Estimating Queue Length for Contraflow Left-Turn Lane Design at Signalized Intersections
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 6
Abstract
An unconventional left-turn treatment called contraflow left-turn lane (CLL) design has been increasingly used in China to relieve traffic congestion associated with left-turn movements at signalized intersections. This study proposed a procedure for estimating the left-turn queue length at signalized intersections with the CLL design. Field data were collected at six approaches at five signalized intersections in the city of Handan, China, and 40 h of traffic data were recorded. A binary logit model was developed to estimate the probability of a driver stopping at the presignal when there are still vacant spaces in the conventional left-turn lane between the main and presignals. A modified shockwave-based method was then proposed for estimating the maximum left-turn queue length for the signalized intersections with the CLL design by considering the unique queuing behavior at the presignal. Sensitivity analyses were conducted to identify the impacts of the key parameters in the proposed queue length model on the maximum left-turn queue length. The results suggest that the effective red time duration, the offset between the main and presignals, and the queuing behavior of left-turning vehicles at the presignals greatly affect the maximum left-turn queue length. The proposed queue-length model was validated with the field data considering varying left-turn traffic demands. The results indicated that the proposed model provides reasonable estimates for the maximum left-turn queue length at the signalized intersections with the CLL design. A procedure was also proposed to help determine the minimum distance between the upstream and downstream signalized intersections for the deployment of the CLL design.
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Acknowledgments
This research was jointly supported by the Projects of International Cooperation and Exchange of the National Natural Science Foundation of China (No. 51561135003), the National Natural Science Foundation of China (No. 51608268), the Natural Science Foundation of Jiangsu Province (BK20150747), and the Scientific Research Foundation of the Graduate School of Southeast University (Grant No. YBJJ1678). The authors thank the National Natural Science Foundation of China, the Natural Science Foundation of Jiangsu Province, and Southeast University for supporting this research.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 145 • Issue 6 • June 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Nov 5, 2017
Accepted: Nov 8, 2018
Published online: Mar 20, 2019
Published in print: Jun 1, 2019
Discussion open until: Aug 20, 2019
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