MDS Policy API gives cities machine-readable control over where, when, and how shared micromobility vehicles operate

Headline Finding

The Open Mobility Foundation’s Mobility Data Specification (MDS) Policy API — now at version 2.x — gives city agencies a standardised, machine-readable toolkit to govern shared scooter and bicycle fleets in real time. Rather than relying on paper permits or manual inspections, cities can push binding rules directly to operators as structured data: where vehicles may ride, where they may park, how fast they may travel, how many may be deployed by a given provider, and how those vehicles must be distributed across equity zones. This is a concrete governance instrument — a data-sharing mandate that converts spatial and operational policy into enforceable code — and its breadth illustrates how far the instrument layer of urban mobility governance has already matured for micromobility, setting a benchmark against which AV governance instruments can be measured.

Detail

The MDS Policy Examples wiki page (Open Mobility Foundation, last edited 9 January 2026) documents the full range of policy types that city agencies can publish to operators via the MDS 2.x Policy API. Each policy is a structured JSON document containing a geographic scope (referenced by geography UUID), a set of vehicle states to which the rule applies, and the rule’s parameters.

Spatial control rules include: an Operating Area rule that confines vehicles to a defined riding geography; No Ride Zone rules that prohibit vehicles from entering specified areas regardless of their status (maximum device count set to 0); No Parking Zone rules that bar vehicles from parking in defined areas (illustrated with a named ‘SJSU’ zone); and Parking Zone rules that designate approved parking locations. A Parking Time Limit rule enforces a maximum dwell time — the example sets a maximum of 7,200 seconds (two hours) — after which a vehicle is considered in violation.

A Speed Limit rule sets a maximum operating speed of 13 km/h for electric scooters within specified geographies, described as a ‘Speed Limit Cap of 12 mph (> 13 mph enforced)’.

Fleet distribution rules include a Deployment Equity Zones policy requiring a minimum of 3 vehicles to be available in each of four named equity zone geographies between 05:00 and 09:00 daily. A Provider Caps or Minimums policy illustrates fleet-size governance: the example caps one named provider (Lime, identified by provider UUID) at a maximum of 750 devices city-wide, while requiring all operators to maintain a minimum of 50 devices.

Fiscal instruments encoded in the API include: a Per Trip Fee of 25 cents applied once per trip starting within the municipal boundary; a Right-of-Way Fee charged once per day per vehicle deployed — 25 cents per day for vehicles in a downtown geography, 5 cents per day for vehicles in a historically underserved neighbourhood, with the higher fee taking precedence when both apply; a Metered Parking Fee of 10 c ents per hour applied to vehicles parked in a congested area during weekday rush hours (07:00–08:30); and two variants of Tiered Parking Fees — one charging per hour of dwell time ($2 for the first hour, $4 for the second, $10 per hour thereafter, yielding $56 for a 6.5-hour park) and one charging a flat fee on exit based on total dwell time ($2 for under one hour, $4 for one to two hours, $10 for over two hours).

Finally, two Real-time Emergency policy types demonstrate dynamic, event-triggered governance: a No Travel geofence automatically created following a 911 fire dispatch (‘Policy automatically created following dispatch L1, matching rule High priority Geofencing’), and a 5 mph slow-speed zone automatically created for an aid response dispatch. Both are pushed to operators in near-real time (the example shows a gap of 61 milliseconds between start_date and published_date for the No Travel policy). A lightweight Real-Time Check for Update mechanism allows operators to poll for policy changes at high frequency without downloading the full policy payload each time.

Governance Implication

1. The spatial-allocation lever is moved directly: MDS Policy rules encode operating areas, no-ride zones, no-parking zones, parking time limits, and equity distribution minimums as machine-readable constraints, replacing discretionary permit conditions with enforceable, auditable data — a material advance in curb-management and operational-design-domain governance.
2. The fiscal lever is moved with precision: per-trip fees, right-of-way fees differentiated by geography (25 cents downtown vs. 5 cents in underserved areas), metered parking fees, and tiered dwell-time fees are all expressible in the same API, giving cities a value-capture toolkit that can be tuned zone by zone and updated without renegotiating permits — directly relevant to fiscal-exposure and value-capture concepts.
3. The equity dimension of the distribution policy (minimum 3 vehicles per equity zone, 05:00–09:00) and the reduced right-of-way fee in historically underserved neighbourhoods show that the instrument can encode distributional goals, not just revenue or restriction — a legitimacy lever move that cities deploying AVs will need to replicate.
4. The real-time emergency geofencing capability — policies auto-generated within milliseconds of a 911 dispatch — demonstrates that MDS-style data infrastructure can support dynamic, event-driven spatial governance, a capability that AV regulators have not yet matched and that the governance clock must catch up to as AV fleets scale.
5. For cities and investors watching the AV transition: MDS for micromobility is the most mature example of performance-based permitting via data-sharing mandate currently in production. The gap between this instrument maturity and the absence of equivalent AV policy APIs is a concrete illustration of the pacing problem (chapter 1) — the governance clock for AVs lags the deployment clock, and MDS shows what catching up could look like.

Sources

https://github.com/openmobilityfoundation/mobility-data-specification/wiki/MDS-Policy-Examples https://github.com/openmobilityfoundation/mobility-data-specification https://www.openmobilityfoundation.org/about-mds/