Using GTFS-RT Feeds for Real-Time Demand Monitoring: A Practitioner’s Walkthrough
GTFS-RT vehicle position and trip update feeds contain more demand signal than most agencies realize — here’s how to extract it.
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Transit analytics and planning intelligence
Technical walkthroughs on GTFS/GTFS-RT data extraction, H3 demand modeling, equity analysis, and procurement guidance — written by transit planners and data scientists for the people doing this work in agencies.
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Why We Use Uber’s H3 Grid for Transit Demand Analysis (and Why TAZ Polygons Fall Short)
Traditional Traffic Analysis Zones encode political boundaries, not travel behavior. H3 hexagonal grids reveal demand patterns that TAZ analysis obscures.
Data-Driven Equity Analysis for Title VI Network Redesigns
When a transit agency redesigns its network, Title VI compliance requires demonstrating equitable service distribution. Here’s how demand surface data supports that analysis.
First/Last Mile Gap Analysis Using GBFS Bike-Share Data
GBFS trip-origination data can pinpoint exactly where fixed-route transit leaves riders stranded at the first and last mile — if you know how to aggregate and fuse it with stop-level boardings.
Three Years After: What Ridership Data Tells Us About Post-Pandemic Travel Behavior
Transit ridership has not simply returned to 2019 levels — it has restructured. The temporal and spatial patterns of post-2022 demand look fundamentally different from pre-pandemic baselines, with significant implications for headway optimization and route coverage.
Making the Case for Data-Driven LRTP Corridor Prioritization at MPOs
Metropolitan Planning Organizations face the challenge of prioritizing LRTP projects with limited data. A demand surface model offers a more defensible analytical foundation.
A Planner’s Primer on Multimodal Demand Fusion
What does it mean in practice to combine GTFS ridership, GBFS bike-share trips, and intersection counts into a single demand model? A non-technical walkthrough of normalization, spatial alignment, and the decisions that shape the output.
Unlocking Mobility Data from Intersection Camera APIs
Many cities have invested in smart intersection infrastructure. Here’s how to normalize and integrate camera API outputs with transit demand data.
Designing Bike-Share Networks That Actually Support Transit — Not Compete With It
Demand surface analysis reveals where bike-share complements fixed-route transit and where placement decisions cannibalize ridership.
A Government Planner’s Guide to Procuring Mobility Analytics Software
What to ask vendors, how to structure an RFP, what data rights provisions matter, and how to evaluate methodology transparency before signing.
The Four-Phase Demand Surface Methodology for Transit Network Redesigns
A step-by-step walkthrough of how Mobvynt supports transit agencies through the full redesign analysis process, from data ingestion to GTFS scenario export.
GTFS, GBFS, and the Case for Open Mobility Data Standards
Open data standards are the foundation that makes multimodal demand analysis possible. Here’s why agencies should require GTFS and GBFS compliance in all mobility contracts.
How Signal Timing Data Supports Transit Priority Decisions
Transit Signal Priority works best when signal timing data is fused with real ridership demand. Here’s how agencies are using intersection data to optimize bus running times.
Building a Mobility Equity Analysis Framework Your Agency Can Actually Use
Equity in transit planning requires more than a Title VI checklist. A demand surface approach lets analysts see where service gaps fall along demographic and socioeconomic lines.