Detector vs. trajectory generated Automated Traffic Signal Performance Measures (ATPMs)

This white paper evaluates traditional detector-based ATSPMs against the emerging use of high-resolution connected car (HRCC) trajectory data. While detector-based methods rely on costly, fixed hardware like loops or radars with limited accuracy and coverage, trajectory-based ATSPMs—enabled by SMATS’ iNode platform and connected car data—offer a flexible, infrastructure-free alternative.

Trajectory data enables richer, lane-level insights into metrics like control delay, Arrival on Green (AOG), split failures, downstream blockage, and level of service, often with fewer samples but greater accuracy. It also supports intuitive visualizations, eliminates guesswork, and scales effortlessly across intersections. The paper concludes that trajectory-based ATSPMs provide a more cost-effective, scalable, and precise solution for agencies seeking to modernize signal performance management.