Public transit is a key component of cities’ mobility networks, especially in dense urban centers. Trains and buses help commuters avoid the hassle of traffic jams on congested roadways, not to mention pricey parking. But some cities are attracting commuters and residents so quickly that public transit cannot keep up -- just ask anyone who lives in Denver, Colorado.
The population in Denver has grown by ~45% since 1996, and the average commuter there now spends 49 hours per year sitting in traffic, but only 4.4% of commuters use public transit (Source: Denver Post). Similar scenarios are playing out across the US in cities like Austin, Seattle, San Francisco, and more. Even though alternatives to driving are available in many of these growing cities, not enough commuters are using them – and congestion keeps getting worse.
Traditionally, public transit planners improve systems by looking at existing transit users’ behavior. They identify potential users as those who live and work near transit stations. But in this era of rapid urban population growth, we cannot consider these groups alone: What about the people who are driving because transit isn’t currently a viable option? What about the people who could be using the transit to commute, but aren’t? In this blog post, I’ll walk you though a few ways Big Data can help address these questions.
We’re excited to share that StreetLight Data has a new public agency partner: Minnesota Department of Transportation (MnDOT). The agency recently signed up for a one-year pilot of our Regional Subscription to StreetLight InSight®, the first online platform that turns Big Data from mobile devices into transportation Metrics.
MnDOT’s Regional Subscription provides designated users with unlimited access to StreetLight InSight for Metrics in the state of Minnesota (and a buffer area). That means MnDOT’s Regional Subscription users can design and run as many StreetLight InSight transportation studies as desired to during their subscription term – without any incremental costs or additional procurement processes.
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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.
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.
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:
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.
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.