From Sensing to Decision: A Generic Architecture for Freight Signal Priority Systems

In a new paper accepted at ITSC 2026, Ziyan Zhang and six co-authors systematically review Freight Signal Priority (FSP) systems from a sensing-to-decision perspective. They propose a generic two-layer architecture: a sensing-to-decision layer that transforms raw inputs (from loop detectors, vision sensors, or V2I) into priority decisions, and a control execution layer that implements approved actions in traffic controllers. The study compares major sensing modalities across dimensions like classification capability, state estimation accuracy, latency, and information richness, highlighting how propagation of uncertainties in vehicle detection, communication, and estimated time of arrival (ETA) can affect priority timing and downstream signal performance.

Unlike prior work that focused solely on priority control algorithms, this review explicitly links sensing design to decision outcomes. The authors examine representative FSP systems to show how modality-specific characteristics influence ETA computation and priority triggering. They identify key deployment challenges—such as sensor noise, communication delays, and lack of reliability-aware design—and highlight research gaps. By assuming no idealized inputs, the proposed architecture provides a conceptual foundation for building scalable FSP systems that can operate robustly under real-world uncertainties, ultimately improving freight mobility and reducing corridor delays in urban networks.