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Critical Segments Identification for Link Travel Speed Prediction in Urban Road Network
Joint Authors
Zhou, Yang
Ru, Xiaolei
Yang, Chao
Xu, Xiangdong
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-08
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Predicting traffic operational condition is crucial to urban transportation planning and management.
A large variety of algorithms were proposed to improve the prediction accuracy.
However, these studies were mainly based on complete data and did not discuss the vulnerability of massive data missing.
And applications of these algorithms were in high-cost under the constraints of high quality of traffic data collecting in real-time on the large-scale road networks.
This paper aims to deduce the traffic operational conditions of the road network with a small number of critical segments based on taxi GPS data in Xi’an city of China.
To identify these critical segments, we assume that the states of floating cars within different road segments are correlative and mutually representative and design a heuristic algorithm utilizing the attention mechanism embedding in the graph neural network (GNN).
The results show that the designed model achieves a high accuracy compared to the conventional method using only two critical segments which account for 2.7% in the road networks.
The proposed method is cost-efficient which generates the critical segments scheme that reduces the cost of traffic information collection greatly and is more sensible without the demand for extremely high prediction accuracy.
Our research has a guiding significance on cost saving of various information acquisition techniques such as route planning of floating car or sensors layout.
American Psychological Association (APA)
Ru, Xiaolei& Xu, Xiangdong& Zhou, Yang& Yang, Chao. 2020. Critical Segments Identification for Link Travel Speed Prediction in Urban Road Network. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1176507
Modern Language Association (MLA)
Ru, Xiaolei…[et al.]. Critical Segments Identification for Link Travel Speed Prediction in Urban Road Network. Journal of Advanced Transportation No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1176507
American Medical Association (AMA)
Ru, Xiaolei& Xu, Xiangdong& Zhou, Yang& Yang, Chao. Critical Segments Identification for Link Travel Speed Prediction in Urban Road Network. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1176507
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1176507