Explicit Coordinated Signal Timing Optimization Using Soft Actor–Critic and Model Predictive Control Along an Arterial

Arterial signal coordination requires coupled decisions on cycle length, phase green times, and offsets in an explicit timing plan. This study presents a modular explicit coordinated signal timing optimization (ECSTO) method for a three-intersection arterial. At each cycle-level decision, a soft actor–critic (SAC) agent selects a common background cycle length and offset corrections for the upcoming cycle. A time–space relationship provides base offsets. Modified model predictive control (MMPC) then allocates phase green times using non-negative, intersection-specific cycle adjustments derived from changes between consecutive offset corrections. It does so without a separately scheduled explicit transition cycle. SAC is trained with a phase-weighted discharged-vehicle reward. System vehicle delay and coordinated-direction space-mean speed are used to evaluate and select policies. Across 1000 common demand scenarios in the simulated arterial, ECSTO had 7.16–11.73% lower aggregate mean system vehicle delay and 5.30–10.19% lower total vehicle travel time than five selected explicit timing-control baselines. These reductions remained statistically significant after Holm adjustment. For coordinated-direction space-mean speed, its mean was significantly below four baselines, illustrating a trade-off between system-wide efficiency and coordinated-direction speed. Ablation results describe differences among four tested timing configurations. The findings are limited to this three-intersection simulation and do not establish field performance or effects in larger networks.