自動学習機能を備えた高速道路旅行時間予測モデルの開発 Online-learning Type of Traveling Time Prediction Model in Expressway

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In expressway, there exist a lot of requirements for traveling time prediction as the information on express way traffic-flow. It is a problem to be solved to predict traveling time with high accuracy in case traffic-flow changes dynamically like the beginning or the end of traffic congestion. It is therefore important to make the trafficsimulation model using time-series data by vehicle detectors. In this case, it is necessary to cope with secular change of traffic-flow characteristics like constructions of new expressways or environment condition changes. Thispaper proposes the new traffic-flow prediction system which has the model learning function by time-series data processing. The system makes the relation model between traffic density and vehicle velocity using neural networks. The neural networks is used as on-line learning model VENN(Vehicle velocity Estimation model on Neural Network). The system simulates the traffic-flow using the VENN and predicts traveling time using the simulation results. The proposed system was already estimated in the actual expressway, which ended in satisfactory results.

収録刊行物

  • 電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society  

    電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society 117(8), 980-985, 1997-08 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10002724992
  • NII書誌ID(NCID)
    AN10012320
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    09136339
  • NDL 記事登録ID
    4267307
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-1608
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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