Integrated traffic control for mixed urban and freeway networks: A model predictive control approach

van den Berg, Monique; Hegyi, Andreas; De Schutter, Bart; Hellendoorn, Hans · 2007 · OpenAlex-citations

DOI: 10.18757/ejtir.2007.7.3.3390

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Summary

This paper addresses the challenge of managing traffic congestion in mixed networks comprising both urban roads and freeways. The authors argue that current control systems typically treat these two network types in isolation, despite their strong interdependence; for instance, freeway congestion often spills back onto urban roads, while urban traffic management policies may displace congestion onto freeways. To resolve this, the study proposes an integrated control approach using Model Predictive Control (MPC) to optimize traffic flow across the entire network, preventing the shifting of problems between road types and improving overall performance. The methodology involves developing a macroscopic traffic flow model specifically designed for mixed networks. For the freeway component, the authors use an extended version of the METANET model, adding specific logic to handle off-ramp blocking and spill-back effects. For the urban component, they employ a modified queue-length model based on Kashani’s work, extended to account for horizontal queues, turning-direction dependencies, and intersection blocking. These models are coupled via on-ramps and off-ramps, with a computational framework that reconciles different simulation time steps for urban and freeway segments. The control strategy utilizes MPC, which determines optimal control inputs—such as signal timings and ramp metering rates—online by minimizing a cost function over a prediction horizon using a receding horizon approach. The study evaluates the proposed method through a case study using a simple benchmark network. The integrated MPC approach is compared qualitatively and quantitatively against implementations of existing dynamic traffic control systems, specifically SCOOT for urban areas and UTOPIA/SPOT for freeways. The results demonstrate the potential benefits of the integrated approach, showing that coordinated control can achieve better trade-offs between urban and freeway performance compared to isolated systems. The findings indicate that the MPC method effectively handles the complex interactions between the two network types, validating the theoretical framework. The significance of this work lies in its contribution to the field of traffic management by providing a unified modeling and control framework for mixed networks. By demonstrating that integrated control outperforms segregated approaches, the paper motivates further development of MPC-based systems for real-world applications. It highlights the importance of considering the coupled nature of urban and freeway traffic to avoid suboptimal outcomes where improvements in one area degrade performance in another. The proposed macroscopic model and control strategy offer a computationally efficient solution suitable for online implementation, addressing the need for effective, short-term traffic management without requiring new infrastructure.

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• mental model of traffic