INRIX Expands Its AI-Driven Traffic Platform to Power the Next Era of Intelligent Mobility
INRIX, a global leader in transportation data and analytics, has announced a sweeping expansion of its Traffic product family, introducing a new generation of AI-driven capabilities designed to help transportation agencies, public sector organizations, and logistics enterprises transition from reactive traffic management to proactive, safety-centered, and performance-optimized operations. This milestone represents the latest chapter in a two-decade journey of innovation that began when INRIX commercialized the first large-scale system to transform GPS data into real-time traffic intelligence. That breakthrough redefined how cities and businesses understood roadway conditions. In 2019, the company once again pushed the industry forward with the launch of AI Traffic, the world’s first traffic platform to harness deep learning models and artificial intelligence to enhance the quality, consistency, and global scalability of traffic analytics. Today, INRIX is building on that foundation by embedding deeper automation, predictive intelligence, and generative AI across its Traffic portfolio, enabling customers to move faster from analyzing complex transportation data to making informed, real-world decisions that improve safety, efficiency, and mobility outcomes.
From Reactive Monitoring to Proactive, Safety-Focused Operations
The newly introduced capabilities mark a structural shift in how transportation systems are managed. Rather than simply reacting to congestion, crashes, or unexpected disruptions as they occur, agencies and enterprises can now anticipate risks earlier, respond to incidents with greater speed and precision, and plan with higher confidence in the integrity and consistency of their data streams. By automating data normalization, enhancing predictive modeling, and strengthening AI-driven insights, INRIX is equipping transportation professionals with tools that reduce operational friction while increasing clarity. These improvements allow organizations to replace fragmented workflows and manual analysis with scalable, trustworthy systems that continuously process and interpret massive volumes of mobility data. The result is a stronger operational foundation for cities striving to reduce congestion, improve roadway safety, and deliver reliable travel experiences under increasing budget constraints and public expectations.
Bryan Mistele, CEO of INRIX, emphasized that transportation professionals are under growing pressure to do more with fewer resources while simultaneously delivering safer and more dependable road networks. He noted that the company continues to invest heavily in AI across its Traffic product family to improve everyday workflows, helping governments, cities, and commercial enterprises accelerate the transition from data to decisions, from historical reporting to forward-looking predictions, and from isolated insights to measurable action.
AI-Generated Radio Traffic Reports Transform Broadcast Operations
One of the most innovative additions to the Traffic portfolio is the launch of AI Traffic Reporter, a fully automated solution designed specifically for media organizations and radio networks. Building upon the AI-first innovation embedded in INRIX Compass, this new offering uses advanced generative AI to convert validated incident intelligence and connected-vehicle signals into broadcast-ready traffic bulletins. Traditionally, radio traffic reporting required manual scripting, human monitoring, and time-sensitive coordination to deliver updates to listeners. AI Traffic Reporter eliminates these bottlenecks by producing consistent, natural-sounding, human-like traffic updates automatically, around the clock. The system can scale across multiple markets and time zones, ensuring that audiences receive timely, accurate traffic information day or night. By transforming raw roadway events into polished, ready-to-air segments, the product allows broadcasters to streamline operations, reduce staffing pressures, and maintain high-quality reporting standards while leveraging continuously updated traffic intelligence.
Global Expansion of Average Daily Traffic Through Volume Profiles
INRIX has also significantly expanded its global traffic intelligence capabilities with the introduction of Volume Profiles on an international scale. This innovation addresses one of the most critical data needs in transportation planning: reliable, directional, and time-specific vehicle volume information. Built on a sophisticated multi-source AI model that normalizes and validates data against ground-truth benchmarks, Volume Profiles deliver detailed vehicle counts segmented by direction, time of day, and day of week in 15-minute increments. By replacing costly and labor-intensive manual traffic counts with continuously updated digital insights, agencies and businesses gain access to stable, consistent volume intelligence that supports infrastructure planning, roadway safety analysis, commercial site selection, and performance benchmarking. The system provides monthly, quarterly, and annual profiles, offering both granular and long-term perspectives on roadway activity. Importantly, the model reduces reliance on any single data provider, strengthening resilience and accuracy across diverse markets. After initial releases in Canada and the United Kingdom, INRIX plans expanded coverage in Germany, Spain, France, Italy, and Sweden in 2026, reinforcing its commitment to delivering scalable global traffic intelligence.
