Queue-Based Traffic Signal Control Considering Vehicle Delay Balancing for Urban Road Networks
Year: 2026
Type: article
Abstract: Traffic signal control is effective in mitigating network congestion. However, most network signal control strategies ignore the fairness of phase service at individual intersections, resulting in excessive delays for low-volume movements, particularly under unbalanced demand patterns. Although some multi-objective network control methods have been proposed to address the fairness-related issues, reweighting the objectives under different traffic conditions requires significant computational effort. This study proposes a novel queue-based Model Predictive Control (MPC) framework that incorporates delay balancing into signal control optimization for road networks. Built upon an extended segment-level flow propagation model, the proposed MPC predicts queue length and flow dynamics without relying on a sophisticated spatiotemporal discretization of road segments. Aunified MPC formulation is then developed, which incorporates a virtual queue mechanism that simultaneously minimizes turn-level queue lengths and enhances delay equity across different vehicle movements. Simulation results on both a single intersection and a network demonstrate the superiority of the proposed MPC compared to existing rival methods, and it is robust against flow prediction errors.
Institutions: Beihang University, Baidu (China)
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W7213428342