• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.15-24
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• 2022

At present, there are few studies on signal control of pedestrian traffic flow and non-motor traffic flow at intersections. Research on the optimization scheme of mixed traffic flow signal control can coordinate and control the overall traffic flow of pedestrians, non-motor vehicles and motor vehicles, which is of great significance to improve the congestion at intersections. For the traffic optimization of intersections, this paper starts from two aspects: channelization optimization and phase design, and reduces the number of conflict points at intersections from spatial and temporal right-of-way allocation respectively. Taking the classical signal timing method as the theoretical basis, and aiming at ensuring the safety and time benefit of traffic travelers, a channelization optimization and signal control scheme of the intersection is proposed. The channelization and phase design methods of intersections with motor vehicles, non-motor vehicles and pedestrians as objects are discussed, and measures to improve the channelization optimization of intersections are proposed. A multi-objective optimization model of intersection signal control was established, and the model was solved based on NSGA-II algorithm.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.130-138
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• 2023

The traffic flow in an urban area is affected by the date, weather, and regional traffic flow. The existing methods are weak to model the dynamic road network features, which results in inadequate long-term prediction performance. To solve the problems regarding insufficient capacity for dynamic modeling of road network structures and insufficient mining of dynamic spatio-temporal features. In this study, we propose a novel traffic flow prediction framework called shared spatio-temporal attention convolution optimization network (SSTACON). The shared spatio-temporal attention convolution layer shares a spatio-temporal attention structure, that is designed to extract dynamic spatio-temporal features from historical traffic conditions. Subsequently, the graph optimization module is used to model the dynamic road network structure. The experimental evaluation conducted on two datasets shows that the proposed method outperforms state-of-the-art methods at all time intervals.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.79-90
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• 2005

There are plenty of optimization models for the signal-system of a single intersection and area traffic. Some of those models are adopted for the real traffic signal control system. The simulators for a single crossroad have been developed, so that we could evaluate optimization models and traffic control systems. However, the simulators for the area traffic are still being developed. Therefore, there are many limitations in the analysis and evaluation for area traffic control system. The area traffic is consisted of several intersections which are very complicated and many traffic strategies are adopted for the control system. This paper features an effective area traffic control system based on the High Lever Architecture(HLA). In this paper, we discuss the design of HLA-based area traffic control simulation. We describe technical motivations for the HLA, the key elements of the architecture and how they are minimum and essential to the goal of reuse and interoperability. A distributed simulation with HLA/RTI provides stable and satisfactory experimental results. Moreover, the prototype traffic control system provides reliable accomplishment compared to the NETSIM and TRANSYT-7F models.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.15-18
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• 2003

There are plenty of optimization models for the signal-system of a single intersection and area traffic. Some of those models are adopted for the real traffic signal control system. The simulators for a single crossroad have been developed, so that we could evaluate optimization models and traffic control systems. However, the simulators for the area traffic are still being developed. Therefore, there are many limitations in the analysis and evaluation for area traffic control systems. The area traffic is consist of several intersections interconnected which are very complicated and many traffic strategy are adopted for the control system. This paper features an effective area traffic control system by High Lever Architecture(HLA) which is a new developed simulation tool. In this paper, we discuss the design of HLA-based area traffic control simulation. We describe technical motivations for the HLA, the key elements of the architecture and how they are minimum and essential to the goal of reuse and interoperability.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.82-88
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• 2005

There are plenty of optimization models for the signal-system of a single intersection and area traffic. Some of those models are adopted for the real traffic signal control system. The simulators for a single crossroad have been developed, so that we could evaluate optimization models and traffic control systems. However, the simulators for the area traffic are still being developed. Therefore, there are some limitations in the analysis and evaluation for area traffic control systems, The area traffic is consist of several intersections interconnected which are very complicated and many traffic strategy are adopted for the control system. This paper features an effective area traffic control system by High Lever Architecture(HLA) which is a new developed simulation tool. In this paper, we discuss the design of HLA-based area traffic control simulation. We describe technical motivations for the HLA, the key elements of the architecture and how they are minimum and essential to the goal of reuse and interoperability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.930-939
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• 2021

In recent years, the use of broadband bandwidth and redundant links for stable transmission in networks has resulted in excessive energy consumption and reduced transmission efficiency. In this paper, we propose an optimization algorithm that reduces the number of transmission links and minimizes transmission energy by removing redundant traffic in networks where traffic redundancy is allowed. The optimization algorithm proposed in this paper uses the meta-heuristic method using Tabu search algorithm. The proposed optimization algorithm minimizes transmission energy by designing a neighborhood generation method that efficiently routes overlapping traffic. The performance evaluation of the proposed optimization algorithm was performed in terms of the number of links used to transmit all traffic generated in the network and the transmission energy consumed. From the performance evaluation results, it was confirmed that the proposed algorithm is superior to other algorithms previously proposed.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.477-480
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• 2003

Packet losses in the Internet can dramatically degrade quality of multimedia streams. Forward Error Correction (FEC) is one of the best methods that can protect data from packet erasures by means of sending additional redundant information. Proposed control algorithm provides the possibility of receiving real-time multimedia streams of given quality wifth minimal traffic overhead. The traffic optimization is reached by adjusting packet size as well as block code parameters. Calculations and simulation results show that for non-bursty network conditions traffic optimization can lead to more than 50% bandwidth reduction.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.678-691
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• 2015

Internet and mobile traffic continues to surge exponentially in recent years due to popularization of smart devices, the appearance of various internet services carrying large amount of traffic from richer content and applications. This phenomenon leaded to various network problems such as the congestion delay, the non-balanced traffic ratio between ISPs, the continuous network investment cost and the Internet access problems. In light of changed data-driven communication ecosystem, There are growing concerns by both academia and industry that settlement-free peering and full transit regime have the limitations such as not only difficulties in maintaining mutual benefits but also difficulties in securing investment incentives for upgrading network performance and quality. Thus, it becomes more necessary for introducing the evolved internet interconnection regime which can fulfill the All-IP network environment. This study derives core issues regarding internet interconnection regime in Korea and suggest new evolved alternatives based on three point of view(traffic optimization, cost optimization, network investment optimization) through the empirical analysis.