Observed Speed Distribution Profiles Enhance Roadway Safety Analysis
Understanding speeding behavior has long been a challenge for transportation agencies relying on limited field studies or averaged speed metrics. INRIX has addressed this gap with Speed Distribution Profiles, an advanced dataset that provides a comprehensive statistical view of observed vehicle speeds. Instead of reporting simple averages, the system leverages connected vehicle data to deliver percentile-based speed distributions across roadways, broken down by direction, time of day, and day of week. This richer statistical approach enables agencies to identify systemic speeding patterns rather than isolated incidents. By revealing the full spread of vehicle speeds, transportation planners can pinpoint high-risk corridors, evaluate the real-world effectiveness of enforcement strategies, and assess the impact of roadway design modifications or policy interventions. The result is evidence-based safety management grounded in large-scale, real-world data rather than limited sampling. Speed Distribution Profiles empower agencies to move beyond snapshots and toward continuous, data-driven oversight of roadway risk.
Advancing Map-Agnostic Incident Intelligence with OpenLR
INRIX is further strengthening its commitment to interoperability and long-term scalability by expanding its use of OpenLR-based location referencing. This innovation ensures that traffic and incident intelligence can be delivered consistently across diverse mapping systems without being tied to proprietary map segments or limited Traffic Message Channel coverage. By dynamically referencing incidents on all roads, including off-TMC segments and complex slip roads, the system can accurately associate events with entry ramps, exit ramps, and connector roadways rather than generalizing them to nearby mainlines. This level of precision enhances situational awareness for navigation providers, transportation agencies, and fleet operators. A map-agnostic framework future-proofs the delivery of high-fidelity traffic intelligence, allowing customers to integrate INRIX data into their existing geographic information systems without compatibility barriers. The approach supports diverse road geometries and evolving mapping ecosystems, ensuring long-term adaptability as digital infrastructure advances.
Modernizing Traffic Signals with Continuous AI Analytics
Another cornerstone of the expanded Traffic portfolio is the modernization of signal operations through enhanced Signal Analytics capabilities. Historically, traffic signal performance has been evaluated through periodic retiming studies that rely on expensive field equipment and manual data collection. INRIX is shifting this paradigm by applying advanced analytics and machine learning to probe vehicle data, enabling continuous performance monitoring across signalized intersections and corridors. These enhancements allow traffic engineers to track operational trends over time rather than relying on one-time snapshots. Engineers can more quickly identify inefficient intersections, detect emerging congestion patterns, and measure the real-world impact of timing adjustments or safety treatments. The platform includes improved usability and workflow features designed to reduce the time required to translate performance metrics into actionable signal optimization strategies. Ongoing platform and API upgrades further establish a foundation for continuous innovation and integration with agency systems. By delivering scalable, data-driven insights without imposing additional burdens on engineering staff, Signal Analytics helps agencies improve travel time reliability, reduce intersection-related crashes, and optimize corridor performance at scale.
Building a Scalable and Trustworthy Traffic Intelligence Ecosystem
Collectively, these innovations define a new generation of INRIX Traffic products built around automation, predictive modeling, and AI-powered decision support. The company’s strategy reflects a broader industry transformation in which transportation agencies and enterprises require not only accurate real-time data but also forward-looking insights that anticipate conditions before they escalate into disruptions. By integrating connected-vehicle data, advanced normalization techniques, generative AI, and map-agnostic referencing, INRIX is creating a cohesive traffic intelligence ecosystem that reduces operational complexity while increasing analytical depth. The expanded product family enables customers to move confidently from insight to implementation, reinforcing safety initiatives, improving congestion management, and enhancing overall mobility operations. As urbanization accelerates and transportation systems grow more interconnected, scalable and trustworthy traffic intelligence will be essential to building resilient, efficient, and safer road networks worldwide.
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