Traffic Status Evolution Trend Prediction Based on Congestion Propagation Effects under Rainy Weather
Joint Authors
Feng, Rui
Cui, Shaohua
Xue, Yongjie
Yu, Bin
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-19
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
In rainy weather, the accurate prediction of traffic status not only helps road traffic managers to formulate traffic management methods but also helps travelers design travel routes and even adjust travel time.
In this paper, based on six-dimensional data (e.g., past and present spatiotemporal traffic status, road network structure, pavement type, water accumulation, and rainfall level), a fuzzy neural network (FNN) prediction system is proposed to predict traffic status.
The traffic status evolution trend is related not only to the existing traffic but also to the new traffic demand.
Therefore, the FNN prediction system designed includes offline and online parts using the data of the past and the day separately and avoids the forecast of new traffic demand.
The fuzzy C-means clustering algorithm is applied to cluster traffic status data under similar rainy weather in the past to form an offline initial dataset, which is used to train FNN weight parameters.
The online part uses real-time detection data and the parameters trained by the offline part to further predict the traffic status and returns the prediction errors to the offline part to correct the weight parameters to further improve prediction accuracy.
Finally, the FNN prediction system is verified using real Beijing expressway network data.
The verification results show that the prediction system can guarantee prediction accuracy and can be used to effectively identify traffic status.
American Psychological Association (APA)
Xue, Yongjie& Feng, Rui& Cui, Shaohua& Yu, Bin. 2020. Traffic Status Evolution Trend Prediction Based on Congestion Propagation Effects under Rainy Weather. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1176628
Modern Language Association (MLA)
Xue, Yongjie…[et al.]. Traffic Status Evolution Trend Prediction Based on Congestion Propagation Effects under Rainy Weather. Journal of Advanced Transportation No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1176628
American Medical Association (AMA)
Xue, Yongjie& Feng, Rui& Cui, Shaohua& Yu, Bin. Traffic Status Evolution Trend Prediction Based on Congestion Propagation Effects under Rainy Weather. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1176628
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1176628