Model predictive control of arterial traffic networks: A positive system approach

Abstract

This paper proposes a model predictive control approach to alleviate traffic congestion in urban arterials within a positive systems framework. The prediction model is based on a cumulative storeand-forward formulation, representing arterial network dynamics through cumulative link inflows and outflows. A piecewise affine outflow function is adopted, with switching conditions determined solely by current and predicted cumulative flows, ensuring the active mode is independent of the optimization variables. The network-wide traffic signal control problem, including all constraints, is formulated as an optimization problem with a linear objective function maximizing cumulative arterial outflow, with green times as control variables. Numerical results indicate that the proposed method reduces average travel time by 39.3% compared to fixed-time control and decreases mean solver computation time by 42 seconds per cycle compared to a quadratic objective formulation, confirming real-time applicability on the Nicholson arterial in Melbourne, Australia.