Cycle-Based Estimation on Lane-Level Queue Length at Isolated Signalized Intersection Using License Plate Recognition Data
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 1
Abstract
Queue length is an important parameter to evaluate the congestion level of urban intersections. Abundant methods based on different data sources, such as loop detector data and mobile sensor data, for estimating queue length have received wide attention. A license plate recognition (LPR) system recording vehicle information can be used as a data source to estimate lane-level queue length. In this study, an improved method is proposed for cycle-based queue length estimation at an isolated signalized intersection using LPR data, considering the residual queued vehicles under oversaturated conditions. First, a modified interpolation method is developed to infer the travel time of unmatched vehicles. Then, the complete arrival and departure information are processed as three characteristic parameters of vehicles, which are the input to the maximum probability function for queue length estimation at each lane. Finally, the proposed model is validated using actual cycle maximum queue length collected from a video camera and LPR data in Changsha city, China. The numerical results showed that the proposed model can achieve accurate estimation for lane-level queue length.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. The license plate recognition data used in this study are confidential with restrictions applied for individual privacy, and these data sources are restricted to apply in analysis. The road structure data and the code of clustering model are available from the corresponding author upon reasonable request.
Acknowledgments
This research was funded in part by the National Natural Science Foundation of China (No. 52172310), Humanities and Social Sciences Foundation of the Ministry of Education (No. 21YJCZH147), Innovation-Driven Project of Central South University (No. 2020CX041), Shandong Provincial Department of Transportation Technology Project (No. 2021B68), and the Fundamental Research Funds for the Central Universities of Central South University (No. 2022ZZTS0753).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 1 • January 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Dec 23, 2021
Accepted: Aug 17, 2022
Published online: Nov 2, 2022
Published in print: Jan 1, 2023
Discussion open until: Apr 2, 2023
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