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StreetLight Data launches on-demand daily traffic counts

The company has data on four million miles of roadway, which covers nearly every road in the Continental US

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StreetLight Data AADT metrics can provide invaluable insight for transportation strategies
StreetLight Data AADT metrics can provide invaluable insight for transportation strategies

Mobility analytics company, StreetLight Data, is launching a new on-demand service providing annual average daily traffic (AADT) metrics, available through the StreetLight InSight platform.

 

The ability to get such data on-demand, in theory, eliminates the need to employ staff or consultants to undertake manual counts, or installing equipment for the purpose of counting, 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,” said Stephen Yoon, senior regional planner at SCAG, the largest metropolitan planning organisation in the US.

 

“Using advanced modelling techniques, we turn a few days of real-world data into an estimate of average daily traffic for an entire year. Unfortunately, most public agencies lack the resources to install and maintain permanent counters on every roadway they want to measure."

 

365 days of traffic data

 

StreetLight Data measures and analyses the movements of millions of vehicles across four million miles of US roadway, collecting and processing 365 days of traffic data, which comes from more than 65 million smart phones, connected cars and connected trucks, as well as census data, road network information, and more.

 

The AADT counts are available for any road, big and small and rural and urban areas. StreetLight Data claims its 2017 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 US were used to train and validate the big data algorithms behind 2017 AADT.

“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"

“Years of fine-tuning our proprietary algorithms, powered by machine learning and deep mobility analytic techniques, give our 2017 AADT metrics unmatched accuracy,” explained Laura Schewel, CEO and co-founder of StreetLight Data.

 

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 Schewel.

 

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