Arizona selects Inrix and StreetLight Data for real-time traffic analysis and planning


The Arizona Department of Transportation (ADOT) has selected a suite of traffic products from leading supplier of transportation analytics and connected car services Inrix to support efforts to more effectively monitor, measure and manage the state’s highway network.

As part of the agreement, ADOT will also use StreetLight Data’s visualization platform to help transform Inrix and other geospatial data into travel pattern analytics for statewide modeling. ADOT will now have greater insight into highway performance and problem areas, enabling better informed infrastructure planning, and transportation investments. Analysis of traffic patterns through the suite of tools will enable the state to manage the performance of its road networks while minimizing costs.

Inrix is a leading provider of real-time, historical, and predictive traffic information, with broad road coverage across the USA. With historical data and multi-year trend analysis collected from more than 300 million ‘connected’ sources, including commercial fleets, GPS, cell towers, mobile devices, and cameras, the company’s data is being used to assist states with setting and tracking progress against new federally-required mobility performance targets.

To improve its system planning, traffic management, and operations, ADOT will use a suite of analytic tools and traffic services from Inrix and StreetLight Data, including:

• Inrix Analytics, a suite of on-demand, cloud-based analysis tools that use the company’s traffic data across the USA. They help transportation professionals understand what is happening on the roads, benchmark and improve roadway performance, and maximize the investment of public funds. The platforms enable ADOT to analyze, visualize and understand road performance without the need for additional technology investments. The data and reporting is in partnership with the University of Maryland’s Center for Advanced Transportation Technology Laboratory (CATT Lab);

• Inrix Real-Time Traffic Flow uses anonymous, real-time GPS data from millions of connected vehicles and devices to deliver the broadest and most accurate traffic information on freeways, highways, interstates and major arterial roads. Inrix enables transportation agencies to monitor live traffic data, including roadway name, time, current speed, typical speed and travel time;

• StreetLight Data’s InSight on-demand, cloud-based platform for transportation analytics, which will allow ADOT to design, run, visualize, and download analyses, such as origin-destination matrices for commercial trucks and personal travel modes. The InSight platform combines the power of Inrix data, location-based services data from smart phones, and ADOT’s own traffic counts, with rich contextual data sets for a unique and powerful set of analytics.

“ADOT is further enhancing road performance management across the entire state with our on-demand traffic data and mobility services,” said Scott Sedlik, vice president and general manager for the global public sector at Inrix. “State officials can now quickly identify and understand specific problem regions throughout Arizona, efficiently resolve any issues, and deliver valuable travel information to drivers.”

Dallas Hammit, ADOT state engineer and deputy director for transportation, commented, “Inrix real-time traffic services help us better understand how the motorists use state highways, so we can more effectively manage our system, and prioritize how we’ll invest limited transportation funding.”

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About Author


Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).