The Sidewalk Clutter Index: Where 311 Scooter Complaints Are Surging
A VerifyAI open-data study · Published June 22, 2026
Shared scooters and e-bikes solved a real problem — the last mile — and created a new one on the sidewalk. When a rider leaves a scooter tipped across a curb ramp or blocking a bus stop, the city hears about it through 311. Those complaints are public record, and they are the clearest public signal of how big the mis-parking problem has actually gotten.
So we pulled them. This study analyzes 145,524 real 311 complaints about improperly parked or abandoned shared scooters and bikes across the five major U.S. cities whose open-data portals let us query the records directly. The headline: 2025 was the worst year on record in every city still growing its program, and across the five cities micromobility-parking complaints are up 81% since 2022.
We build an AI photo-verification API that operators use to confirm a scooter is parked legally at the end of a ride. That puts us close to the parking problem — but this study isn't about our product. Every number below comes from public city open data, with the queries published so you can check them. Think of it as a map of the problem, not a sales sheet.
The headline numbers
- 145,524 total complaints analyzed across five cities' open-data portals.
- 30,952 complaints in 2025 alone across the five cities — a record, and +81% versus 2022.
- Chicago had the steepest rise: e-scooter parking complaints jumped +824% from 2022 (821) to 2025 (7,588).
- San Francisco (11,132) and Seattle (10,152) logged the highest raw 2025 volumes.
- Austin is the counter-example: complaints fell ~70% from 2022 to 2025 as the city's permitted fleet shrank — a reminder that this is a fleet-size and policy story, not an inevitability.
- In New York City, 96% of all 311 "E-Scooter" complaints carry the descriptor "Improperly Parked or Abandoned" — i.e., the problem is overwhelmingly a parking problem, not a riding or vandalism one.
City-by-city: complaints by year
Each city files micromobility complaints a little differently — Chicago and NYC have a dedicated scooter category, Seattle bundles scooters with bike-share, and San Francisco logs them as free-text within broader sidewalk and parking-enforcement requests (see Methodology for exact filters). Counts are therefore most meaningful within a city over time, and as a direction-of-travel signal across cities — not as a precise apples-to-apples leaderboard.
Each panel: annual count of micromobility-parking 311 complaints for that city. Bars marked * are partial-year (data pulled mid-2026) and are excluded from year-over-year comparisons.
The pattern is consistent in the three cities with growing fleets. Chicago roughly doubled its complaint count two years running (+141% in 2024, +110% in 2025). Seattle climbed every single year since its 2020 launch, with a +59% jump in 2025. San Francisco is noisier year to year but set a clear record in 2025 at more than 11,000 complaints. Even NYC's small Bronx-centered pilot quadrupled in 2024.
Austin runs the other way. After peaking above 10,000 complaints in 2023, Austin's micromobility complaints fell to about 1,600 in 2025 — tracking a sharp reduction in permitted vehicles and operators. It's the clearest evidence in the dataset that mis-parking volume follows fleet size and enforcement, and can be brought down.
Ranked: complaint growth, 2022 → 2025
Indexing each city to a common full-year window — 2022 to 2025, the span all five cities cover with complete data — shows how differently these programs have trended.
Across all five cities combined, complaints rose from 17,144 in 2022 to 30,952 in 2025 — an 81% increase. Strip out Austin's decline and the four growing-fleet cities rose +85% in a single year from 2024 to 2025 (15,877 → 29,371).
