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Urban Link Travel Time Estimation Based on Low Frequency Probe Vehicle Data
Joint Authors
Bing, Qichun
Tian, Xiujuan
Zhou, Xiyang
Zhang, Wei
Yang, Zhao-Sheng
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-06
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
To improve the accuracy and robustness of urban link travel time estimation with limited resources, this research developed a methodology to estimate the urban link travel time using low frequency GPS probe vehicle data.
First, focusing on the case without reporting points for the GPS probe vehicle on the target link in the current estimation time window, a virtual report point creation model based on the K -Nearest Neighbour Rule was proposed.
Then an improved back propagation neural network model was used to estimate the link travel time.
The proposed method was applied to a case study based on an arterial road in Changchun, China: comparisons with the traditional artificial neural network method and the spatiotemporal moving average method revealed that the proposed method offered a higher estimation accuracy and better robustness.
American Psychological Association (APA)
Zhou, Xiyang& Yang, Zhao-Sheng& Zhang, Wei& Tian, Xiujuan& Bing, Qichun. 2016. Urban Link Travel Time Estimation Based on Low Frequency Probe Vehicle Data. Discrete Dynamics in Nature and Society،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1103547
Modern Language Association (MLA)
Zhou, Xiyang…[et al.]. Urban Link Travel Time Estimation Based on Low Frequency Probe Vehicle Data. Discrete Dynamics in Nature and Society No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1103547
American Medical Association (AMA)
Zhou, Xiyang& Yang, Zhao-Sheng& Zhang, Wei& Tian, Xiujuan& Bing, Qichun. Urban Link Travel Time Estimation Based on Low Frequency Probe Vehicle Data. Discrete Dynamics in Nature and Society. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1103547
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1103547