StreetLight InSight® for Transportation

Transportation engineers and urban planners need accurate, precise, and comprehensive data about how people move. With our StreetLight InSight platform, it takes just a few mouse clicks for transportation experts to study travel patterns with the best Big Data resources .

Set Up and Run Transportation Studies On Your Computer

Unlike with household surveys, license plate studies, sensors, or any other Big Data analytics provider, StreetLight InSight lets you design and run travel behavior analyses with your web browser. There's no software installation, sensor deployment, or survey design required. StreetLight InSight Metrics are not only faster and easier to collect. They're also more accurate, and more comprehensive than analytics derived from most traditional data resources. Our Metrics include:

  • Origin-Destination Matrices
  • Select Link Analyses
  • 2016 AADT 
  • Trip Purpose 
  • Visitor Activity Volume and Home/Work Locations 
  • Average Travel Times and Travel Time Distributions
  • Internal/External Studies
  • Commercial and Personal Travel Vehicle Comparisons

Metrics can be customized to specific times of day, days of the week, and times of year. StreetLight InSight provides visualizations, shapefiles, and CSV files.

Ready to see StreetLight InSight in action?

Watch Our Demo Videos

*Most StreetLight InSight Metrics are processed in minutes, but processing times vary project-by-project. Contact us to discuss your project in detail.

Our Metrics Development Process

StreetLight InSight Metrics are based on Big Data. That's the massive volume of geospatial information created by mobile phones, GPS devices, connected cars, fitness trackers, and commercial fleet management systems. When these devices ping cell towers and satellites, they create location records.

We transform trillions of these anonymized records into useful information with our proprietary algorithmic processing engine, Route Science®. When you use StreetLight InSight, you tap into the useful information that Route Science pulls from Big Data. And you avoid the hassle of manually processing trillions of location records into travel patterns.  

How Our RouteScience Processing Engine Works

Step 1: Deidentify

First, the data is reviewed to ensure all personally identifying information (PII) has been removed by our suppliers. We do this to ensure individual privacy from the beginning, and we do not possess any PII. 

How Our RouteScience Processing Engine Works

Step 2: Clean

Next, we review the data and remove any incomplete or inaccurate data points. For example, if we have only one record for a particular device within a given time period, that data point is removed.

How Our RouteScience Processing Engine Works

Step 3: Patternize

Our next step is to algorithmically link these data points into  activities and trips. We then can identify likely home and work locations as well as origins, destinations, and routes traveled.

How Our RouteScience Processing Engine Works

Step 4: Contextualize

We then contextualize and further de-identify the data, as well as integrate additional data sets. These additional data sets give our Metrics more meaning. They include road network maps, demographic information, parcel and land use data, and more.

How Our RouteScience Processing Engine Works

Step 5: Aggregate

Finally, we normalize and combine these trips into aggregate Metrics. To protect individual privacy, our Metrics only describe groups of devices. They never describe individuals.

Validating Our Metrics

To ensure the accuracy of our Metrics, we validated them against traditional data sources such as Bluetooth-based counting technology and license plate surveys. Read more on our blog or contact us for more details.

Read Our Blog Post
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FREE GUIDE to Unlocking Big Data's Value with Real-World Examples

With Big Data, transportation experts can answer questions about travel behavior that were once unanswerable. Download our "Big Data for Transportation" eBook to learn more.

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