| City | 2022 | 2025 | Change | 2025 share marked "parking" | |---|---|---|---|---| | Chicago | 821 | 7,588 | +824% | Dedicated "E-Scooter Parking Complaint" type | | New York City | 235 | 499 | +112% | 96% "Improperly Parked or Abandoned" | | Seattle | 5,122 | 10,152 | +98% | "Scooter or Bike Share Issue" category | | San Francisco | 5,767 | 11,132 | +93% | Sidewalk/parking-enforcement requests | | Austin | 5,199 | 1,581 | −70% | "Shared Micromobility" / "Dockless Mobility" | | All five | 17,144 | 30,952 | +81% | — |
What the complaints are actually about
Where a city tags a reason, the answer is unambiguous: this is a parking problem. New York City's 311 system breaks "E-Scooter" complaints into descriptors, and the split is stark:
| NYC "E-Scooter" complaint descriptor | Complaints | Share | |---|---|---| | Improperly Parked or Abandoned | 1,997 | 96% | | Parking Corral Not Maintained | 54 | 3% | | Damaged or Vandalized | 31 | 1% |
Chicago tells the same story by construction: its category is literally named "E-Scooter Parking Complaint." These aren't complaints about reckless riding or broken vehicles — they're about a scooter left where it shouldn't be, blocking a sidewalk, a curb ramp, or a doorway. That is precisely the failure that ends-of-ride parking rules are written to prevent.
Why this is a permit problem, not just a nuisance
For an operator, sidewalk clutter isn't a PR issue — it's an existential one. The complaints in this dataset are the input to enforcement:
- Rider-facing fines. Pensacola, FL adopted penalties of up to $150 for riders who park scooters improperly — cities increasingly treat sidewalk clutter as an enforceable violation.
- Relocation SLAs. Operators routinely sign permit terms requiring a misparked or complaint vehicle to be relocated within roughly an hour. Miss the window repeatedly and penalties or fleet-cap reductions follow.
- Measured compliance. Many cities ingest operator data through the Mobility Data Specification (MDS) and audit parking compliance directly, rather than taking an operator's word for it.
A 311 complaint is the first domino. Enough of them turn into fines, then into a fleet cap, then into a permit that doesn't get renewed. The cities in this study are generating those complaints at record rates.
What actually reduces the complaints
GPS alone can't fix this. Consumer GPS in a dense downtown drifts several meters — the difference between "in the corral" and "blocking the crosswalk" — and a latitude/longitude pair can't tell you whether a scooter is upright, inside the rack, and clear of the pedestrian path.
The mitigation operators have converged on is end-of-ride photo verification: the rider can't close the trip until they submit a photo, and that photo is checked against the city's parking rules before the ride ends. The category leader in this space, Captur, reports an 80%-plus reduction in mis-parking in its published case studies — the clearest public evidence that verifying the parking photo, rather than just storing it, moves the number.
Plenty of apps already capture an end-of-ride photo. The mechanism that reduces complaints is verifying it — confirming, automatically and in real time, that the vehicle is actually parked correctly against this city's specific rules, and asking for a better photo before the ride can end if it isn't. A photo filed away for later review doesn't stop the 311 call; a verdict at the gate does.
This is the category VerifyAI works in: a photo-verification API that returns a pass/fail parking verdict in under 200ms, on-device and offline-capable, with each city's rules encoded as policy-as-code. We've written separately about how operators cut parking fines with end-of-ride verification and compared the available parking-compliance tools. But the takeaway from the data above stands on its own: the complaints are real, they're rising, and they're about parking.
VerifyAI is GDPR-aligned, with a SOC 2 audit in progress — not yet SOC 2 certified. The 80%-plus mis-parking-reduction figure cited above is Captur's published case-study claim, not a VerifyAI result. We have not measured a clutter-reduction rate of our own and don't claim one here.
Methodology
What we counted. Annual counts of 311 / service-request records relating to shared micromobility (e-scooters and, where the city bundles them, shared bikes) — focused on improper-parking and abandonment complaints. We report counts by calendar year of the complaint's creation date.
