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Success stories across North America

With more than 6,000 projects every month, StreetLight’s analytics have informed transportation analyses in all lower 48 States, Canada and Mexico. Below are some of the entities using StreetLight, followed by numerous case studies we invite you to peruse.

STATES

State Clients - Minnesota Department of Transportation, Ohio Department of Transportation, Main Department of Transportation, Massachusetts Department of Transportation, Transport Canada, Florida Department of Transportation, Virginia Department of Transportation, Iowa Department of Transportation

CITIES & MPOs

City and MPO Clients - LA Dot, Incog, Ottawa, Greater Madison MPO, New York City DOT, Atlanta GA, Toronto, Metroplan Orlando

CONSULTING FIRMS

Consulting Firm Clients - Steer, AECOM, CDM Smith, Kimley Horn, Fehr Peers, Stantec, HDR, Parsons

ENTERPRISE

Enterprise Clients - Ford Mobility, Siemens, BCG, Alaska Airlines, Uber, Spin, Bloomberg, Macquarie
Logos

Read about our customers' successes

Equity

Opportunities for Equitable Mode Shift

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Emissions

Sharing Regional Transportation Emissions Data

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Know Where to Place EV Charging Station Locations

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Multimodal Planning in the City of Toronto

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Aerial,View,Of,People,And,Bicycle,Are,Going,Across,Crosswalk

Enhancing Bike and Pedestrian Safety in Pittsburgh

To enhance bike and pedestrian safety, the City of Pittsburgh used StreetLight Data’s Origin-Destination (O-D) Metrics to capture bike and pedestrian trip information. See why high-travel corridors didn’t correlate with crash severity.

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Dwell Time Analysis for National Parks

The amount of visitors in national parks has grown steadily over recent decades, leading to overcrowding. StreetLight’s dwell-time analysis helped the National Park Service better understand visitor-use management.

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Gauging Potential Demand for Intercity Passenger Rail Transport

When a rail operator needed travel patterns between five major metropolitan areas in the Northeast to identify travel demand, StreetLight’s customized solution linked consecutive trip stops into a longer tour, using adjustable temporal thresholds.

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Florida Trucks Case Study Cover Image

Quantifying Long Haul Trucks on Florida Highways

StreetLight identified what percentage of truck traffic was short-haul (entering or exiting at a ramp) vs long-haul (passing straight through the corridor).

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Windsor Ont Transit

Revamping a Legacy Transit Plan in Ontario

Over 20 years of budget constraints left Windsor, Ontario with a legacy transit system in need of overhaul. Big Data helped planners establish project scope, prioritize, and determine budget needs.

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Golden Gate Park Visitor Patterns

Golden Gate Park needed to count visitors through unsanctioned entrances. With StreetLight’s help, they got counts, trip origins, demographics, and more.

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CA Park System

Pinpointing Visitor Volume at California Park System

To balance public access and its environmental impact, the Nature Reserve of Orange County turned to StreetLight for detailed park visitor data.

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Ft Lauderdale Case Study

Cost-Effective Congestion Analysis for Fort Lauderdale

Saving money over pricey bluetooth or licence plate analysis, Kittelson identified the surprising source of congestion on Ft. Lauderdale’s main corridor.

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Sarasota case Study

Active Transportation Plan for Sarasota

See Sarasota’s data-backed active transportation plan that guided decisions and funding for transit, bicycle, and pedestrian facilities.

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AADT/INCOG

Tulsa MPO Fills Traffic Count Gaps

When jurisdictions in an Oklahoma MPO’s regions stopped collecting counts, StreetLight provided complete and reliable AADT metrics for the entire area.

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boston globe ride hailing case study

Delivering Boston’s Ride-Hailing Metrics

Learn how StreetLight’s analysis confirmed that ride-hailing vehicles contribute substantially to congestion, Download now to learn more about identifying ride-hailing and delivery travel.

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uber air landing node concept

Choosing Locations for Uber Air

Download our case study to learn what metrics Uber Air used to optimize site locations, how many trips per day Uber Air predicts for demand, and how many terminals it needs to meet that demand

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Napa Valley Vineyard

Fast Congestion Analysis in Napa

How Napa pinpointed the cause of congestion, saved time and money, and improved bus lines for commuters.

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cloverleaf highway intersection

Quantifying Cut Through Traffic Measures in a California City

See how Big Data was used to measure and communicate congestion before and after cut through restrictions.

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Football helmet

Football Hall of Fame Projects Tourism Explosion

The Pro Football Hall of Fame projected that annual visitors would jump from 300,000 to three million. To plan transportation for this tourism boost, planners turned to Big Data StreetLight for facts about where visitors came from, traffic hot spots, and parking options.

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Bicycles on a beach

Virginia Bike Tourism: Measuring Economic Impact

Planners knew that tourists visited the Virginia Capital Trail, but they didn’t have metrics for measuring bicycle tourism’s economic impact. They turned to Big Data for detailed information about bike and pedestrian trips.

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long haul truck driving on highway

Detailed Truck Data for Virginia’s Port

To support transportation project prioritization, ongoing studies, and federal funding applications, Port of Virginia planners needed to know which routes were commonly used by port trucking. Learn how Big Data helped solve this transportation problem.

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Cars parked on street in Lafayette, California

Busting Congestion with Big Data in Lafayette, CA

Helping the city prioritize policy and infrastructure to reduce congestion in downtown Lafayette.

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overhead view of Northern Virginia

Transportation Demand Management in Virginia

Planners analyzed hundreds of congested road segments to diagnose areas where certain techniques may have the biggest impact and to guide planning.

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Transportation Demand Management for Snowbowl Traffic

Flagstaff’s planners needed transportation demand management data for increasing Snowbowl traffic. See how Big Data helped.

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