• Title/Summary/Keyword: traffic model

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Discrete event simulation of Maglev transport considering traffic waves

  • Cha, Moo Hyun;Mun, Duhwan
    • Journal of Computational Design and Engineering
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    • v.1 no.4
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    • pp.233-242
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    • 2014
  • A magnetically levitated vehicle (Maglev) system is under commercialization as a new transportation system in Korea. The Maglev is operated by an unmanned automatic control system. Therefore, the plan of train operation should be carefully established and validated in advance. In general, when making a train operation plan, statistically predicted traffic data is used. However, a traffic wave often occurs in real train service, and demand-driven simulation technology is required to review a train operation plan and service quality considering traffic waves. We propose a method and model to simulate Maglev operation considering continuous demand changes. For this purpose, we employed a discrete event model that is suitable for modeling the behavior of railway passenger transportation. We modeled the system hierarchically using discrete event system specification (DEVS) formalism. In addition, through implementation and an experiment using the DEVSim++ simulation environment, we tested the feasibility of the proposed model. Our experimental results also verified that our demand-driven simulation technology can be used for a priori review of train operation plans and strategies.

Prediction of Road Traffic Noise by Box Model (BOX Model에 의한 도로교통소음 예측)

  • Yeo, Woon-Ho;Yu, Myong-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.1
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    • pp.57-62
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    • 1994
  • In order to establish a prediction method for road traffic noise generated from actual traffic flow, a new approach is proposed for practical use. One block in urban road is regarded as one box in this study. This prediction method is able to treat any kind of road traffic noise generated from one block. The validity of the proposed prediction method has been experimentally confirmed by applying it to actually observed road traffic noise data. The correlation between observed and predicted noise level is good.

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A Study on Analysis Characteristic Self-similar for Network Traffic with Multiple Time Scale (다중화된 네트워크 트래픽의 self-similar 특성 분석에 관한 연구)

  • Cho, Hyun-Seob;Han, Gun-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.11
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    • pp.3098-3103
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    • 2009
  • In this paper, self-similar characteristics over statistical approaches and real-time Ethernet network traffic measurements are estimated. It is also shown that the self-similar traffic reflects real Ethernet traffic chareacteristics by comparing TCP-MT source model which is exactly self-similar model to the traditional Poisson model.

Accident Analysis of 3-legged and 4-legged Roundabouts (3지와 4지 회전교차로의 사고분석)

  • Park, Min-Kyu;Park, Byung-Ho
    • Journal of the Korean Society of Safety
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    • v.27 no.3
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    • pp.161-166
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    • 2012
  • This study deals with the accident of roundabout. The objective is to analyze the traffic accidents occurred in 3-legged and 4-legged roundabouts through the developed models. In developing the multiple linear regression models, this study uses the number of traffic accidents as a dependent variable and such the variables as geometric structures, traffic characters and others as the independent variables. The correlation and multicollinearity of variables were analyzed using SPSS17.0. The main results are as follows. First, R-square value of developed models were analyzed to be 0.851(3-leg) and 0.689(4-leg), respectively. Second, the independent variables in the 3-legged roundabout accident model were analyzed to be the traffic volume and number of crosswalk, and the variables in the 4-legged roundabouts were evaluated to be the traffic volume and signal. Finally, the paired t-test shows that the predicted values and observed values are not statistically different.

Hierarchical Optimal Control of Urban Traffic Networks

  • Park, Eun-Se
    • ETRI Journal
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    • v.5 no.2
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    • pp.17-28
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    • 1983
  • This paper deals with the problem of optimally controlling traffic flows in urban transportation traffic networks. For this, a nonlinear discrete-time model of urban traffic network is first suggested in order to handle the phenomenon of traffic flows such as oversaturatedness and/or undersaturatedness. Then an optimal control problem is formulated and a hierarchical optimization technique is applied, which is based upon a prediction-type two-level method of Hirvonen and Hakkala.

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A Study on Stochastic Wave Propagation Model to Generate Various Uninterrupted Traffic Flows (다양한 연속 교통류 구현을 위한 확률파장전파모형의 개발)

  • Chang, Hyun-Ho;Baek, Seung-Kirl;Park, Jae-Beom
    • Journal of Korean Society of Transportation
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    • v.22 no.4 s.75
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    • pp.147-158
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    • 2004
  • A class of SWP(Stochastic Wane Propagation) models microscopically mimics individual vehicles' stochastic behavior and traffic jam propagation with simplified car-following models based on CA(Cellular Automata) theory and macroscopically captures dynamic traffic flow relationships based on statistical physics. SWP model, a program-oriented model using both discrete time-space and integer data structure, can simulate a huge road network with high-speed computing time. However, the model has shortcomings to both the capturing of low speed within a jam microscopically and that of the density and back propagation speed of traffic congestion macroscopically because of the generation of spontaneous jam through unrealistic collision avoidance. In this paper, two additional rules are integrated into the NaSch model. The one is SMR(Stopping Maneuver Rule) to mimic vehicles' stopping process more realistically in the tail of traffic jams. the other is LAR(Low Acceleration Rule) for the explanation of low speed characteristics within traffic jams. Therefore, the CA car-following model with the two rules prevents the lockup condition within a heavily traffic density capturing both the stopping maneuver behavior in the tail of traffic jam and the low acceleration behavior within jam microscopically, and generates more various macroscopic traffic flow mechanism than NaSch model's with the explanation of propagation speed and density of traffic jam.

