Blog Feature

Big Data

Need Ride-Hailing Services Intel? Big Data Has That.

April 10, 2019

The ride-hailing revolution launched by Uber and Lyft has expanded to embrace shuttles, autonomous vehicles, and micro-mobility options like scooters and bike share.

As ride-hailing services expand, car ownership is decreasing, putting pressure on original equipment manufacturers (OEM) in the automotive industry. Many transportation and mobility companies are working with us to explore business options in this emerging industry.

Planning a ride-hailing business requires researching the target market to understand the best mobility options with strong business potential, and accurately forecasting revenue. But how can a company do that in a business where no data about core patterns exists outside of a few dominant companies who don’t data share? Big Data to the rescue.

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Blog Feature

Big Data

Thank You to Maine for Thoughts on Big Data Privacy

April 5, 2019

We are proud to have recently been selected by the Maine Turnpike Authority to provide comprehensive transportation analytics to help with planning, policy, and operational improvements for Maine’s transportation system. We think this partnership is big news, and so do Mainers!

Several Maine newspapers, online forums, and television outlets have covered the story. The amount of attention that Mainers give their transportation department is impressive, and we encourage thoughtful writing and dialogue about the intersection of big data, transportation, and privacy.

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Blog Feature

Big Data | Transportation

More Transportation Data Fun with Quadruple the Sample Size!

March 25, 2019

One of the most important metrics for our clients is “sample size” - the number of trips or devices analyzed to deliver a specific analysis within StreetLight InSight®. We’re happy to announce that starting with transportation data from January 2019, we’ve doubled our typical sample size since December 2018, and more than quadrupled it since the same time last year! What that means for our clients is better results, especially for areas with lower trip counts. Here’s why.

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Blog Feature

Big Data | Transportation

Big Data Meets Bike-Ped. Interview with Sean Co.

March 12, 2019

Following the launch of the transportation industry’s first bicycle and pedestrian analytics in January, StreetLight Data welcomed seasoned planner and avid cyclist Sean Co to help drive industry adoption of our MULTI MODE analytics. Most recently at Strava, Sean has years of transportation planning experience at consulting firms and government agencies. We talked with Sean about his bike racing background, the power of Big Data bike and pedestrian metrics, and what fuels his passion for active transportation.

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Blog Feature

Big Data | Smart Cities | Transportation

How Does Gig Driving Interact with Congestion? A Road-by-road Analysis.

December 13, 2018
Many of our clients are concerned with new modes of travel and how they interact with existing transportation. Composed of services like Uber, Lyft, Postmates, and Instacart, “Gig Driving” for riders and delivery has been a persistent concern. And its impact on congestion is hotly debated topic at conferences, in the press and among friends. Some claim it makes congestion better (less parking or less personal car driving), and others claim it makes congestion worse. The biggest challenge to finding the answer is a deep lack of available data about this mode of transportation.

Our own data team at StreetLight suspects the answer is “it depends.” We hypothesize that the interaction between Gig Driving and Congestion depends heavily on what we call “context,” i.e. location, existing transit, urban density, land use, time of day, etc. We also believe that Gig Driving is here to stay and that we can arm policy makers with data to avoid the desire to “undo” what is a mobility megatrend — and instead try to harness and accelerate positive effects on the community and transportation networks, while mitigating the negative ones.

To test our hypothesis about granular variation, we used our access to billions of transportation data points, and a lot of expertise in data science and transportation. We measured the interaction between Gig Driving and congestion road-by-road throughout the Greater Miami region.

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Blog Feature

Events

StreetLight Data CEO to speak at National League of Cities Annual Conference

November 6, 2018

With traffic a top-of-mind issue across the country, city streets are ripe for innovation: Our roadways, curbs and sidewalks have become proving grounds for exciting technologies such as autonomous transit, dockless bike and scooter sharesand, of course, new forms of data collection.

That's a lot of innovation to squeeze into a few city blocks. How can private companies and local governments work together to accommodate it all? Find out at "Making Room for Innovation on City Streets," a session at this week's “City Summit” conference in Los Angeles, hosted by the National League of Cities. 

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Blog Feature

Case Studies

Nantucket Uses StreetLight Data to Estimate Population

October 5, 2018

Seasonal population peaks are difficult to measure - especially in popular destinations like Nantucket Island. But population size is a critical metric for transportation planning, federal funding allocation, and more.

The Wall Street Journal cites a StreetLight Data client, the Nantucket Open Data Platform, who uses StreetLight's innovative mobility analytics to estimate the island's population around the year. This data is helping public agencies and local businesses in Nantucket build better plans for the future.

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Blog Feature

Big Data

Measuring Travel Behavior at Walt Disney World

September 6, 2018

This blog article was written by an Antonia Cheatham, a StreetLight Data summer intern. Antonia lives in the Richmond, Virginia area. She is a rising high school senior at Huguenot High School who is also pursuing an Associates Degree in Social Studies at J. Sargeant Reynolds College via the Early College Academy program. In her free time, Antonia enjoys dancing, reading and Robotics. Her long-term career goal is to become a lawyer.

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Blog Feature

Big Data | Corridor Studies | Traffic

The Waze Effect: 4 Steps for Cities to Fight Back

August 28, 2018

Thanks to navigation apps like Waze and Google Maps, GPS-enabled smartphones are changing the way we drive. It’s much easier to avoid a traffic jam or to find the closest gas station than it used to be. However, as many urban and transportation planners know, these apps have negative consequences.

When navigation apps route drivers through local roads in residential areas, they introduce congestion, air pollution, noise, and safety issues to streets that are designed for much low traffic volumes. The so-called “Waze Effect” is wreaking havoc on residential neighborhoods in all types of cities, especially during rush hour. It’s not only major metropolises such as Los Angeles, CA and Boston, MA that are impacted, but also smaller communities such as Fremont, CA and Takoma Park, MD.

So, what can transportation planners do about it? One way is to use the very data that smartphone apps create to your advantage. In this article, I’ll share four steps for cities to fight the Waze Effect with Big Data.

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