Flow Labs, an AI-powered transportation software provider, has unveiled a new, proprietary standard for intersection performance measurement, helping agencies to analyze signal operations and reduce congestion.
The Integrated Signal Performance Measures (ISPMs) offer a more comprehensive approach to signal performance management, according to Flow Labs, enabling improved accuracy, better decision support, and an entirely new strategy for addressing the limitations of traditional methods.
ISPMs use AI to integrate multiple datasets, including detection, signal, and probe data, representing a significant step forward in traffic management with the potential to dramatically improve mobility nationwide.
The deployment of Automated Traffic Signal Performance Measures (ATSPMs), and more recently Probe-Based Signal Performance Measures (PBSPMs) have significantly advanced intersection management over the past decade or more. While they’ve been helpful in providing engineers with tools to better understand signal performance, these more traditional methods have shown limitations, particularly concerning data completeness and accuracy.
ATSPMs, for example, provide crucial insights for signal retiming and traffic flow improvement, but rely on connectivity and expensive hardware, including detection devices that are frequently inaccurate. On the other hand, PBSPMs provide a regional hardware free solution, but offer limited diagnostic capabilities to identify signal issues, and sometimes lack accuracy due to low probe data penetration rates.
To overcome these varied challenges, Flow Labs developed ISPMs, building on the strengths of both technologies.
“Despite the advancements in signal performance measures over the last several years, many signals across the country continue to perform poorly, causing endless gridlock in communities,” said Jatish Patel, founder and CEO of Flow Labs. “ATSPMs and PBSPMs have had a profound impact on signal analytics and have allowed signal management to get closer to its destination. We developed ISPMs to get us the whole way there, simultaneously combining the strengths and eliminating the weaknesses of its predecessors.”
By combining multiple datasets, including detection, signal, and probe data, Flow Labs’ ISPM uses AI to integrate the information into a more comprehensive and accurate analysis of signal performance. This holistic approach not only addresses the limitations of traditional measures, but also enhances diagnostic capabilities, decision support, and overall traffic signal management.
Flow Labs noted that ISPMs are not simply the addition of ATSPMs and PBSPMs. Instead, by compiling and analyzing various datasets, an ISPM can provide innovative performance measures that are not available in either, including detector health measures, accurate turning count movements, hardware-free red light running and dilemma zone entry detection, freight and truck activity, vulnerable road user and other safety insights.
Patel concluded, “ISPMs are a scalable, cost-effective solution that gives agencies the most comprehensive and accurate view of their intersections. It allows them to understand network behavior, and with decision support, adjust signal timing plans which can significantly reduce regional congestion and ease driver stress.”
