Macroscopic Fundamental Diagram-Based Integral Sliding Mode Perimeter Control for Oversaturated Regions
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 9
Abstract
Macroscopic fundamental diagram (MFD)-based perimeter control has a potential to improve traffic throughput and relieve the overall congestion. In practice, not only the MFD but also the traffic demand suffers from a variety of inherent uncertainties. Hence, this paper aims to contrive a robust control technique to address the perimeter traffic flow control issue in the oversaturated region. To this end, an integral sliding mode control is proposed to drive the traffic state to the desirable condition. The developed strategy deals with practical issues such as finite time stability and range of uncertainty in both MFD and traffic demand. Theoretical analysis verifies that the developed integral sliding mode control approach can guarantee the finite time convergence of the traffic state to the desired one. The performance of the developed scheme is attested by considering various traffic scenarios with uncertain MFDs and traffic demand, in which a comparative performance study with the proportional and integral control method is conducted. It is indicated that the developed scheme can alleviate the congestion in the urban network and improve the throughput of the urban network.
Practical Applications
The research presented in this article proposes a novel perimeter control technique designed to enhance traffic flow management in densely populated urban road networks, particularly during peak congestion times. By leveraging the macroscopic fundamental diagram (MFD) and integral sliding mode control theory, the method significantly boosts traffic throughput and alleviates the impact of congestion. This advancement can be seamlessly integrated into current urban traffic management systems, leading to more efficient and convenient urban commutes. Additionally, it addresses the rise in vehicle emissions due to heavy traffic, aiding in the reduction of pollution and supporting sustainable development initiatives. The technique also curtails vehicle fuel consumption and cuts down on costs associated with congestion-related delays, thereby fostering resource optimization and economic growth within urban environments. Moreover, the method is designed to be resilient, taking into account the variability of traffic demand and ensuring the robustness of the traffic control strategy. Overall, the article demonstrates the practical application of advanced control technologies to address real-world traffic challenges, providing a scalable and robust solution adaptable to realistic situations with the uncertainties of urban traffic demand.
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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 work was supported by the National Natural Science Foundation of China under Grant No. 52272309, the National Natural Science Foundation of China under Grant No. 62303325, and the Shanghai Science and Technology Innovation Action Plan Morning Star Project (Sail Special) (No. 23YF1429700).
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© 2024 American Society of Civil Engineers.
History
Received: Jul 20, 2023
Accepted: Apr 9, 2024
Published online: Jun 26, 2024
Published in print: Sep 1, 2024
Discussion open until: Nov 26, 2024
ASCE Technical Topics:
- Continuum mechanics
- Deformation (mechanics)
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Infrastructure
- Integrals
- Mathematics
- Motion (dynamics)
- Sliding effects
- Solid mechanics
- Structural mechanics
- Traffic analysis
- Traffic congestion
- Traffic engineering
- Traffic flow
- Traffic management
- Transportation engineering
- Uncertainty principles
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