• Title/Summary/Keyword: Traffic network model

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The Relation of CLR and Blocking Probability for CBR Traffic in the Wireless ATM Access Network

  • Lee, Ha-Cheol;Lee, Byung-Seub
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.11C
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    • pp.1158-1163
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    • 2002
  • In this paper it is focused on the relation between CLR (Cell Loss Ratio) and blocking probability, GoS(Grade of Services) parameters in the wireless ATM (Asynchronous Transfer Mode) access network which consists of access node and wireless channel. Traffic model of wireless ATM access network is based on the cell scale, burst scale and call connection level. The CLR equation due to buffer overflow for wireless access node is derived for CBR (Constant Bit Rate) traffic. The CLR equation due to random bit errors and burst errors for wireless channel is derived. Using the CLR equation for both access node and wireless channel, the CLR equation of wireless ATM access network is derived. The relation between access network CLR and blocking probability is analyzed for CBR traffic.

Revolutionizing Traffic Sign Recognition with YOLOv9 and CNNs

  • Muteb Alshammari;Aadil Alshammari
    • International Journal of Computer Science & Network Security
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    • v.24 no.8
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    • pp.14-20
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    • 2024
  • Traffic sign recognition is an essential feature of intelligent transportation systems and Advanced Driver Assistance Systems (ADAS), which are necessary for improving road safety and advancing the development of autonomous cars. This research investigates the incorporation of the YOLOv9 model into traffic sign recognition systems, utilizing its sophisticated functionalities such as Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN) to tackle enduring difficulties in object detection. We employed a publically accessible dataset obtained from Roboflow, which consisted of 3130 images classified into five distinct categories: speed_40, speed_60, stop, green, and red. The dataset was separated into training (68%), validation (21%), and testing (12%) subsets in a methodical manner to ensure a thorough examination. Our comprehensive trials have shown that YOLOv9 obtains a mean Average Precision (mAP@0.5) of 0.959, suggesting exceptional precision and recall for the majority of traffic sign classes. However, there is still potential for improvement specifically in the red traffic sign class. An analysis was conducted on the distribution of instances among different traffic sign categories and the differences in size within the dataset. This analysis aimed to guarantee that the model would perform well in real-world circumstances. The findings validate that YOLOv9 substantially improves the precision and dependability of traffic sign identification, establishing it as a dependable option for implementation in intelligent transportation systems and ADAS. The incorporation of YOLOv9 in real-world traffic sign recognition and classification tasks demonstrates its promise in making roadways safer and more efficient.

Optimal buffer partition for provisioning QoS of wireless network

  • Phuong Nguyen Cao;Dung Le Xuan;Quan Tran Hong
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.57-60
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    • 2004
  • Next generation wireless network is evolving toward IP-based network that can various provide multimedia services. A challenge in wireless mobile Internet is support of quality of service over wireless access networks. DiffServ architecture is proposed for evolving wireless mobile Internet. In this paper we propose an algorithm for optimal buffer partitioning which requires the minimal channel capacity to satisfy the QoS requirements of input traffic. We used a partitioned buffer with size B to serve a layered traffic at each DiffServ router. We consider a traffic model with a single source generates traffic having J $(J\geq2)$ quality of service (QoS) classes. QoS in this case is described by loss probability $\varepsilon_j$. for QoS class j. Traffic is admitted or rejected based on the buffer occupancy and its service class. Traffic is generated by heterogeneous Markov-modulated fluid source (MMFS).

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Network Traffic Analysis System Based on Data Engineering Methodology (데이터 엔지니어링 방법론을 기반으로한 네트워크 트래픽 분석 시스템)

  • Han, Young-Shin;Kim, Tae-Kyu;Jung, Jason J.;Jung, Chan-Ki;Lee, Chil-Gee
    • Journal of the Korea Society for Simulation
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    • v.18 no.1
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    • pp.27-34
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    • 2009
  • Currently network users, especially the number of internet users, increase rapidly. Also, high quality of service is required and this requirement results a sudden network traffic increment. As a result, an efficient management system for huge network traffic becomes an important issue. Ontology/data engineering based context awareness using the System Entity Structure (SES) concepts enables network administrators to access traffic data easily and efficiently. The network traffic analysis system, which is studied in this paper, is designed and implemented based on a model and simulation using data engineering methodology to be avaiable in evaluating large network traffic data. Extensible Markup Language (XML) is used for metadata language in this system. The information which is extracted from the network traffic analysis system could be modeled and simulated in Discrete Event Simulation (DEVS) methodology for further works such as post simulation evaluation, web services, and etc.

A Study on the Traffic Controller of ATM Call Level Based on On-line Learning (On-line 학습을 통한 ATM 호레벨 트래픽 제어 연구)

  • 서현승;백종일;김영철
    • Proceedings of the IEEK Conference
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    • 2000.06a
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    • pp.115-118
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    • 2000
  • In order to control the flow of traffics in ATM networks and optimize the usage of network resources, an efficient control mechanism is necessary to cope with congestion and prevent the degradation of network performance caused by congestion. To effectively control traffic in UNI(User Network Interface) stage, we proposed algorithm of integrated model using on-line teaming neural network for CAC(Call Admission Control) and UPC(Usage Parameter Control). Simulation results will show that the proposed adaptive algorithm uses of network resources efficiently and satisfies QoS for the various kinds of traffics.

