Nonlinear Model Predictive Control for Coordinated Traffic Flow Management in Highway Systems
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Date
2020
Publication Type
Conference Paper
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yes
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Abstract
The growing level of freeway traffic congestion comprises an everyday life issue with social, economic, and environmental implications for modern metropolitan areas. There is evidence that Variable Speed Limits (VSL) and Ramp Metering (RM) are two effective practical approaches to ameliorate traffic congestion. In this work we use the augmented METANET model, which is one of the most widely used macroscopic models for freeway traffic, to demonstrate the positive effects that these approaches can have on traffic flow and congestion. Since the modified METANET is a nonlinear model, nonlinear model predictive control (NLMPC) is a control method pathway for this system. It performs as a recursive on-line finite-horizon optimization of nonlinear problems, subject to the system dynamics and additional constraints, and has the privilege of prediction of future system states. We utilized the NLMPC method for the coordination of VSL and RM in highway networks. We simulate the implementation of the proposed control method on a freeway that contains a typical setting of on-ramps, off-ramps, as well as a lane drop that creates a physical bottleneck. The simulation results demonstrate significant improvement in the traffic flow conditions and provide useful insights about the way that VSL and RM manage to achieve this improvement. Understanding the special characteristics of capacity drop in highways, and how to ameliorate it, is crucial for future large-scale implementations. © 2020 EUCA.
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Publication status
published
Editor
Book title
2020 European Control Conference (ECC)
Journal / series
Volume
Pages / Article No.
428 - 433
Publisher
IEEE
Event
18th European Control Conference (ECC 2020) (virtual)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
08686 - Gruppe Strassenverkehrstechnik
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
Notes
Due to the Corona virus (COVID-19) the conference was conducted virtually.
Funding
188622 - Real-time traffic estimation and control in a connected environment (SNF)