Adaptable robust traffic signal control for urban road networked systems with uncertain capacity

Abstract

In order to effectively mitigate congestion and propagate uncertainty in road networked systems, a robust signal control with adaption to traffic dynamics is presented. A Stochastic Traffic Model (STM) is introduced to appropriately address spatial evolution of traffic congestion inside road links. An Identification of Robust Family (IRF) for Stochastic Performance Index (SPI) is proposed. A stochastic program can be proposed and efficiently solved by a variant of Bendersﾒ decomposition. While time-varying SPI value functions can be improved progressively by proposed adaption algorithm, the feasibility of constraints against high-consequence realization of capacity uncertainty is recursively enforced for unknown probability distribution of occurrence. Numerical experiments are performed at a real-data city road network. As compared to recently proposed the state-of-the-art traffic signal control, obtained results showed that the proposed robust signal control can exhibit sufficient gain of achieving road network effectiveness while attenuating time-varying congestion in the presence of uncertain capacity at links downstream.