Urban Expressway Congestion Forewarning Based on Slope Change of Traffic Flow Fundamental Diagram
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 6
Abstract
Traffic congestion has become a significant problem that hinders the proper functioning of the transportation system. Traffic congestion forewarning methods can provide traffic management with accurate congestion prediction information, thus taking timely measures to avoid or alleviate traffic congestion. In this paper, we propose a data-plus-model framework-based expressway congestion forewarning method that can be used in the absence of high-quantity and high-quality data. First, we applied historical traffic flow data to determine the approximate extent of the traffic congestion forewarning and fitted a proper traffic fundamental diagram to characterize the traffic flow. Then, the critical congestion forewarning parameters were obtained according to the slope change of the fundamental diagram. Finally, the proposed method was applied to an expressway section in Beijing to forewarn of traffic congestion with multiday historical traffic data. The experimental results show that the proposed method can effectively analyze the trend of traffic flow accurately and quickly give early forewarning of congestion, which is helpful in reducing the occurrence and persistence of congestion.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was supported by the China Postdoctoral Science Foundation (2021M700304).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 6 • June 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Nov 29, 2021
Accepted: Feb 11, 2022
Published online: Apr 7, 2022
Published in print: Jun 1, 2022
Discussion open until: Sep 7, 2022
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