Analysis on Factors Affecting Traffic Accident Severity - Case Study : Arterial Included Curve Section - (교통사고심각도 영향요인 분석에 관한 연구 - 곡선부가 포함된 국도를 중심으로 -)

  • Park, Jae Hong;Yun, Duk Geun;Sung, Jung Gon
    • Journal of the Korean Society of Safety
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    • v.28 no.6
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    • pp.84-89
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    • 2013
  • The main causes of traffic accidents can be classified by 3 factors - human error, vehicle deficiency and road environmental problem and most accidents occurs not only 1 factor but combination of 2 or 3-factors. Among these factors, road environmental factor is the most important factor due to influence the behavior of cars and road users and road environmental factor affects 30% of total accidents approximately. The 5 years traffic accidents data analyzed to verify the accidents severity on Korea National Highways. In order to analyze the severity, Ordered Probit Model was used. As a independent variables of this model the number of lane, neighbor road environments, sight distance, vertical grade, lane width, shoulder width and traffic volume were used and as a dependent variables the minor injuries, serious injuries and fatalities were used. Research results shows that sight distance and lane width are identified as significant factors for the traffic accident severity and lesser sight distance and lane width shows greater traffic accident severity.

A Travel Speed Prediction Model for Incident Detection based on Traffic CCTV (돌발상황 검지를 위한 교통 CCTV 기반 통행속도 추정 모델)

  • Ki, Yong-Kul;Kim, Yong-Ho
    • Journal of Industrial Convergence
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    • v.18 no.3
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    • pp.53-61
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    • 2020
  • Travel speed is an important parameter for measuring road traffic and incident detection system. In this paper I suggests a model developed for estimating reliable and accurate average roadway link travel speeds using image processing sensor. This method extracts the vehicles from the video image from CCTV, tracks the moving vehicles using deep neural network, and extracts traffic information such as link travel speeds and volume. The algorithm estimates link travel speeds using a robust data-fusion procedure to provide accurate link travel speeds and traffic information to the public. In the field tests, the new model performed better than existing methods.

A Study on the Criteria for an Optimal Traffic Control at an Intersection System (교차로(交叉路)에서의 교통통제방법(交通統制方法) 선정기준(選定基準)에 관(関)한 연구(硏究))

  • Cha, Dong-Wan;Ryu, Chun-Beon;No, Hyeong-Bong;Jang, Seok-Gwon
    • Journal of Korean Institute of Industrial Engineers
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    • v.8 no.1
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    • pp.29-39
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    • 1982
  • This paper presents a practical guidence for determining an optimal traffic control system at intersections in the urban areas in Korea. Two alternative systems, unsignalized and signalized, are considered. For analyzing the unsignalized system, two kinds of simulation model are developed ; gap acceptance model and first -in -first - out model. For the signalized system the total delay function for general arrival distribution is developed under the assumption that departure time is constant and it is used to find an optimal cycle time. Finally, the results in these two alternative systems are compared under the minimum average delay criterion and an optimal traffic control system is determined. This approach supports the decision making whether to install a traffic signal system in an intersection with given traffic flows and, if installed, determines what is the optimal cycle time and how the traffic signal phases are divided. And it also gives upper bounds of traffic flows to be passed in the unsignalized and the signalized system, which can be effectively used whenever an intersection is designed.

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Anomaly Detection Scheme of Web-based attacks by applying HMM to HTTP Outbound Traffic (HTTP Outbound Traffic에 HMM을 적용한 웹 공격의 비정상 행위 탐지 기법)

  • Choi, Byung-Ha;Choi, Sung-Kyo;Cho, Kyung-San
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.5
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    • pp.33-40
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    • 2012
  • In this paper we propose an anomaly detection scheme to detect new attack paths or new attack methods without false positives by monitoring HTTP Outbound Traffic after efficient training. Our proposed scheme detects web-based attacks by comparing tags or javascripts of HTTP Outbound Traffic with normal behavioral models which apply HMM(Hidden Markov Model). Through the verification analysis under the real-attacked environment, we show that our scheme has superior detection capability of 0.0001% false positive and 96% detection rate.