StreetLight Data Unveils Accurate On-Demand Traffic Counts for 4 Million Miles of Roadway - Nearly Every Road in the Continental U.S.
New Annual Average Daily Traffic (AADT) for 2017 Enables Smarter Cities and Better Data-Driven Infrastructure Decisions
SAN FRANCISCO, Oct. 24, 2018 /PRNewswire-PRWeb/ -- StreetLight Data, Inc., the leader in big data analytics for mobility, today announced another major transportation market innovation with the launch of its new Annual Average Daily Traffic (AADT) metrics available on-demand through the StreetLight InSight® platform.
Annual traffic counts available on-demand for any roadway in the U.S. are a holy grail for transportation planners and engineers. Historically they have had to task staff or consultants with manually counting, installing equipment or modeling traffic, which isn't feasible or accurate for understanding road congestion at scale.
"For most roadways, we collect AADT using temporary traffic count sensors that operate for two to seven days with limited information. Using advanced modeling techniques, we turn a few days of real-world data into an estimate of average daily traffic for an entire year," said Stephen S. Yoon, Senior Regional Planner at SCAG, the largest metropolitan planning organization in the U.S. "Unfortunately, most public agencies lack the resources to install and maintain permanent counters on every roadway they want to measure."
"We measure and analyze the movements of millions of vehicles across 4 million miles of U.S. roadway, collecting and processing 365 days of traffic data," explained Laura Schewel, CEO and co-founder of StreetLight Data. "Years of fine-tuning our proprietary algorithms, powered by machine learning and deep mobility analytic techniques, give our 2017 AADT metrics unmatched accuracy."
Available for any road – big and small, rural to urban areas – the company's 2017 AADT counts outperform industry-standard accuracy targets, as published recently in StreetLight's 2017 AADT Methodology and Validation white paper. Data from over 2,400 permanent count stations across the U.S. were used to train and validate the big data algorithms behind 2017 AADT.
The diversity and accuracy of data feeding StreetLight's AADT algorithms are a key competitive advantage. They include 365 days of data from over 65 million smart phones, connected cars and connected trucks, as well as census data, road network information, and more. StreetLight's data resources are larger and more spatially accurate than cellular data used by competitors.
With new federal requirements put in place by the "Moving Ahead for Progress in the 21st Century Act" (MAP-21), local and state government agencies must increase reporting of performance metrics for planning and funding allocation. This, in turn, has increased the need for quick, easy, dynamic and cost-effective AADT measurements.
"An accurate count of vehicles on the road is the fundamental building block for so much of what we need to measure about transportation – safety, environmental impact, congestion impact, and more. Our 2017 AADT metric is the first step among many exciting new analytics our data science team is building," said CEO Laura Schewel.
Learn more at StreetLightData.com/AADT.
About StreetLight Data
StreetLight Data pioneered the use of big data analytics to help transportation professionals solve their biggest problems. Applying proprietary machine learning algorithms to over 4 trillion mobile location data points, the company measures diverse travel patterns and makes them available on demand via the world's first SaaS platform for mobility, StreetLight InSight®. From identifying sources of congestion to optimizing new infrastructure to planning for autonomous vehicles, StreetLight powers more than 1,500 projects globally every month.
SOURCE StreetLight Data, Inc.
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