ODDYSSEYExplore markets

ODDYSSEY / PUBLIC-DATA FRAMEWORK

Methodology

A clear record of where the evidence comes from, what we extract, which metros enter the comparison, and how the screening score is built.

Public-data market screening and hypothetical fleet operations. Not a safety assessment or deployment approval.

San Francisco Bay Area skyline used as visual context
REFERENCE ENVIRONMENTEvidence starts with place.Illustrative image · not a scoring input
01

SOURCE REGISTER

Start with provenance

The verified.v2 public-data release links every available measurement to its saved evidence record. It records the source, period, geography, transformation, assumptions, retrieval time, and raw-file hash so a number can be traced back to its input.

REFERENCE RELEASEverified.v2
DATA VERSION2024-acs5__2024-tiger__NOAA-1991-2020__TIGER-edges-2024__AFDC-current__commute-B08013-B08303-r2
COHORT20 candidates + 15 references
RANKING IDe1e3650e5a6a13ca8a48
RELEASE SHA-2568533f5fec66352797963cd41a23430642bac6ad0ff0a50569449d013a9445df6
01

U.S. Census ACS 5-Year Summary File

2024 five-year estimates
Dataset / variables
B01003 · B08201 · B08301 · B08013 · B08303
Geography
CBSA estimates; county population denominators

Population, households by vehicle availability, commute mode, and commute duration. The corrected commute measure uses aggregate travel minutes divided by workers who did not work from home; B08301 remains the transit-share universe. Both commute inputs and their margins of error are recorded for all 35 candidate and reference CBSAs. Input MOEs are not confidence intervals for the derived ratio or score.

Census ACS data
02

U.S. Census TIGER/Line geography and roads

2024 CBSA, county, and county-edge geography
Dataset / variables
TIGER/Line CBSA · County · Edges
Geography
Official CBSA polygons and member counties

CBSA and county polygons define the comparison area. Whole member-county land area uses Census ALAND; counties are assigned by representative point. TIGER network edges supply public road centerline length, road classes, and junction topology. Walkways, trails, private resource roads, and parking-lot roads are excluded. City-proper boundaries are not used for ranking.

2024 Census CBSA geography
03

NOAA NCEI U.S. Climate Normals

1991–2020 climate normals
Dataset / variables
Annual precipitation · snowfall · days with Tmax ≥ 90°F
Geography
NOAA station points mapped to CBSA representative points

Precipitation and snowfall use the nearest reporting station within 100 km. Hot-day counts average up to three qualifying stations in that radius. The pipeline requests standard units and quality attributes, records station IDs and distances, and leaves unavailable snowfall missing.

NOAA climate normals
04

Alternative Fuels Data Center / NLR

Current public station snapshot in the release
Dataset / variables
AFDC alternative-fuel stations · public DC fast charging
Geography
Station points joined to 2024 CBSA and county polygons

Filter electric-fuel (ELEC), public-access stations with operational status E; count reported DC fast ports, deduplicate station IDs, and join coordinates to frozen geography. Missing DC counts invalidate the feature. Public charging does not measure private depot access or secured fleet capacity.

AFDC data downloads
05

Waymo public market evidence

Status evidence dated 2026-09-26
Dataset / variables
waymo_markets · public rides and market-status page
Geography
Publicly named reference metros mapped to CBSAs

Dated public operator evidence defines the reference-market cohort and its recorded category. The verified.v2 release contains 15 enabled commercial references. This public snapshot is not evidence of private fleet availability, internal strategy, or service coverage beyond what the source states.

Waymo public ride markets
06

PublicaMundi MappingAPI state boundaries

Bundled illustrative U.S. state GeoJSON
Dataset / variables
us-states.json
Geography
State shapes for map display only

This bundled map layer provides visual context. It is not the scoring geography and is not used for CBSA or county joins. Upstream attribution is preserved.

PublicaMundi source file
SELECTED METRO RECORD

Inspect a metro record

Choose a candidate or public reference market to inspect the release’s stored measurements and complete source records. This page does not recalculate rankings.

Exact feature values, missing reasons, and full provenance records appear here after you choose a metro.

02

EXTRACTION REGISTRY

Variables extracted from those sources

The active ranking.v2 model has 15 required variables, grouped into three pillars. We show the source and extraction rule beside the exact registry key, transformation, and within-pillar weight.

A

ODD familiarity

40% of score

Public climate, commute, and road-network proxies. Familiarity compares a candidate with a whole reference environment.

ODD familiarity variable registry
VariableUnitExtractionSourceWeightTransform
Annual precipitationannual_precipitation_mmmm/yearNearest qualifying NOAA 1991–2020 station within 100 km; convert inches to millimeters.NOAA NCEI10%log1p
Annual snowfallannual_snowfall_mmmm/yearNearest NOAA station reporting snowfall within 100 km; convert inches to millimeters. Missing is not zero.NOAA NCEI10%log1p
Days at or above 90°Fhot_days_32cdays/yearMean annual days with maximum temperature ≥ 90°F (32.22°C), averaged across up to three qualifying stations within 100 km.NOAA NCEI10%linear
Mean commutemean_commute_minutesminutesB08013_E001 aggregate travel minutes ÷ B08303_E001 workers not working from home.2024 ACS20%linear
Road densityroad_density_km_per_km2km/km²Included TIGER road centerline kilometers ÷ CBSA land area in km².2024 TIGER/Line10%log1p
Intersection densityintersection_density_per_km2intersections/km²Consolidated degree-three-or-higher road junctions ÷ CBSA land area in km². Nearby divided-road junctions are clustered within 20 m.2024 TIGER/Line10%log1p
Freeway sharefreeway_sharefractionLength of Census road classes S1100 and S1630 ÷ included road length.2024 TIGER/Line10%linear
Arterial sharearterial_sharefractionLength of Census road class S1200 ÷ included road length.2024 TIGER/Line10%linear
Local-road sharelocal_road_sharefractionLength of classes S1400, S1640, and S1730 ÷ included road length. A Census road-class grouping, not an FHWA functional class.2024 TIGER/Line10%linear
B

Public infrastructure

20% of score

Public charging quantity and coarse county coverage. Neither measure establishes a private depot or technical readiness.