How we pulled it. Each figure was queried on June 22, 2026 directly from the city's official open-data portal using its public Socrata SoQL API ($where, $group, date_extract_y, count(*)). The exact dataset, filter, and series window for each city:
| City | Open-data portal | Dataset ID | Filter used | Series window |
|---|---|---|---|---|
| Chicago | data.cityofchicago.org | v6vf-nfxy (311 Service Requests) | sr_type = 'E-Scooter Parking Complaint' | 2022–2026 |
| Seattle | data.seattle.gov | 5ngg-rpne (Customer Service Requests) | webintakeservicerequests = 'Scooter or Bike Share Issue' | 2020–2026 |
| San Francisco | data.sfgov.org | vw6y-z8j6 (311 Cases) | service_details contains scooter (free-text) | 2018–2026 (shared-scooter era) |
| New York City | data.cityofnewyork.us | erm2-nwe9 (311 Service Requests) | complaint_type = 'E-Scooter' | 2021–2026 |
| Austin | data.austintexas.gov | xwdj-i9he (311 Unified Data) | sr_type_desc contains Micromobility or Dockless (four department-renamed variants combined) | 2018–2026 |
Cross-city comparisons use the 2022–2025 window because all five cities have complete data for those years. Year-over-year change figures exclude any partial year. 2026 is a partial year (data pulled in late June 2026) and is shown in the per-city panels for context only, marked with an asterisk and a muted bar.
Reproducing it. The counts are deterministic — anyone can re-run them. For example, Chicago's by-year series is:
https://data.cityofchicago.org/resource/v6vf-nfxy.json
?$select=date_extract_y(created_date) as yr, count(*) as n
&$where=sr_type='E-Scooter Parking Complaint'
&$group=yr&$order=yrFiling conventions differ by city. Chicago and NYC have a dedicated scooter category; Seattle bundles scooters with shared bikes in one category (so its counts include some bike-share complaints); San Francisco has no scooter category, so we matched the word "scooter" in the free-text service_details field, which can include a small number of non-shared-scooter mentions. Treat counts as most reliable within a city over time, and directional across cities.
Reporting is not incidence. A 311 count measures complaints filed, which is shaped by how easy each city makes reporting and by public awareness — not a perfect census of every mis-parked vehicle. Rising 311 apps and outreach can lift counts on their own.
San Francisco's pre-2018 rows are excluded because "scooter" in that era largely referred to mobility scooters and motor scooters, not the shared e-scooters introduced in 2018.
Cities we could not include
We aimed for broader coverage but several portals don't expose a queryable micromobility complaint category:
- Los Angeles — MyLA311 (
data.lacity.org) is queryable, but its request-type taxonomy has no scooter or micromobility category (scooters are managed through LADOT's dockless permit program, not 311). No defensible count was possible. - Denver and Minneapolis — both publish open data through ArcGIS Hub rather than a Socrata SoQL endpoint, so a like-for-like programmatic complaint query wasn't available for this pull. They're candidates for a future expansion of the index.
We'd rather report five cities with clean, reproducible queries than pad the list with numbers we can't stand behind.
Sources
- Chicago 311 Service Requests — City of Chicago Open Data (data.cityofchicago.org/resource/v6vf-nfxy)
- Seattle Customer Service Requests — City of Seattle Open Data (data.seattle.gov/resource/5ngg-rpne)
- San Francisco 311 Cases — DataSF (data.sfgov.org/resource/vw6y-z8j6)
- NYC 311 Service Requests — NYC Open Data (data.cityofnewyork.us/resource/erm2-nwe9)
- Austin 311 Unified Data — City of Austin Open Data (data.austintexas.gov/resource/xwdj-i9he)
- Captur mis-parking-reduction case-study figures — captur.ai
- Mobility Data Specification (MDS) — Open Mobility Foundation
See the problem from the operator's side
If you run a micromobility program, the complaints in this study are the metric a city watches when it decides whether to renew your permit. The lever operators pull is verifying the end-of-ride parking photo before the ride can close.
Try VerifyAI's parking verification free — $5 in sandbox credit, no card. Encode your city's parking rules and watch pass/fail verdicts come back in real time. Or book a demo to see it wired into an operator workflow.
The Sidewalk Clutter Index is a public-data study by VerifyAI, a Switch Labs product. Data pulled June 22, 2026. Press and researchers: the full per-city dataset and queries are reproducible from the methodology above — reach out for the compiled dataset.