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A Prediction of Marine Traffic Volume using Artificial Neural Network and Time Series Analysis (인공신경망과 시계열 분석을 이용한 해상교통량 예측)

  • Yoo, Sang-Lok;Kim, Jong-Su;Jeong, Jung-Sik;Jeong, Jae-Yong
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.1
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    • pp.33-41
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    • 2014
  • Unlike the existing regression analysis, this study anticipated future marine traffic volume using time series analysis and artificial neural network model. Especially, it tried to anticipate future marine traffic volume by applying predictive value through time series analysis on artificial neural network model as an additional input variable. This study used monthly observed values of Incheon port from 1996 to 2013. In order for the verification of the forecasting of the model, value for 2013 is anticipated from the built model with observed values from 1996 to 2012 and a proper model is decided by comparing with the actual observed values. Marine traffic volume of Incheon port showed more traffic than average for May and November by 5.9 % and 4.5 % respectably, and January and August showed less traffic than average by 8.6 % and 4.7 % in 2015. Thus, it is found that Incheon port has difference in monthly traffic volume according to the season. This study can be utilized as a basis to reflect the characteristics of traffic according to the season when investigating marine traffic field observation.

A Study on Providing Real-Time Route Guidance Information by Variable Massage Signs with Driver Behavior (운전자 행태를 고려한 VMS의 실시간 경로안내 정보제공에 관한 연구)

  • Lee, Chang-U;Jeong, Jin-Hyeok
    • Journal of Korean Society of Transportation
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    • v.24 no.7 s.93
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    • pp.65-79
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    • 2006
  • The ATIS(Advance Traveler Information System), as one part of ITS, is a system aiming to disperse traffic volume on transportation networks by providing traffic information to transportation users on pre-trip and en-route trips. One of tools in ATIS is usage of VMS(Variable Message Signs). It provides to the drivers with direct information about state of processing direction. which is considered as the most effective method in ATIS. The purposes of providing VMS information are classified two categories. One is to provide simple information to drivers for their convenience. The other is to manage traffic demand to improve transportation network performance. However, for more effective and reliable VMS information, several strategies should be taken into account. The main VMS management strategy is "Traffic Diversion Strategy for minimum delay" when traffic congestion or incident are occurred. For effective operation. firstly. reasonable diversion traffic volume is determined by network traffic condition Secondly, it is necessary to make providing information strategy which reflects driver response behavior for controling diversion traffic volume. This paper focuses on the providing real-time route guidance information by VMS when congestion is occurred by the incidents. This sturdy estimates time-dependent system optimal diversion rate that inflects travel time and queue lengths using traffic flow simulation model on base Cellular Automata. In addition, route choice behavior models are developed using binary logit model for traffic information variable by traffic system controller. Finally, this study provides time-dependent VMS massage contents and degree of providing information in order to optimize the traffic flow.

Navigational Anomaly Detection using a Traffic Network Model (교통 네트워크 모델 기반 이상 운항 선박 식별에 관한 연구)

  • Jaeyong Oh;Hye-Jin Kim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.828-835
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    • 2023
  • Vessel traffic service operators (VTSOs) need to quickly and accurately analyze the maritime traffic situation in the vessel traffic service (VTS) area and provide information to the vessels. However, if traf ic increases rapidly, the workload of VTSOs increases, and they may not be able to provide adequate information. Therefore, it is essential to develop VTSO support technologies that can reduce their workload and provide consistent information. In this paper, we propose a model for automatically detecting abnormal vessels in the VTS area. The proposed model consists of a positional model and a contextual model and is specifically optimized for the traffic characteristics of the target area. The implemented model was tested by using real-world data collected at a test center (Daesan Port VTS). Our experiments confirmed that the model could automatically detect various abnormal situations, and the results were validated through expert evaluation.

Toward Stochastic Dynamic Traffic Assignment Model: Development and Application Experiences (Stochastic Dynamic Assignment 모형의 개발과 활용)

  • 이인원;정란희
    • Journal of Korean Society of Transportation
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    • v.11 no.1
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    • pp.67-86
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    • 1993
  • A formulation of dynamic traffic assignment between multiple origins and single destination was first introduced in 1987 by Merchant and Nemhauser, and then expanded for multiple destination in the late 1980's (Carey, 1987). Based on behavioral choice theory which provides proper demand elasticities with respect to changes in policy variables, traffic phenomena can be analysed more realistically, especially in peak periods. However, algorithms for these models are not well developed so far(working with only small toy network) and solutions of these models are not unique. In this paper, a new model is developed which keeps the simplicity of static models, but provides the sensitivity of dynamic models with changes of O-D flows over time. It can be viewed as a joint departure time and route choice model, in the given time periods(6-7, 7-8, 8-9 and 9-10 am). Standard multinomial logit model has been used for simulating the choice behavior of destination, mode, route and departure time within a framework of the incremental network assignment model. The model developed is workable in a PC 386 with 175 traffic zones and 3581 links of Seoul and tested for evaluating the exclusive use of Namsan tunnel for HOV and the left-turn prohibition. Model's performance results and their statistical significance are also presented.

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Development of A System Optimum Traffic Control Strategy with Cell Transmission Model (Cell Transmission 이론에 근거한 시스템최적 신호시간산정)

  • 이광훈;신성일
    • Journal of Korean Society of Transportation
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    • v.20 no.5
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    • pp.193-206
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    • 2002
  • A signal optimization model is proposed by applying the Cell-Transmission Model(CTM) as an embedded traffic flow model to estimate a system-optimal signal timing plan in a transportation network composed of signalized intersections. Beyond the existing signal-optimization models, the CTM provides appropriate theoretical and practical backgrounds to simulate oversaturation phenomena such as shockwave, queue length, and spillback. The model is formulated on the Mixed-Integer Programming(MIP) theory. The proposed model implies a system-optimal in a sense that traffic demand and signal system cooperate to minimize the traffic network cost: the demand departing from origins through route choice behavior until arriving at destinations and the signal system by calculating optimal signal timings considering the movement of these demand. The potential of model's practical application is demonstrated through a comparison study of two signal control strategies: optimal and fixed signal controls.