Real-time dynamic traffic routing using variable structure control

Majid, Hirsh; Abouaissa, Hassane; Jolly, Daniel; Morvan, Gildas · 2013 · Crossref

DOI: 10.1109/itsc.2013.6728407

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Summary

This paper addresses the problem of real-time dynamic traffic routing (DTR) to alleviate congestion in transportation networks. The authors propose a novel control algorithm designed to minimize the difference in travel times between alternate routes, thereby achieving a user-equilibrium traffic pattern where no single route is overloaded. The motivation stems from the limitations of existing optimization-based approaches, which are often unsuitable for online control due to computational constraints or reliance on nominal models. To overcome these issues, the study employs Variable Structure Control (VSC), specifically sliding mode control, combined with the concept of differential flatness. This approach allows for robust trajectory planning and tracking that is resilient to modeling errors and disturbances. The methodology utilizes the METANET second-order macroscopic traffic flow model to describe the dynamics of traffic density and mean speed. The control input is defined as a split rate variable at diversion points, determining how incoming traffic demand is distributed among alternate routes. The control design consists of two parts: trajectory planning, achieved using differentially flat systems to determine the optimal open-loop control, and trajectory tracking, ensured by a high-speed switched feedback control that forces the system state onto a predefined sliding surface. The paper details the mathematical formulation for a sample network consisting of two alternate routes, each divided into sections, deriving the necessary control laws and switching surfaces based on the system's flat outputs. The study validates the proposed algorithm through numerical simulations on the described sample network. The simulations demonstrate the effectiveness of the VSC-based controller in managing traffic flow under various geometric conditions. By actively adjusting the split rates in real-time, the controller successfully minimizes the travel time differences between the alternate routes. The results indicate that the sliding mode control strategy effectively handles the nonlinear dynamics of the traffic system, maintaining stability and performance despite the complex interactions described by the METANET model. The significance of this work lies in its application of advanced control theory—specifically the combination of differential flatness and sliding mode control—to a practical transportation problem. The proposed algorithm offers a robust solution for online dynamic traffic routing, capable of handling real-time variations and uncertainties better than traditional optimization methods. This approach contributes to the field of intelligent transportation systems by providing a mathematically rigorous framework for reducing congestion and improving traffic efficiency through dynamic route guidance. The paper concludes by outlining potential directions for further development, suggesting the extension of this methodology to more complex network configurations.

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