Traffic signals may be part of every city, but the way agencies manage them is changing rapidly.
For decades, traffic engineers relied on scheduled retiming, field observations, and citizen complaints to guide signal improvements. While sometimes effective, these traditional methods often miss underlying issues.
Advances in signal performance measures (SPMs) are reshaping this landscape. With the rise of connected vehicle data and GPS-enabled probe technology, agencies now have access to continuous, network-wide insights that make it possible to shift from reactive operations to proactive, performance-based management. The recent INRIX Unlocking the Power of Traffic Signal Performance Measures (SPMs) webinar explored this evolution and highlighted how INRIX Signal Analytics is providing unprecedented visibility into how signals operate in the field.
A Century of Signals, Decades of Measuring Performance
Traffic signals have existed since the early 1900s, but systematic performance measurement developed much later. A major step forward came with the Highway Capacity Manual, which provided standardized definitions for key performance concepts such as control delay, level of service, capacity, and progression quality. While the HCM did not rely on real time data, it established the performance metrics and analytical framework that still underpin how signal operations are evaluated today.
Building on this foundation, the late twentieth and early twenty first centuries saw the emergence of detector–based measurement systems using loop detectors, magnetic sensors, and other fixed infrastructure. These technologies enabled more direct observation of signal operations and led to high resolution, controller–based SPMs that quantified arrivals on green, split failures, queue formation, and other indicators of signal health. Although powerful, these systems required dedicated hardware, communications, and ongoing maintenance, which limited their scalability and made network wide deployment costly.
The next major shift came with widespread adoption of GPS equipped vehicles and connected car networks. Vehicles effectively became mobile sensors, offering a scalable and cost–effective way to observe intersection performance without relying on roadside infrastructure. Signal Analytics builds on this evolution by delivering cloud based, hardware free SPMs that agencies can deploy across their networks without installing or maintaining additional equipment.
From Traditional Practices to Performance-Based Operations
Historically, agencies have managed signals through two main approaches:
- Scheduled Retiming: Signals are retimed every three to five years as part of capital programs. While effective, this means resources are spent on signals that may not truly need adjustment. Also leading issues that arise between cycles can go unnoticed for months or years.
- Complaint-Driven Management: Citizen feedback provides real-world insight, but it often reflects isolated experiences. Complaints are also biased toward vocal road users rather than the locations with the greatest operational needs.
Performance-based operations flip this model. Instead of waiting for problems to surface, agencies use continuous data to detect when and where issues occur. This approach enables:
- Real-time awareness of emerging issues
- Prioritization of corridors in need of retiming
- Objective validation of complaints and model assumptions
- Faster response to detection failures or construction disruptions
- Clear before-and-after measurement of improvements
Probe-based SPMs make this shift possible at scale. The Comparison Mode feature in Signal Analytics is also designed specifically to simplify before-and-after studies and support reporting.
How Probe-Based Signal Performance Measures Work
Probe data is derived from connected vehicles traveling through intersections. Each vehicle provides timestamped GPS waypoints. By analyzing these traces, Signal Analytics determines:
- When vehicles arrive at and depart from intersection areas
- Whether they stop or pass through on green
- The delay experienced at each approach
- The movement taken (left, through, right)
- The travel time pattern across different times of day
These individual traces are combined into key performance metrics such as:
- Average control delay
- Percent arrival on green
- Excessive delay (3+ minutes) as a proxy for split failures
- Turn movement ratios
- Vehicle counts and demand patterns
- Time–space trajectory plots
These metrics reflect the actual behavior of real vehicles, providing accurate, field-measured insights. Signal Analytics packages these metrics into dashboards and sortable lists, allowing agencies to quickly pinpoint unusual patterns.
Core Use Cases for Agencies
Probe-based SPMs give agencies a fast, data-driven way to detect operational issues such as sudden delay spikes, abnormal arrival-on-red patterns, construction impacts, or equipment failures, often within hours. This early insight helps engineers validate citizen complaints, confirm whether simulation models match real-world conditions, and understand where problems truly exist.
By combining sortable lists, trends, and comparison tools, agencies can prioritize corridors or intersections that need the most attention, ensuring staff time and funding are used effectively. These same tools also make it easy to quantify before-and-after conditions, showing how travel times or delays change following timing updates, technology deployments, or corridor improvements helping agencies demonstrate value and refine their strategies.
Empowering the Future of Traffic Operations
SPMs are no longer just a specialized tool; they are becoming an operational necessity. With scalable, probe-based solutions, agencies can achieve the level of network-wide visibility needed to manage signals proactively. The result is more efficient operations, faster response to issues, better use of resources, and improved mobility for everyone on the road. Signal Analytics plays a pivotal role in this shift, giving agencies continuous, real-world signal performance data without installing hardware or modifying controllers.
To learn more about Signal Analytics visit: inrix.com/products/signal-analytics/