⚠️ Work in progress — data and figures are preliminary.

Solvent Streets

Livermore, CA

Pavement & Parking Analysis | Last computed 2026-06-19

City Summary

City Area (acres) 16846.0
City Area (sq mi) 26.32
Total Paved (acres) 2155.8
% Paved 12.8%

roads

Features 15678
Area (acres) 1750.0
Area (sq mi) 2.73

parking

Features 488
Area (acres) 350.4
Area (sq mi) 0.55

sidewalks

Features 1933
Area (acres) 137.6
Area (sq mi) 0.22
Coverage %
0%25%50%75%100%

Interactive Forecast

Tier Min PCI Max PCI $/unit

Methodology

This section describes the data sources, models, and assumptions behind the analysis presented in each dashboard.

Data sources

The exact sources and endpoints used for a given example are listed in that example's Config tab.

Decay model

Each road classification decays independently via

PCI(t) = PCI₀ · exp(−k · t)

where k is an annual decay constant that depends on the road classification. Higher-class roads (motorway, trunk, primary) decay more slowly than lower-class roads (residential, service) because they are built to thicker, more rigorous design standards and typically receive more frequent maintenance. Default values are derived from LTPP data reported in FHWA-RD-01-156, Long-Term Pavement Performance and ship as part of the forecast package; they are continental-US averages and do not account for local climate, traffic, or construction quality. A config may set a per-city decay_rate to tune for local conditions (e.g. freeze/thaw or road salt); that override is applied as the rate for a typical road and scales every road class proportionally, so the per-class ordering (higher classes decay slower) is preserved rather than flattened. Sidewalks decay on a separate, slower track and are not treated as a highway class.

Cost model

Treatment costs are banded by PCI: each band has a representative $/sq m value, and costs between bands are linearly interpolated at the tier midpoints, so the cost-versus-PCI curve is smooth rather than step-shaped. Above the highest anchor (the midpoint of the preventive tier) and below the lowest anchor (the midpoint of the reconstruction tier), the cost is clamped to that anchor's value rather than extrapolated. Default cost tiers are expressed in $/sq m and sourced from FHWA treatment-selection guidance; they are calibration inputs, not measurements, and local bid prices will differ. Roads and sidewalks use independent cost tiers because the treatment economics differ substantially.

Scenario comparisons

PVMT ships with three comparison runs driven by annual funding level, all using the worst-first allocation strategy (budget is spent on the lowest-PCI segments first):

A do-nothing baseline (no spend, uncontrolled decay) is shown alongside the funded runs for comparison.

The forecast library also implements a preventive-first strategy (prioritize highest-PCI segments that are still in the preservation window), but the default UI comparisons do not exercise it. Preventive vs. worst-first allocation is governed by per-strategy efficiency multipliers; those multipliers are illustrative calibration constants chosen to reflect the direction and sign of the effect reported in FHWA-HIF-12-042, Pavement Preservation: Preserving our Investment — that $1 of preventive maintenance is reported to avoid $6–$10 of future reconstruction — not to reproduce that benefit-cost ratio as a single-year spending efficiency.

Area growth

Optional compound annual growth applies to pavement area each year:

Area(y) = Area₀ · (1 + g)^y

where g is configured per city (default zero). This lets an example model a city that is still expanding its street network; it does not model demolition or removal.

Solvency metrics (streets/roads only)

The dashboard's Financials headline and the cross-city leaderboard report three solvency figures. They are computed on the roads/streets cohort only — the aggregate scenarios blend roads, parking, and sidewalks but cost the blend at road tiers, which would mis-price sidewalks, so an absolute dollar claim must be roads-only. They are derived from a worst-first run at the city's configured annual budget.

Three caveats apply to these figures specifically:

Assumptions and limitations

References

Project Configuration

Input Configuration

# Livermore, CA — simple single-city example
#
# Livermore is in Alameda County, so both OpenStreetMap (Overpass) and the
# Alameda County ArcGIS FeatureServer are available as data sources.
# This is a good starting point for new users.

config_id = "livermore-ca"

[forecast]
#@cite MTC 2024 (Pavement Condition of Bay Area Jurisdictions 2024, 3-year moving average)
#@cite     https://mtc.ca.gov/digital-library/5099739-pavement-condition-bay-area-jurisdictions-2024 (accessed 2026-06-14)
initial_pci = 75
#@cite City of Livermore 2021-23 CIP, ~$9.7M street maintenance over FY2021-22 & FY2022-23, annualized
#@cite     https://stories.opengov.com/livermoreca/published/qebxtbqDg (accessed 2026-06-14)
current_budget = 4850000.0

[[cities]]
name = "Livermore, CA"
overpass = true
arcgis_url = "https://services5.arcgis.com/ROBnTHSNjoZ2Wm1P/arcgis/rest/services/Street_Centerlines/FeatureServer/0/query"

Effective configuration (with defaults)

[grid]
  hex_edge_m = 100.0

[display]
  units = "imperial"
  min_hex_area = 100.0

[export]
  title = ""
  coordinate_decimals = 0

[forecast]
  initial_pci = 75.0
  decay_rate = 0.035
  growth_rate = 0.0
  years = 20
  current_budget = 4.85e+06

  [[forecast.cost_tiers]]
    min_pci = 70.0
    max_pci = 101.0
    cost_per_sqm = 5.0
    label = "preventive"

  [[forecast.cost_tiers]]
    min_pci = 40.0
    max_pci = 70.0
    cost_per_sqm = 50.0
    label = "rehab"

  [[forecast.cost_tiers]]
    min_pci = 0.0
    max_pci = 40.0
    cost_per_sqm = 150.0
    label = "reconstruction"

[[cities]]
  name = "Livermore, CA"
  overpass = true
  arcgis_url = "https://services5.arcgis.com/ROBnTHSNjoZ2Wm1P/arcgis/rest/services/Street_Centerlines/FeatureServer/0/query"
  hex_edge_m = 0.0
  boundary_relation_id = 0
  allow_private_arcgis = false