• 제목/요약/키워드: Traffic Information Center

검색결과 417건 처리시간 0.025초

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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    • 제13권6호
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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.

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

  • 김동민;정용무;민수영
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2012년도 춘계학술대회
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    • pp.535-538
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    • 2012
  • 최근 ITS(Intelligent Transportation System)와 관련된 연구들이 활발하게 진행되면서 정보화 사회에 알맞은 차세대 교통정보 체계를 구축하는데 일조하고 있다. 도로상의 차량 속도 및 교통 정보를 실시간으로 감지할 수 있는 시스템을 구축하여 운전자에게 정보를 제공함으로써 전체 교통 상황의 흐름에 좋은 영향을 끼칠 수 있다. 본 연구에서는 각기 다른 근원지로부터 제공되는 실시간 교통 정보를 가공하여 보다 신뢰적인 실시간 교통정보를 제공하는 알고리즘을 개발하고 이를 적용하는 플랫폼 구축에 관한 연구이다.

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Traffic Optimized FEC Control Algorithm for Multimedia Streaming Applications.

  • Magzumov, Alexander;Jang, Wonkap
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 I
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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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    • 제19권1호
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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.

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

  • 정성학
    • 한국컴퓨터정보학회논문지
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    • 제14권10호
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    • pp.259-270
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    • 2009
  • 본 연구의 목적은 통합도로교통 서비스 체계 구현을 위한 교통정보센터를 구축하는데 있다. 이러한 목적을 달성하기 위하여 기존의 교통정보센터 기능과 운영현황을 분석하고, 통합도로교통정보 서비스를 제공하는 교통정보센터를 개발함으로서 안전지향형 통합도로교통정보센터의 구현사례를 소개한다. 지능형교통체계는 안전지향의 통합도로교통정보 서비스 제공을 통한 교통안전체계를 구현할 뿐 만 아니라 전방의 홍수, 폭설 낙석, 도로유실 붕괴 등과 같은 자연재해 및 긴급상황 발생시 관련 정보를 시의 적절하게 제공함으로써 운전자의 안전한 도로운행을 지원하게 된다. 따라서 통합도로교통정보 서비스체계의 교통정보센터는 국민들에게 편리하게 사용할 수 있는 대국민 교통정보 서비스 제공으로 이용자 친화형 교통관리체계와 통합도로교통정보센터 기능을 실현하는데 일조할 것이다.

A Flow Analysis Framework for Traffic Video

  • Bai, Lu-Shuang;Xia, Ying;Lee, Sang-Chul
    • 한국공간정보시스템학회 논문지
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    • 제11권2호
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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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교통정보센터 간 정보 연계체계 개선방안 (Improvement of Information Connection System among Traffic Information Centers)

  • 임성한
    • 한국ITS학회 논문지
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    • 제13권2호
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    • pp.34-41
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    • 2014
  • 본 연구의 목적은 신뢰성 높은 교통정보 서비스를 위하여 교통정보센터 간 정보 연계체계 개선방안을 도출하는 것이다. 교통정보 연계체계의 문제점으로 교통정보센터 간 연계시간 과다 소요로 인한 오차 발생, 정보 생성시각 및 생성주체에 관한 정보 부재 등으로 인한 정보의 신뢰도 부족, 정보 연계 관리체계 미비 등의 문제점을 인식하였다. 교통정보 연계체계 개선방안으로 연계시간 최소화, 정보의 신뢰성 향상 및 연계 관리체계 구축방안을 제시하였다.

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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    • 제15권10호
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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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    • 제20권4호
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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.

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

  • 김은정;배광수;안계형;이철기
    • 한국ITS학회 논문지
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    • 제9권6호
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    • pp.13-21
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    • 2010
  • 도로교통공단과 경찰청은 2005년부터 전국 주요도시에 교통정보센터, 도로교통정보시스템(UTIS), CCTV, VMS 통신망 등 교통정보 기반시설을 설치하는 "도시지역 광역교통정보 기반확충사업"을 추진 중에 있다. 중앙교통정보센터는 국내 교통정보 허브(Hub) 기능을 담당하는 동시에 표준화된 광역교통정보관리체계의 구축 및 지역간 구분없는 UTIS 교통정보를 제공하는 역할을 수행하고 있다. 본 연구에서는 중앙교통정보센터를 통해 통합 제공되는 UTIS 교통정보 서비스의 효율적 추진과 품질향상을 도모하기 위한 방안을 모색하기 위해 수행되었다. 최종수요자(End-User) 요구분석, 기존사례검토 및 계층적 분석기법(AHP) 등을 활용하여 UTIS 교통정보 제공서비스의 성과평가지표를 개발하였으며, 평가시행방안을 수립 제시하였다. 개발된 성과평가지표는 총 5개 부문 20개 지표로 구성되어 있으며, UTIS 교통정보 제공에 따른 직접적/간접적 평가가 가능토록 하였다. 본 연구에서 제시된 평가지표 및 평가방법을 활용함으로써 중앙교통정보센터 UTIS 교통정보 제공서비스의 품질 개선을 도모할 수 있을 것으로 기대되며, 타 교통정보시스템의 운영성과 평가 시에도 확장 적용이 가능할 것으로 판단된다.