ITSFeed

The data, standards, and technology behind mobility.

ITS
Intelligent transportation systems
Feed
The live data layer

Author

Nick Sawinyh

Contributor

Nick Sawinyh writes for ITS Feed on the data and technology layer of transportation: feeds, standards, interoperability, and the systems agencies run.

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12articles

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Published work

  1. AI in TransportationExplainer

    AI in transit: where it's real and where it's a demo

    Transit agencies are running machine learning in production today, but not in the places the marketing points to. Here is what the working deployments have in common, and why the ones that stall usually stall on data rather than on models.

  2. Agency ITRoundup

    July 2026 roundup: open-loop fares, the NTD's new rules, and MDS 2.1

    What moved on the transportation data layer from mid-June to mid-July 2026: World Cup open-loop fare launches, new National Transit Database reporting rules, MDS 2.1 in preview, and AI landing in agency software.

  3. Feeds & StandardsExplainer

    What GTFS is, and how a transit feed fits together

    GTFS is the open format that puts transit schedules into your maps app. Here is what a feed contains, how its files join together, and why it became the default for transit data worldwide.

  4. Feeds & StandardsExplainer

    What GTFS-Realtime is, and how a feed works

    GTFS-Realtime is the standard for live transit data: what a feed carries, how Protocol Buffers structure it, and why the quality rests on the systems behind it.

  5. InteroperabilityExplainer

    What intelligent transportation systems actually are

    Intelligent transportation systems is a broad label that hides a precise idea. Here is what ITS covers, the architecture that holds it together, and why it is really a data-exchange problem.

  6. InteroperabilityExplainer

    How buses talk to traffic lights: transit signal priority

    Transit signal priority lets a late bus ask a traffic signal for a few more seconds of green. Here is the request-to-grant message chain, how it differs from emergency preemption, and how NTCIP 1211 lets mixed-vendor buses and controllers interoperate.

  7. Data PlatformsExplainer

    Mobility as a service: what actually stuck

    Mobility as a service promised one app to plan, book, and pay for every trip on a subscription. The flagship consumer bundle went bankrupt. Here is what the idea got right, what it got wrong, and which pieces survived.

  8. Quality & ComplianceExplainer

    Bus bunching and headway: why three arrive at once

    Three buses arriving nose to tail is not bad luck. It is a feedback loop in frequent service, where a late bus falls further behind and the one behind it catches up. Here is the mechanism, why agencies measure headway instead of schedule, and what they do about it.

  9. Quality & ComplianceExplainer

    Ghost buses: why the app shows a bus that never comes

    A ghost bus is a prediction with no vehicle behind it. Here is how a transit app generates one, the four ways it happens, and how Chicago drove its rate down.

  10. Feeds & StandardsExplainer

    How real-time arrival predictions actually work

    The countdown on the sign is a prediction, not a readout of a bus you can see. Here is the data chain behind it, from the vehicle's GPS to the feed the sign reads, and the three ways agencies turn location into a time.

  11. Quality & ComplianceExplainer

    What the National Transit Database actually holds

    The NTD is the federal record of US public transit: who rides, what it costs, and who has to report. Here is what it holds, who files it, and how to pull the numbers yourself.

  12. Agency ITExplainer

    Fare payment modernization: account-based ticketing, fare capping, open-loop

    Agencies are moving fare logic off the card and into a back office. Here is what account-based ticketing, fare capping, and open-loop payment each mean, and which agencies have made the switch.