• Journal of Korean Society of Transportation
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• v.12 no.3
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• pp.49-64
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• 1994

The development of a mathematical modular framework based on Petri Network theory to model a traffic network is the subject of this paper. Traffic intersections are the primitive elements of a transportation network and are characterized as event driven and asynchronous systems. Petri network have been utilized to model these discrete event systems; further analysis of their structure can reveal information relevant to the concurrency, parallelism, synchronization, and deadlock avoidance issuse. The Petri-net based model of a generic traffic junction is presented. These modular networks are effective in synchronizing their components and can be used for modeling purposes of an asynchronous large scale transportation system. The derived model is suitable for simulations on a multiprocessor computer since its program execution safety is secured. The software pseudocode for simulating a transportation network model on a multiprocessor system is presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.487-492
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• 2004

This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. In general, the modeling method of CDES has been studied many times, but that of FDES hasn't been nearly studied by qualitative character and scarcity of applicated system. This paper models traffic system with FDES's character in FTTPN and designs a traffic signal controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.499-505
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• 2004

In this paper, we studied about AGVs modeling and material handling automation simulation using a virtual AGV. The proposed virtual AGV model that operates independently each other is based on a real AGV. Continuous straight-line and workstation model using vector drawing method that could easily, rapidly work system modeling are suggested. Centralized traffic control, which could collision avoidance in intersection and should not stop AGV as possible, and algorithm for detour routing which performs when another AGV is working in pre-routed path are proposed. The traffic control and the algorithm have been proved efficience by simulation.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2195-2206
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• 2021

In order to mitigate the damage caused by accidents in nuclear power plants (NPPs), evacuation strategies are usually managed on the basis of off-site effects such as the diffusion of radioactive materials and evacuee traffic simulations. However, the interactive behavior between evacuees and the accident environment has a significant effect on the consequential gap. Agent-based modeling (ABM) is a method that can control and observe such interactions by establishing agents (i.e., the evacuees) and patches (i.e., the accident environments). In this paper, a radiological emergency evacuation model is constructed to realistically check the effectiveness of an evacuation strategy using NetLogo, an ABM toolbox. Geographic layers such as radiation sources, roads, buildings, and shelters were downloaded from an official geographic information system (GIS) of Korea, and were modified into respective patches. The dispersion model adopted from the puff equation was also modified to fit the patches on the geographic layer. The evacuees were defined as vehicle agents and a traffic model was implemented by combining the shortest path search (determined by an A ^* algorithm) and a traffic flow model incorporated in the Nagel-Schreckenberg cellular automata model. To evaluate the radiological harm to the evacuees due to the spread of radioactive materials, a simple exposure model was established to calculate the overlap fraction between the agents and the dispersion patches. This paper aims to demonstrate that the potential of ABM can handle disaster evacuation strategies more realistically than previous approaches.

• Spatial Information Research
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• v.22 no.1
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• pp.9-17
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• 2014

This study was intended to reliably predict the traffic green house gas emission in Daegu with the use of spatial statistical technique and calculate the traffic green house gas emission of each administrative district on the basis of the accurately predicted emission. First, with the use of the traffic actually surveyed at a traffic observation point, and traffic green house gas emission was calculated. Secondly, on the basis of the calculation, and with the use of Universal Kriging technique, this researcher set a suitable variogram modeling to accurately and reliably predict the green house gas emission at non-observation point suitable through spatial correlation, and then performed cross validation to prove the validity of the proper variogram modeling and Kriging technique. Thirdly, with the use of the validated kriging technique, traffic green gas emission was visualized, and its distribution features were analyzed to predict and calculate the traffic green house gas emission of each administrative district. As a result, regarding the traffic green house gas emission of each administration, it was found that Bukgu had the highest green house gas emission of $291,878,020kgCO_2eq/yr$.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.824-826
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• 2000

네트워크 데이터 traffic 특성은 네트워크의 성능분석과 설계에 중요한 요소이고 적절한 traffic modeling을 통해 load balancing, fault tolerance 및 전송속도 개선 둥 시스템 성능을 높이는데 보다 유용한 자료를 제공할 수 있어 지금까지 많은 연구가 진행되어 왔다. 그러나 네트워크 traffic은 네트워크의 규모와 서비스 종류 등 여러 가지 이유로 어느 한가지 모델로 규정짓는 것이 용이하지 않다. 또한 근래 인터넷 사용자의 수가 급속히 증가함에 따라 네트워크 traffic의 대부분이 world wide web에 기인하는 특성을 볼 수 있다. 본 논문에서는 웹서버 운용환경 하에서 적용될 수 있는 traffic model들에 대해 고찰하고 실제 네트워크에서의 패킷 모니터 링을 통한 traffic 분석 예를 보인다.

• ETRI Journal
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• v.42 no.3
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• pp.366-375
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• 2020

The network traffic prediction of a smart substation is key in strengthening its system security protection. To improve the performance of its traffic prediction, in this paper, we propose an improved gravitational search algorithm (IGSA), then introduce the IGSA into a wavelet neural network (WNN), iteratively optimize the initial connection weighting, scalability factor, and shift factor, and establish a smart substation network traffic prediction model based on the IGSA-WNN. A comparative analysis of the experimental results shows that the performance of the IGSA-WNN-based prediction model further improves the convergence velocity and prediction accuracy, and that the proposed model solves the deficiency issues of the original WNN, such as slow convergence velocity and ease of falling into a locally optimal solution; thus, it is a better smart substation network traffic prediction model.

• Computers and Concrete
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• v.32 no.4
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• pp.411-423
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• 2023

The rapid development of road transport has increased the number of bridges that require widening. A critical issue in the construction of bridge widening is the influence of vibrations of the old bridge on the casting of wet joint concrete between the old and new bridges owing to the running traffic. Typically, the bridge is closed to traffic during the pouring of wet joint concrete, which negatively affects the existing transportation network. In this study, a newly developed microscopic traffic load modeling approach and the vehicle-bridge interaction theory are incorporated to develop a refined numerical framework for the analysis of random traffic-bridge coupled dynamics. This framework was used to investigate traffic-induced vibrations at the wet joint of a widened bridge. Based on an experimental study on the vibration resistance of wet joint concrete, traffic control strategies were proposed to ensure the construction performance of cast-in-site wet joint concrete under random traffic without interruption. The results show that the vibration displacement and frequency of the old bridge, estimated by the proposed framework, were comparable with those obtained from field measurements. Based on the target peak particle velocity and vibration amplitude of the wet joint concrete, it was found that traffic control measures, such as limiting vehicle gross weight and limiting traffic volume by closing an additional traffic lane, could ensure the construction performance of the wet joint concrete.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.6-10
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• 2005

With the rapid industrial development, railways have become a main traffic means of transportation. However, rail traffic noise and vibration have become a major problem in urban areas which is a very serious issue for the living environment. Especially, railway noise induced by rail operations has influenced on the residents living near railway tracks. The purpose of this paper is to investigate the Raynoise modeling in railway applications. Generally, my acoustics have been used to investigate the effectiveness of noise barriers in railway applications and barriers are modeled using the commercial software Raynoise. A-weighted sound pressure level have been measured at six locations, 4m from the track and are compared with experimental values. Based on the analysis of the results, Comparison between numerical and experimental values are within 1dB (A). Also, when a train is m through the Raynoise modeling, the general influential sphere of railway noise can be determined. Therefore, this study will be using basic data in establishing effective railway noise prevention plans far the future. Also, we could know that is applicable of Raynoise modeling at railway noise.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.257-269
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• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.