• Title/Summary/Keyword: Traffic Information Center

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Kalman Filtering-based Traffic Prediction for Software Defined Intra-data Center Networks

  • Mbous, Jacques;Jiang, Tao;Tang, Ming;Fu, Songnian;Liu, Deming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.2964-2985
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    • 2019
  • Global data center IP traffic is expected to reach 20.6 zettabytes (ZB) by the end of 2021. Intra-data center networks (Intra-DCN) will account for 71.5% of the data center traffic flow and will be the largest portion of the traffic. The understanding of traffic distribution in IntraDCN is still sketchy. It causes significant amount of bandwidth to go unutilized, and creates avoidable choke points. Conventional transport protocols such as Optical Packet Switching (OPS) and Optical Burst Switching (OBS) allow a one-sided view of the traffic flow in the network. This therefore causes disjointed and uncoordinated decision-making at each node. For effective resource planning, there is the need to consider joining the distributed with centralized management which anticipates the system's needs and regulates the entire network. Methods derived from Kalman filters have proved effective in planning road networks. Considering the network available bandwidth as data transport highways, we propose an intelligent enhanced SDN concept applied to OBS architecture. A management plane (MP) is added to conventional control (CP) and data planes (DP). The MP assembles the traffic spatio-temporal parameters from ingress nodes, uses Kalman filtering prediction-based algorithm to estimate traffic demand. Prior to packets arrival at edges nodes, it regularly forwards updates of resources allocation to CPs. Simulations were done on a hybrid scheme (1+1) and on the centralized OBS. The results demonstrated that the proposition decreases the packet loss ratio. It also improves network latency and throughput-up to 84 and 51%, respectively, versus the traditional scheme.

A study on building the platform and development of algorithm for collecting real-time traffic data (실시간 교통정보 수집을 위한 알고리즘 개발 및 플랫폼 구축에 관한 연구)

  • Kim, Dong-Min;Jeong, Young-Mu;Min, Soo-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.535-538
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    • 2012
  • Recently active research for ITS(Intelligent Transportation System) helps to build for next generation traffic information system at information society. Build the system for sensing a vehicle speed and traffic information on the road. Provide collected data to driver, flow of overall traffic impacts have a good influence. In this study, research for building the platform and development algorithm that provided from other source processing real-time traffic data provides a more reliable real-time traffic data.

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Traffic Optimized FEC Control Algorithm for Multimedia Streaming Applications.

  • Magzumov, Alexander;Jang, Wonkap
    • 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.

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Shared Spatio-temporal Attention Convolution Optimization Network for Traffic Prediction

  • Pengcheng, Li;Changjiu, Ke;Hongyu, Tu;Houbing, Zhang;Xu, Zhang
    • 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.

A Study on the Development of Intelligent Transport System Center for Integrated Road Transport Information Service System (통합도로교통정보 서비스 체계 구현을 위한 교통정보센터 개발 연구)

  • Chung, Sung-Hak
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.259-270
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    • 2009
  • The objective of this study is to provide systematic design of the Korea's Integrated Road Transport System in intelligent transport systems. Integrated Road Transport System services support safety driving and traffic information for travellers, and rapid response of the system for emergency status not only dissemination of traffic for traffic but also flood, heavy snowfall, falling rocks, closed-road, collapse, accident and so on. Therefore, integrated road transport system service contributes national highway safety management system to the voice of the nation of integrated road transport system center service for user friendly.

A Flow Analysis Framework for Traffic Video

  • Bai, Lu-Shuang;Xia, Ying;Lee, Sang-Chul
    • Journal of Korea Spatial Information System Society
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    • v.11 no.2
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    • pp.45-53
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    • 2009
  • The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

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Improvement of Information Connection System among Traffic Information Centers (교통정보센터 간 정보 연계체계 개선방안)

  • Lim, Sung Han
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.13 no.2
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    • pp.34-41
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    • 2014
  • The purpose of this study is to present the improvement of connection system between traffic information centers for reliable traffic information service. We recognized traffic information error caused by too much time in conjunction between traffic information centers, lack of reliability of traffic information caused by absence of generation time and generation institution of traffic information. We presented minimization methods of connection time, improvement methods of reliability of traffic information and development methods of connection state management system.

Traffic Flow Sensing Using Wireless Signals

  • Duan, Xuting;Jiang, Hang;Tian, Daxin;Zhou, Jianshan;Zhou, Gang;E, Wenjuan;Sun, Yafu;Xia, Shudong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.10
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    • pp.3858-3874
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    • 2021
  • As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

A Study on the Verification of Traffic Flow and Traffic Accident Cognitive Function for Road Traffic Situation Cognitive System

  • Am-suk, Oh
    • Journal of information and communication convergence engineering
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    • v.20 no.4
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    • pp.273-279
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    • 2022
  • Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

A Development of the Evaluation Index for UTIS Traffic Information Service (UTIS 교통정보 제공서비스 성과평가 인덱스 개발)

  • Kim, Eun-Jeong;Bae, Kwang-Soo;Ahn, Gye-Hyeong;Lee, Chul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.6
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    • pp.13-21
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    • 2010
  • Road Traffic Authority and National Police Agency is currently managing the "development of an integrated metropolitan traffic information infrastructure" that installs of facilities for a traffic information infrastructures, such as Local Traffic Information Center, UTIS(Urban Traffic Information System), CCTV, VMS and etc. CTIC was established in 2005 to act as an traffic information hub and to provide integrated UTIS traffic information without regional barriers. This study was carried out to seek for solution to improve quality of UTIS traffic information service for the Central Traffic Information Center(CTIC). In this study, the Evaluation index for UTIS traffic information service was developed and the implementation plan was established by using requirement analysis method, case study and AHP(Analytic Hierarchy Process) technique. The Evaluation index consist of 5 fields and 20 index, it make possible evaluation of direct/indirect effect for UTIS traffic information service. In conclusion, It is expected that quality of UTIS traffic information service will be improved by using developed evaluation index and also can be applied for performance evaluation of other traffic information systems.