Control Strategy for Ramp Traffic Based on Improved ALINEA Algorithm
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 11
Abstract
This study presents a ramp control strategy that builds upon the ALINEA framework to enhance the throughput of expressways equipped with vehicles-to-everything capabilities. The conventional ALINEA control strategy relies on input flow data from the previous cycle, which may not accurately reflect the current traffic conditions. To overcome this limitation, the gate recurrent unit is employed to predict the current traffic volume, serving as an improved input flow. Furthermore, a novel combined ramp control strategy is proposed in consideration of the driver’s tolerance level under the constraints of ramp queuing. This combined strategy selectively employs different ramp control methods based on the varying queuing conditions of vehicles on the ramp. A comparative analysis with the conventional ALINEA control strategy reveals that the improved ALINEA approach can reduce total travel times by up to 9.84% in merging area, concurrently reducing ramp queues length by 23.30%. The research used predicted traffic parameters for ramp control, which is a new framework for achieving active traffic control on ramp. In addition, the ramp control strategy takes into account the balance between the ramp and the main line, which is very helpful for avoiding the influence of ramp vehicles on adjacent urban streets.
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Data Availability Statement
The data, models, and codes used in the study are available from the corresponding author by request.
Acknowledgments
This research was supported by the National Key Research and Development Program of China (No. 2022YFC3803700).
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 150 • Issue 11 • November 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Nov 1, 2023
Accepted: May 31, 2024
Published online: Aug 21, 2024
Published in print: Nov 1, 2024
Discussion open until: Jan 21, 2025
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