Public infrastructure variable registry
VariableUnitExtractionSourceWeightTransform
Public DC ports per 100,000 peoplepublic_dc_ports_per_100kports/100,000 peopleDeduplicated operational public DC fast ports ÷ CBSA population × 100,000.AFDC / NLR + ACS70%log1p
Population in counties with public DCpopulation_share_in_counties_with_dcfraction of CBSA populationPopulation in member counties with at least one operational public DC port ÷ CBSA population.AFDC / NLR + ACS30%linear
C

Market opportunity

40% of score

Scale and transportation context. These variables are not observed ride-hailing demand.

Market opportunity variable registry
VariableUnitExtractionSourceWeightTransform
Resident populationpopulationpersons2024 ACS B01003_E001 published CBSA estimate.2024 ACS30%log1p
Population densitypopulation_density_per_km2persons/km²Resident population ÷ CBSA land area in km²; water area excluded.ACS + 2024 TIGER/Line25%log1p
Zero-vehicle household sharezero_vehicle_household_sharefraction of households2024 ACS B08201_E002 households with no vehicle ÷ B08201_E001 total households.2024 ACS30%linear
Transit commute sharetransit_commute_sharefraction of workers 16+2024 ACS B08301_E010 public-transit commuters ÷ B08301_E001 workers in the commute-mode universe.2024 ACS15%linear
03

COMPARISON COHORT

Cities being tested

Each named market resolves to an official Census CBSA, keeping the whole regional geography consistent across Census, charging, and road inputs.

Why this set?

The 20 candidate metros are the project’s configured target expansion cohort. The repository does not record a city-by-city inclusion rationale or a quantitative nationwide selection cutoff, so this set should not be read as a representative U.S. sample or as the highest-scoring metros nationwide. CBSA-level comparison was selected because metro geographies capture regional travel and align with the source data better than city-proper boundaries.

20 MARKETS

Candidate expansion cohort

Configured candidates evaluated by the screening model.

  1. 01Jacksonville, Florida
  2. 02Columbus, Ohio
  3. 03Indianapolis, Indiana
  4. 04Milwaukee, Wisconsin
  5. 05Memphis, Tennessee
  6. 06Louisville, Kentucky
  7. 07Oklahoma City, Oklahoma
  8. 08El Paso, Texas
  9. 09Albuquerque, New Mexico
  10. 10Kansas City, Missouri
  11. 11Cincinnati, Ohio
  12. 12Cleveland, Ohio
  13. 13Raleigh, North Carolina
  14. 14Virginia Beach, Virginia
  15. 15Richmond, Virginia
  16. 16Salt Lake City, Utah
  17. 17Birmingham, Alabama
  18. 18Tulsa, Oklahoma
  19. 19Providence, Rhode Island
  20. 20Hartford, Connecticut
15 MARKETS · EVIDENCE AS OF 2026-09-26

Waymo public reference cohort

Enabled commercial reference metros used for normalization and familiarity comparisons.

  1. 01Phoenix, Arizona
  2. 02San Francisco Bay Area, California
  3. 03Los Angeles, California
  4. 04Austin, Texas
  5. 05Atlanta, Georgia
  6. 06Dallas, Texas
  7. 07Denver, Colorado
  8. 08Houston, Texas
  9. 09Miami, Florida
  10. 10Nashville, Tennessee
  11. 11Orlando, Florida
  12. 12San Antonio, Texas
  13. 13San Diego, California
  14. 14Tampa, Florida
  15. 15Las Vegas, Nevada

The 15 reference metros belong to the normalization cohort; they are not candidates in the expansion ranking. Reference status reflects dated public evidence and does not establish service boundaries or fleet availability.

04

SCORING METHOD

How the comparison is built

The engine is deterministic and release-based. It uses only the configured public measurements and explicit model assumptions.

01 / FAMILIARITY40%Climate, commute, and road context
02 / READINESS20%Public charging quantity and county coverage
03 / OPPORTUNITY40%Population and transportation context
  1. 01

    Freeze a release and comparison cohort

    Each result is bound to one immutable data release and one model version. The verified.v2 normalization cohort includes all 20 configured candidates and 15 enabled, complete reference metros. No city outside that set contributes to the bounds.

  2. 02

    Transform and normalize each feature

    Apply the registry transform first: linear values stay unchanged; log1p requires a finite, nonnegative value. Normalize against the release’s frozen minimum and maximum, then clip to [0, 1]. A constant feature is removed globally for that release. Bounds never refit when filters, reference choices, or weights change.

  3. 03

    Score the three pillars

    Familiarity measures weighted Euclidean distance across the nine normalized ODD features to each eligible complete reference vector; the nearest whole reference is selected, with similarity = 100 × (1 − distance). Readiness and Opportunity are weighted combinations of their normalized features.

  4. 04

    Combine and rank

    Combine Familiarity at 40%, Readiness at 20%, and Opportunity at 40%. Sort by full-precision Expansion Score, then canonical city ID. Scores are relative indices for their release, not probabilities, demand forecasts, or comparable values across releases.

  5. 05

    Keep missingness and legal context explicit

    All 15 required ranking measurements must be present for a candidate to be ranked. No imputation or city-specific weight redistribution occurs. Optional road fields do not affect rankability. Legal evidence stays outside the numeric score.