StreetLight InSight® for Transportation

Transportation modelers, planners, and engineers need accurate, precise, and comprehensive data about how people move. With our StreetLight InSight platform, you can use the best Big Data resources to analyze real-world travel behavior on your computer.

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 comprehensive and precise than many traditional data resources. Our Metrics include:

Origin-Destination Matrices

Origin-Destination Matrices

Trip Purpose

Trip Purpose

Select Link Analyses

Select Link Analyses

Average Travel Times and Travel Time Distributions

Average Travel Times and Travel Time Distributions

2016 AADT

2016 AADT

Commercial and Personal Travel Vehicle Comparisons

Commercial and Personal Travel Vehicle Comparisons

Learn More About Our Metrics

 

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.

*Most StreetLight InSight Metrics are processed in minutes, but processing times vary analysis-by-analysis. Contact us to discuss your needs 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 and commercial trucks, fitness trackers, and more. 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.

Learn More About Our Data Resources and Processing Technology

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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