Mobility Analytics Blog

StreetLight Data Blog

The latest news about Big Data and mobility analytics.

Blog Feature

Modeling Travel Demand: Introducing StreetLight InSight® Metrics for PTV Visum

We’re excited to share that StreetLight Data and PTV Group have taken the next step in our partnership: Our first integration of StreetLight Data’s transportation analytics into PTV Visum, one of PTV Group’s flagship software platforms for travel demand modeling. For the first time, transportation professionals can use up-to-date, comprehensive Big Data analytics in their models in just a few mouse clicks.

Our new feature means that modelers do not have to manually process .CSV files or write custom code to use our origin-destination matrices in their Visum models. Instead, they can install the StreetLight Add-In to Visum, then pull in the data they need in a flash. In this article, we’ll explain why we decided to build an integrated data solution for modelers, how it works, and the next steps for our partnership.

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Blog Feature

Big Data  |  Case Studies  |  Transportation

Ohio DOT Selects StreetLight Data and INRIX for On-Demand Mobility Intelligence

Ohio Department of Transportation (ODOT) recently selected StreetLight Data to provide on-demand transportation studies along with one of our partners, INRIX. We’re thrilled to see ODOT join the hundreds of public agencies across the US and Canada that benefit from our Big Data analytics. 

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Blog Feature

Big Data  |  Location-Based Services  |  Transportation

Real-World Travel Patterns: Who Works on Labor Day?

The Labor Day public holiday celebrates American workers by giving them the day off – or at least, that’s the idea.  Here at StreetLight Data, we wanted to find out how many American workers are still commuting to their jobs on Labor Day. The results were surprising: Only about ~56% of American workers get the day off nationwide, with some variation in results across different states. In this blog post, we’ll walk you through our analysis of Labor Day travel patterns.

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Blog Feature

Big Data  |  Traffic

Why Big Data Matters for Traffic Congestion Studies

Traffic congestion negatively effects the economy, roads and our quality of life. Some people tend to blame pass-through trips, commercial attractions or employers, but expectations don’t always line up with hard data about what really causes congestion.

In California’s Napa County, for example, it is common to blame traffic on wine-tasting tourists. However, when planners used Big Data to map out travel behavior in traffic congestion studies, they found out that commuters actually contributed as much to congestion as tourists. High housing costs in Napa are a major part of the problem.

It’s not easy to figure out why congestion happens, especially in downtown districts. Learn how to improve the accuracy of your traffic congestion studies by using analytics derived from Big Data.

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Blog Feature

Big Data  |  Performance Measurement  |  Smart Cities  |  Transportation

Big Data and Air Quality: Understanding Vehicle Emissions

This year, the Eastern Research Group (ERG), Coordinating Research Council (CRC), and StreetLight Data teamed up to validate one of the big as yet unmet promises for Big Data – the ability to better model and thus manage criteria pollutant air emissions from vehicles.

The results of our work show that using Big Data to model emissions at the county level is more accurate than industry-standard practices today. Of three different counties we analyzed, we found that:

  • Two counties would have overestimated their emissions if they used the industry-standard approach, and
  • One would have underestimated emissions by as much as 14% for a typical day and up to 110% in an individual hour.

Modeling emissions accurately matters: It allows air quality models to better predict concentrations of the regulated air pollutants ground-level ozone and particulate matter in different counties, which informs air quality planning and control strategies at the local level. In this blog post, we will walk you through the new methodology and some of our key findings.

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Blog Feature

Big Data  |  Mobile  |  Software Updates  |  Transportation

Let’s Get Transparent: The Size of Your Big Data Sample

Locational Big Data – the geospatial data created by mobile devices – is ubiquitous. Smartphones, connected cars, fitness trackers, and more create trillions of location records as their users go about their daily lives. There are many benefits of this Big Data, but one, of course, is large sample size. But just knowing something is “large” is not always enough. Many of our clients want to know more detailed info on sample size for individual projects. It helps them understand certainty of results.

In this blog post, I’ll explain how we’ve updated StreetLight InSight® (that's our easy-to-use online platform for transforming Big Data into transportation analytics) so that our clients always know the size of the sample they’re working with.

 

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