Transportation agencies are under increasing pressure to improve traffic operations while working with limited staff, budgets, and field resources. To make the most of their time, engineers need a way to quickly identify problem locations, prioritize improvements, and measure results across an entire network. Probe–based Signal Analytics uses vehicle trajectory data derived from anonymous GPS points to measure how vehicles move through signalized intersections and corridors. By providing continuous visibility into real-world traffic performance, it helps to identify problem locations, prioritize retiming work, and measure results without deploying permanent or temporary detection or running manual counts at every intersection. When to Use Signal Analytics Signal Analytics is especially useful when: - You need to triage a large network but don’t have staff for intersection‑by‑intersection reviews - Complaints are coming in, but it’s not obvious which intersection is causing the problem - You want to evaluate retiming results without running new field studies - Detector coverage is inconsistent, unreliable, or nonexistent - You need network level visibility before deciding where to invest limited time and resources. What Inputs You Need Before Beginning? You don’t need signal timing files or detector data to get value. At minimum you’ll need: - A list of signalized intersections (or a corridor) - A clearly defined time window (e.g., specific dates, weekday AM peak, PM peak) - One or two performance questions (e.g. Where is delay occurring? How well is progression working? Are queues spilling back?) That’s it. What Probe Based Signal Analytics Measures Probe based analytics focuses on what vehicles experienced, not what was programmed. Key measures include: - Arrivals on Green (AOG): Did vehicles make it through without stopping? - Control Delay: How much extra time did vehicles spend because of the signal? - Excessive Delay: How many vehicles waited longer than 3 minutes