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ENTERPRISE
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.
READ CASE STUDY
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.
READ CASE STUDY
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).
READ CASE STUDY
Sharing Regional Transportation Emissions Data
Learn how Streetlight helped the Twin Cities Metropolitan Council measure individual communities’ emissions from passenger and commercial vehicles.
READ CASE STUDY
Identifying Opportunities for Bike-Ped Mode Shift
Trading in traditional travel demand models for StreetLight’s bike and pedestrian data, Jacobs projected mode shift for a bike-ped bridge in Portland.
READ CASE STUDY
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 accurate park visitor data.
READ 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.
READ 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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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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Know Where to Place EV Charging Station Locations
Download our case study to see how planners worked with Siemens and StreetLight Data to analyze the metrics for EV placement.
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Fast and Accurate Congestion Analysis in Napa
How Napa pinpointed accurate cause of congestion, saved time and money, and improved bus lines for commuters.
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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 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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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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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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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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Multimodal Planning in the City of Toronto
Analytics informed planning studies for “Gateway Mobility Hubs” that will provide convenient, affordable, multimodal modes and improve connections to transit options in Toronto’s outskirts.
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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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