Dynamic Systems Modeling and Integrated Transportation Demand-and-Supply Management with a Polynomial Arrival Queue Model
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 4
Abstract
Dynamic systems modeling (DSM) provides an opportunity to systematically investigate traffic system dynamics at the network scale. However, simulation-based DSM approaches are often criticized for their heavy computational burden and low efficiency, as well as the difficulty in calibrating and validating their results. In this study, we propose an analytical modeling approach that integrates the analysis of both demand and supply sides using the polynomial arrival queue (PAQ) model. This model approximates the arrival rate by a polynomial function and the discharge rate by a constant, offering an efficient and accurate representation of traffic dynamics. Our proposed approach allows for the joint optimization of demand regulation policies and infrastructure capacity-building efforts, addressing the shortcomings of locally oriented congestion reduction strategies in isolation. This integrated approach is of great importance for transportation network modeling, management, and control. Overall, our study presents a novel and effective approach to transportation engineering, utilizing DSM and analytical modeling to optimize both demand and supply sides, ultimately improving transportation network performance.
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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.
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 150 • Issue 4 • April 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Jun 14, 2023
Accepted: Oct 26, 2023
Published online: Jan 27, 2024
Published in print: Apr 1, 2024
Discussion open until: Jun 27, 2024
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