Minimum required sample size to estimate traffic metrics
Guide to sample size calculation for traffic metrics using Central Limit Theorem formulas and data stacking—no sensors required.
Overview
This white paper offers a clear framework for determining the minimum sample size needed to reliably estimate key traffic metrics—such as travel time, delay, speed, Arrival on Green (AOG), split failure rates, and flow rate (e.g., AADT, VMT, TMC). Drawing on the Central Limit Theorem, it provides formulas tailored to each metric type, accounting for confidence intervals and acceptable error margins.
SMATS further demonstrates how data stacking over multiple days and time periods can help transportation professionals meet sample size thresholds in iNode, their analytics platform. Illustrated use cases show how agencies can enhance the statistical validity of traffic studies without installing physical sensors—streamlining performance measurement for smarter planning and operations.
