Using Big Data to Address Data Gaps and Validate Travel Demand Models
When the pandemic hit, the City of Edmonton, Canada, was unable to run its typically active annual traffic count program, leaving city planners with significant traffic data gaps. Access to Big Data helped provide a complete picture of before and during pandemic traffic patterns that helped validate and refine their regional travel demand model. StreetLight’s Origin-Destination Metrics helped Edmonton planners:
Zero in on pandemic-driven shifts in traffic patterns
Obtain historical data for analysis and model validation
View the entire mobility landscape, gaining insight into traffic volume across the entire city
Learn how you can apply StreetLight’s Metrics to fill traffic count gaps (without the need for heavy investment in traffic programs) and power your infrastructure initiatives.
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“Many Cities and MPOs do not have access to regular traffic counts on low-activity corridors such as local roads. StreetLight is a next-generation data source, offering a more comprehensive traffic picture than we’ve ever had before. The applications are endless.”
Sandeep Datla
Senior Transportation Modeling Engineer
Your biggest transportation challenges require better analytics
Origin-Destination for multiple modes
Granular, on-demand Metrics segmented by time of day and day of week
Layer on demographics, trip attributes, and more
Powering 10,000+ Projects Every Month
Using Big Data to Address Data Gaps and Validate Travel Demand Models
