Real-Time Prediction of Lane-Based Queue Lengths for Signalized Intersections
Joint Authors
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-03
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
Queue length is one of the most important traffic evaluation indexes for traffic signal control at signalized intersections.
Most previous studies have focused on estimating queue length, which cannot be predicted effectively.
In this paper, we applied the Lighthill–Whitham–Richards shockwave theory and Robertson’s platoon dispersion model to predict the arrival of vehicles in advance at intervals of 5 seconds.
This approach fully described the relationship between disparate upstream traffic arrivals (as a result of vehicles making different turns) and the variation of incremental queue accumulation.
It also addressed the shortcomings of the uniform arrival assumption in previous research.
In addition, to predict the queue length of multiple lanes at the same time, we integrated the prediction of the traffic volume proportions in each lane using the Kalman filter.
We tested this model in a field experiment, and the results showed that the model had satisfactory accuracy.
We also discussed the limitations of the proposed model in this paper.
American Psychological Association (APA)
Li, Bing& Cheng, Wei& Li, Lishan. 2018. Real-Time Prediction of Lane-Based Queue Lengths for Signalized Intersections. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1181332
Modern Language Association (MLA)
Li, Bing…[et al.]. Real-Time Prediction of Lane-Based Queue Lengths for Signalized Intersections. Journal of Advanced Transportation No. 2018 (2018), pp.1-18.
https://search.emarefa.net/detail/BIM-1181332
American Medical Association (AMA)
Li, Bing& Cheng, Wei& Li, Lishan. Real-Time Prediction of Lane-Based Queue Lengths for Signalized Intersections. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1181332
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181332