How do robot delivery corridors compare?
No two robot delivery corridors are alike. This matrix puts them side by side on the operability signals that decide whether a sidewalk fleet can run: connectivity for teleoperation, sidewalk width for passage, grade for climbing power, operating days for weather exposure, and building and restaurant density for demand. The spread is real: corridor grades range from nearly flat to steep, and open-data coverage itself varies, so a lighter row can reflect a data gap rather than an easy corridor. Every figure is measured from an open dataset and rolled up here, so the matrix carries a Derived basis, not the registry verified chip.
Every figure is measured from an open dataset and rolled up here. How we verify.
Operability matrix, best-measured first
| Corridor | Metrics | Mbps | Sidewalk >3m | Max grade | Op days/yr | Restaurants | Basis |
|---|---|---|---|---|---|---|---|
| LA West Side | 21 | 286 | 94% | 1.8% | 330 | 964 | Derived |
| SF Core | 21 | 184.8 | not measured | 5.4% | 300 | 699 | Derived |
| Chicago | 20 | 355 | not measured | 0.8% | 260 | 925 | Derived |
| Austin | 18 | 348 | not measured | 2.2% | 280 | 169 | Derived |
| Phoenix | 18 | 322 | not measured | 1% | 340 | 17 | Derived |
| Miami | 17 | 258 | not measured | 1.2% | 230 | 287 | Derived |
| Dallas-Fort Worth | 16 | 279 | not measured | 1.5% | 305 | 154 | Derived |
| Atlanta | 14 | 363 | not measured | 3.5% | 260 | 188 | Derived |
| Alexandria, VA | 12 | 266 | not measured | 2.5% | 280 | 76 | Derived |
Source: rolled up from the measured Atlas datasets (Ookla connectivity, OSM sidewalks and buildings, USGS grade, NOAA weather, city open-data portals). A blank cell is an open-data gap for that corridor, not a zero. Because this is a roll-up of measured datasets, it carries the Derived basis.
How to read the matrix
Each row is a corridor and each column an operability signal. Metrics is how many measured signals we hold for that corridor, so a fuller row is one we can reason about with more confidence. Grade and connectivity are the two that most directly gate a small sidewalk fleet: a steep grade taxes drive motors, and low connectivity limits teleoperation. Blank cells are genuine open-data gaps, which is itself a finding about which corridors are hardest to characterize.
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Every figure is measured from an open dataset (Ookla, OpenStreetMap, USGS, NOAA, and municipal open-data portals) and rolled up into this matrix, so it carries the Derived basis. A blank cell is an open-data gap, not a zero. These are measured-from-open-data facts, not reviewed DEPLOY registry records, so none carries the registry verified chip. How we verify
Related answers
Which robot corridors have the most data?
The open-data coverage scorecard per corridor.
Read article →
Which robot delivery corridors are densest?
Restaurant, cafe, and shop density per corridor.
Read article →
How steep are robot delivery corridors?
Measured grade across the same corridors.
Read article →
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