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.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.