Online-learning Type of Traveling Time Prediction Model in Expressway
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- Koyama Toshihiro
- Toshiba Corporation
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- Ohba Yoshikazu
- Toshiba Corporation
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- Shimada Shigehito
- Toshiba Corporation
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- Ueno Hideki
- Toshiba Corporation
Bibliographic Information
- Other Title
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- 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
- ジドウ ガクシュウ キノウ オ ソナエタ コウソク ドウロ リョコウ ジカン
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Abstract
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.
Journal
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- IEEJ Transactions on Industry Applications
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IEEJ Transactions on Industry Applications 117 (8), 980-985, 1997
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679635472256
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- NII Article ID
- 10002724992
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- NII Book ID
- AN10012320
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- ISSN
- 13488163
- 09136339
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- NDL BIB ID
- 4267307
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed