• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.2
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• pp.1-8
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• 2014

This paper introduces a new framework of predicting the arrival time of an aircraft by incorporating the probabilistic information of what type of trajectory pattern will be applied by human air traffic controllers. The proposed method is based on identifying the major patterns of vectored trajectories and finding the statistical relationship of those patterns with various traffic complexity factors. The proposed method is applied to the traffic scenarios in real operations to demonstrate its performances.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.505-508
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• 2000

We discuss simulation results concerning the performance of the TCP protocol when running over high-speed HFC networks. Hybrid Fiber Coaxial are likely to provide fast and cost effective sup-port to a variety of applications including Video on demand, interactive computer games, and internet-type applications such as Webbrowsing, ftp, and telephony. Since most of these applications, use TCP as the transport later protocol, the key to their success largely depends on the effectiveness of the TCP protocol. In all simulation scenarios the TCP traffic is maxed with some background traffic whose level is taken as a variable parameter. Both the background traffic and TCP traffic are either unshaped, or shaped according to the GCRA algorithm. The effect of the background traffic on the TCP protocol performance is discussed varying the buffering capacity with nodes as well as the peak bit rate that each TCP connection is allowed to use.

• ETRI Journal
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• v.41 no.5
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.148-162
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• 2023

The objective of this study is to derive the appropriate perception location for changes in driving behavior of autonomous vehicles in urban road environments based on traffic safety signs. For this purpose, 32 types of signs that induce changes in driving behavior were selected from currently used traffic safety signs and classified as three types according to changes in driving behavior. Based on this, three scenarios were designed: stop, speed change, and lane change scenarios. These were used to confirm the impact on traffic flow. As a result of the analysis, it was found that each scenario needs to receive information on traffic safety signs in advance to ensure changes in traffic flow and safety. Consequently, the appropriate perception location can be used as a basis for establishing standards for delivering message sets to autonomous vehicles or revising traffic safety signs for them. In addition, this study is expected to contribute to the establishment of safe and efficient driving strategies on urban roads as autonomous vehicles are introduced in the future.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.6-12
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• 2023

For the commercialization and standardization of autonomous vehicles, demand for rigorous safety criteria has been increased over the world. In Korea, the number of extraordinary service permission for automated vehicles has risen since Hyundai Motor Company got its initial license in March 2016. Nevertheless, licensing standards and evaluation factors are still insufficient for operating on public roadways. To assure driving safety, it is significant to verify whether or not the vehicle's decision is similar to human driving. This paper validates the safety of the autonomous vehicle by drawing scenario-based comparisons between manual driving and autonomous driving. In consideration of real traffic situations and safety priority, seven scenarios were chosen and classified into basic and advanced scenarios. All scenarios and safety factors are constructed based on existing ADAS requirements and investigated via a computer simulation and actual experiment. The input data was collected by an experimental vehicle test on the SNU FMTC test track located at Siheung. Then the offline simulation was conducted to verify the output was appropriate and comparable to the manual driving data.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.47-52
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• 1999

The methods currently in use to evaluate traffic impacts on the transportation network involve some fundamental shortcomings. First, the methodss do not properly take into account regional and local traffic impacts on the transportation network simultaneously. Second, temporal distribution of traffic, a major contributor to transportation problems, is not accurately accounted for. Third, traffic impact studies require costly and labor-intensive efforts to collect necessary data and to establish to collect necessary data and to establish traffic impact models. In this research, a new method called AMIS is developed for congestion management, access control, and impact simulation to overcome the shortcomings involved in the current methods. The new method is designed for a variety of scenarios such as access management strategies, land use policies, traffic impacts, and other congestion management strategies. This method can effectively be used, with little modification, anywhere in the United States. It is an improvement over the current traffic impact simulation methods that produces more reliable and accurate traffic impact estimates. The case studies conducted in this research have offered evidence that the new method, AMIS, is a credible congestion management tool. Most importantly, a case study presented in this paper illustrates how the new method can be used not only to estimate regional and local impacts of alternate supply management policies in the course of a day, but virtually on an hour-by-hour basis.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

• Journal of Korea Game Society
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• v.12 no.6
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• pp.5-14
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• 2012

The purpose of this paper is to demonstrate how three-dimensional gesture recognition technology, in children's traffic safety programs, can be an effective solution for instructing children in the safest ways to interact with traffic. In terms of traffic accidents, walking unaccompanied is the most dangerous traffic related activity for children. By using a three-dimensional serous game training program that implements gesture recognition, more accurate real life scenarios can be implemented in existing children's traffic training programs. The implementation of this technology will increase the possibility of changing the habits and attitudes of children, which in turn will lower the amount of walking related traffic accidents in children.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.144-152
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• 2018

This study focuses on collecting traffic data using drones to compensate for limitation of the data collected by the existing traffic data collection devices. Feasibility analysis was performed to verify the traffic data extracted from drone videos and optimal methodology for extracting data was established through analysis of various data reduction scenarios. It was found from this study that drones are very economical traffic data collection devices and have strength of determining the level-of-service(LOS) for uninterrupted flow condition in a very simple and intuitive way.

• Journal of Information Technology Applications and Management
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• v.30 no.6
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• pp.17-29
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• 2023

In this paper, we aim to propose cyber security considerations and countermeasures for infrastructure and services in the UAM(Urban Air Mobility) Air Traffic Management field, which is one of the key elements of the UAM market that has not yet bloomed. Air traffic management is an important factor for safe navigation and social acceptance of UAM. In order to realize air traffic management, infrastructure and services based on solid network connectivity must be established. And for industries where connectivity is the core component, it can become an infiltration route for cyber threats. Therefore, cyber security is essential for the infrastructure and services. In detail, we will look into the definition of the existing air traffic management field and the cyber threats. In addition, we intend to identify cyber security threat scenarios that may occur in the newly designed UAM air traffic management infrastructure. Moreover, in order to study the cyber security countermeasures of the UAM air traffic management infrastructure, there will be analysis of the UAM operation concept. As a result, countermeasures applicable to the infrastructure and service fields will be suggested by referring to the cyber security frameworks.