Abstract
Route travel time varies with vehicles and traffic demand. Besides the average route travel time, route travel time reliability in the form of travel time distribution is indispensable. However, the sample size of Complete Route Travel Times (TTC) is rather small for many reasons. Existing methods using convolution distribution rely on strong assumptions about the correlation structure or the link travel time distributions; other methods relying on scaled Partial Route Travel Times (TTP) may extend the estimation bias. To overcome these issues, we present an estimation method for route travel time distribution by fusing kinds of route travel time information from Automatic Number Plate Recognition (ANPR) data. The proposed method firstly improves the data quality for estimation in four steps, including route redefinition, observation extraction, path inference, and scaling. Secondly, using TTP data, it convolutes the empirical travel time distributions on all the partial routes divided at the breakpoints identified by the Hopkins statistics. Thus, the link correlations are considered and the assumption about the correlation structure is eschewed. Thirdly, the convolution distribution and TTC information are fused to estimate the actual route travel time distribution based on Bayes’ theorem and Shannon’s information entropy. Finally, estimation results using different methods are compared to evaluate the developed model.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China, No. 61773347, and the Natural Science Foundation of Zhejiang Province, No. LY17F030017. The authors would like to thank the Traffic Police Detachment in Qingdao for providing ANPR data for research.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 145 • Issue 7 • July 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Sep 5, 2018
Accepted: Nov 13, 2018
Published online: May 7, 2019
Published in print: Jul 1, 2019
Discussion open until: Oct 7, 2019
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