We believe in transparency about our process. Learn more about where we source our data, our process for analyzing it and converting it into useful metrics, and the validation studies that support its accuracy.
StreetLight VMT Monitor Methodology and Validation White Paper
This white paper outlines our motivation, methodology, and some validation results for StreetLight Data’s daily Vehicle Miles Travelled (VMT) Monitor.
StreetLight AADT 2019 Canada Methodology and Validation White Paper
When you’re looking for up-to-date AADT counts in your Canadian provinces, turn to StreetLight to get quick, easy, cost-effective AADT measures. Our 2019 metric is an update to our previously released 2018 metric, and it continues to outperform industry-standard accuracy targets.
AADT 2019 Methodology and Validation
StreetLight Data developed an accurate AADT for over four million miles of urban and rural roadway in the U.S. that outperforms industry-standard accuracy targets and can be used by industry practitioners for traffic impacts studies and more.
Multimode Methodology and Validation
We are transparent about sharing the methodology for deriving our active transportation metrics, and the validation supporting the data. Learn how our metrics focus on commuter and household travel rather than fitness travel
Traffic Volume Methodology and Validation White Paper
Our white paper shares technical details about the methodology, algorithm development, validation, and data sources used in our traffic Volume output.
Turning Movements Validation White Paper
Using StreetLight InSight® to calculate turning movement ratios, focusing on validation of unique, Big-Data derived travel pattern analytics against publicly available turning movement ratios derived from traffic counts.
AADT 2018 + Canada White Paper
Learn more about technical details about the methodology, algorithm development, validation, and data sources used in StreetLight Data’s AADT 2018 + Canada metrics.
Enriching Household Travel Surveys with Big Data Metrics
Travel surveys are best at capturing subjective, not objective, information. Learn how Big Data gathers fast and accurate measurements for transportation studies.
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