Technical Papers
Sep 28, 2019

Real-Time Prediction of Lane-Based Delay Using Incremental Queue Accumulation

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 12

Abstract

Using a real-time prediction model of lane-based queue lengths, the authors predicted the lane-based delay using real-time prediction of the incremental queue accumulation (IQA), which can effectively overcome the difficulty of field data collection when using the IQA to calculate the delay. The authors used the Lighthill–Whitham–Richards (LWR) shockwave theory to analyze the IQA changes under different shockwaves. The proposed model was divided into underflow and overflow cases to illustrate the variation of the IQA when a residual queue exists. Two types of delay formulas were considered regarding the effects of the signal offset: coordinated lane and noncoordinated lane delays. The model was tested in a field experiment and compared with the Webster model and the Highway Capacity Manual IQA model, and the results showed that the model has satisfactory accuracy and strong robustness.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 61364019); and the Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security of China (Grant No. 2017KFKT04).

References

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 145Issue 12December 2019

History

Received: Nov 29, 2018
Accepted: Apr 9, 2019
Published online: Sep 28, 2019
Published in print: Dec 1, 2019
Discussion open until: Feb 28, 2020

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Authors

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Ph.D. Student, Faculty of Transportation Engineering, Kunming Univ. of Science and Technology, Kunming, Yunnan 650093, China; Engineer, Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security, Dept. of Public Security of Anhui Province, Hefei, Anhui 230088, China. ORCID: https://orcid.org/0000-0002-6022-8854. Email: [email protected]
Professor, Faculty of Transportation Engineering, Kunming Univ. of Science and Technology, Kunming, Yunnan 650093, China (corresponding author). ORCID: https://orcid.org/0000-0003-4369-6530. Email: [email protected]
Associate Professor, Infrastructure Construction Dept., Kunming Univ. of Science and Technology, Kunming, Yunnan 650093, China. Email: [email protected]

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