MAC frame.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.485-492
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• 2010

Intelligent Transport System(ITS) has been studied in various systems, such as road environment information offering, vehicle short-range wireless/wire communication, vehicle collision preventing and pedestrian safety offering systems. Related to this, the USN technology based on the sensing accuracy for motorists and pedestrians safety, the information reliability, the maintenance and convenience for Sensor Network is highlighted. This study uses various sensors to construct USN to the road, and connect it to the developed RSU so it collects the real-time road environment information and offers it to OBU and Traffic Control Surveillance Center with Road Weather Information System. RSU collects roadside information for driver's safety and analyzes it to offer IP and beacon service according to the service priority to OBU & upper layer terminal. In the upper layer terminal it is developed the IP based Settop Box application program to offer the urban traffic information & road environment, and environment sensor error, etc. Finally, RWIS develops the real-time collection of roadside information to complement the driver's safety to the intelligent traffic system, and presents various service modes with technology convergence.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.67-74
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• 2022

In recent, the number of real-time traffic information sources and providers has increased as increasing smartphone users and intelligent transportation system facilities installed at roadways including vehicle detection system (VDS), dedicated short-ranged communications (DSRC), and global positioning system (GPS) probe vehicle. The accuracy of such traffic information would vary with these heterogeneous information sources or spatiotemporal traffic conditions. Therefore, the purpose of this study is to propose an empirical strategy of heterogeneous information fusion to improve the accuracy of real-time traffic information. To carry out this purpose, travel speed data collection based on the floating car technique was conducted on 227 freeway links (or 892.2 km long) and 2,074 national highway links (or 937.0 km long). The average travel speed for 5 probe vehicles on a specific time period and a link was used as a ground truth measure to evaluate the accuracy of real-time heterogeneous traffic information for that time period and that link. From the statistical tests, it was found that the proposed fusion strategy improves the accuracy of real-time traffic information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.24-25
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• 2022

Based on the case of Busan Port November anchorage, which is a group anchorage, related regulations to promote group anchorage safety management, the turning radius of anchored ship, and more accurate weather information collection and safety through improvement of the supporting system for VTS operations to apply the anchorage location in accordance with reality that it is a suggestion for management improvement methods.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.120-125
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• 2000

SNMP(Simple Network Management Protocol) could have the overhead of network, if the number of the agent system which is managed by the management system is increased by the polling for the collection of network management information and the reply traffic for it. In this Paper, the polling method used in SNMP is improved, and Group Polling method is proposed. This can reduce the overhead of network, on case that the agent system is to be increased. The proposed method collects information by grouping agent systems, and have smaller reply latency time and communication overhead than the previous method. So if the number of agent system or the Polling count is numerous, the proposed method is more efficient. As the result of the prototype test, the increasement of agent system can have small variation of traffic and transmission delay time.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.241-250
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• 2008

With the ever-growing amount of traffic, there is an increasing need for good quality travel time information. Various existing outlier filtering and missing data imputation algorithms using AVI data for interrupted and uninterrupted traffic flow have been proposed. This paper is devoted to development of an outlier filtering and missing data imputation algorithm by using Toll Collection System (TCS) data. TCS travel time data collected from August to September 2007 were employed. Travel time data from TCS are made out of records of every passing vehicle; these data have potential for providing real-time travel time information. However, the authors found that as the distance between entry tollgates and exit tollgates increases, the variance of travel time also increases. Also, time gaps appeared in the case of long distances between tollgates. Finally, the authors propose a new method for making representative values after removal of abnormal and "noise" data and after analyzing existing methods. The proposed algorithm is effective.