• Title/Summary/Keyword: 도심부 단속류 도로

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Incident Detection for Urban Arterial Road by Adopting Car Navigation Data (차량 궤적 데이터를 활용한 도심부 간선도로의 돌발상황 검지)

  • Kim, Tae-Uk;Bae, Sang-Hoon;Jung, Heejin
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.13 no.4
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    • pp.1-11
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    • 2014
  • Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

A Path-based Traffic Flow Simulation Model for Large Scale Network (기종점 기반 대규모 가로망 교통류 시뮬레이션 모형)

  • 조중래;홍영석;손영태
    • Journal of Korean Society of Transportation
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    • v.19 no.3
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    • pp.115-131
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    • 2001
  • The Purpose of this study is to develop a simulation model for large-scale network with interrupted flow as well as uninterrupted flow. The Cell Transmission(CT) theory is used to simulate traffic flow. Flow transition rules have been newly developed to simulate traffic flows at merging and diverging sections, and signalized intersections. In the model, it is assumed that dynamic OD table is exogenously given. Simulation results for toy network shows that the model can explain queue dynamics not only in signalized intersections of urban arterials, but also in merging and diverging sections of freeway. In case study, the model successfully simulated traffic flows of 145,000 vehicles on CBD network of city of Seoul with 74 traffic zones, 133 signalized intersections among 395 nodes and 1110 links.

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