# Conducting Traffic And Demand Studies

> Evaluates demand forecasts for toll roads, airports, and ports with independent engineer review and scenario sensitivity analysis. Use when analyzing traffic studies, validating demand forecasts, or stress testing revenue projections.

- Skill: `lev-os/conducting-traffic-and-demand-studies` (Agent Skill)
- Install (CLI): `npx skillmds@latest add lev-os/conducting-traffic-and-demand-studies`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lev-os/conducting-traffic-and-demand-studies/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Finance & Business
- Author: lev-os (https://skillmd.com/u/lev-os)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/lev-os/conducting-traffic-and-demand-studies

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# Conducting Traffic And Demand Studies

## When To Use

- Reviewing an independent traffic consultant's demand forecast for a toll road, managed lane, bridge, or tunnel concession
- Evaluating passenger or cargo throughput projections for airport or port financings
- Stress-testing revenue assumptions in a P3/PPP financial model prior to financial close
- Assessing ramp-up risk during construction-to-operations transition
- Comparing competing demand studies submitted by sponsor vs. lender's independent engineer (IE)

## Inputs To Gather

- **Traffic/demand study report** from the independent traffic consultant (e.g., Steer, CDM Smith, AECOM)
- **Base-case financial model** with revenue line items linked to volume assumptions
- **Socioeconomic data inputs** used in the model (population growth, employment, GDP, vehicle registrations)
- **Network and route assumptions** — competing facilities, planned capacity additions, toll/tariff schedules
- **Historical traffic data** (if brownfield) — at least 5 years of monthly volumes by vehicle class or passenger type
- **Concession/PPP agreement** sections on toll escalation, revenue sharing, and minimum traffic guarantees
- **Independent engineer report** and any lender technical advisor commentary on the demand study
- **Comparable asset benchmarks** — ramp-up curves and mature-year volumes from similar facilities [VERIFY jurisdiction-specific data availability]

## Workflow

1. **Validate methodology and model structure**
   - Confirm the demand model type (four-step transport model, stated-preference survey, gravity model, econometric regression) and whether it is appropriate for the asset class
   - Check that the model's zone system, network coding, and assignment algorithm are consistent with the study area
   - For airports: verify air traffic movement forecasts use unconstrained demand adjusted for capacity constraints
   - For ports: confirm TEU/tonnage projections account for hinterland competition and shipping route shifts

2. **Audit socioeconomic assumptions**
   - Compare population and employment growth rates against independent government or third-party forecasts (e.g., census bureau, state demographer, Woods & Poole)
   - Assess whether GDP elasticity assumptions are within accepted ranges for the asset type (typically 0.8–1.2 for toll roads, 1.5–2.5 for airports) [VERIFY against current industry benchmarks]
   - Flag any assumption that deviates materially from the IE's independent view

3. **Evaluate ramp-up profile**
   - For greenfield assets, benchmark the ramp-up curve against comparable facilities — typical toll road ramp-up is 3–5 years to reach stabilized demand
   - Assess whether the study accounts for induced demand, mode shift, and traveler learning curves
   - Check that Year 1 volumes reflect realistic day-one capture, not annualized mature-year demand

4. **Test toll/tariff sensitivity**
   - Verify price elasticity values used in the model (typical range: −0.1 to −0.4 for toll roads) [VERIFY asset-specific elasticity ranges]
   - Confirm that toll escalation assumptions (CPI-linked, fixed schedule, dynamic pricing) match the concession agreement
   - Run or review scenarios with +/−20% volume variance and corresponding revenue impact

5. **Perform scenario and downside analysis**
   - **Base case**: consultant's central forecast
   - **Rating agency case**: typically 70–80% of base-case volumes (S&P/Moody's/Fitch methodology) [VERIFY current rating agency haircut conventions]
   - **Bankable case / P90**: downside used for debt sizing, often 80–90% of base
   - **Stress case**: recession scenario with GDP contraction and demand drop of 20–30%
   - Calculate DSCR under each scenario and confirm covenant compliance

6. **Cross-check against comparable assets**
   - Compile volume data from comparable toll roads, airports, or ports at similar stages of maturity
   - Identify whether the study's forecasts sit within the reasonable range of comparables
   - Flag outlier assumptions (e.g., per-capita trip rates significantly above peer facilities)

7. **Assess independent engineer and lender advisor positions**
   - Summarize the IE's haircuts or adjustments to the sponsor's traffic study
   - Note any unresolved disagreements between the traffic consultant and the IE
   - Identify conditions precedent tied to traffic study acceptance

## Output

- **Demand Study Review Memo** containing:
  - Executive summary of forecast reasonableness (supportable / conditionally supportable / not supportable)
  - Methodology assessment with identified strengths and weaknesses
  - Socioeconomic assumption comparison table (study vs. independent sources)
  - Ramp-up benchmarking chart against comparable assets
  - Scenario matrix: volumes, revenues, and DSCRs across base/downside/stress cases
  - Elasticity sensitivity table showing revenue impact of toll/tariff changes
  - Risk register of key demand-side risks (competing routes, policy changes, autonomous vehicles, remote work trends)
  - Recommendations for structuring protections (reserve accounts, minimum revenue guarantees, traffic band mechanisms)

## Quality Checks

- All socioeconomic inputs are cross-referenced against at least two independent data sources
- Elasticity values fall within published ranges for the asset class; outliers are justified or flagged with [VERIFY]
- Ramp-up assumptions are benchmarked against at least three comparable facilities
- DSCR calculations under the rating agency case confirm the project meets minimum coverage thresholds (typically 1.20x–1.40x for investment-grade toll roads) [VERIFY lender/rating agency specific thresholds]
- The financial model's revenue line items reconcile to the traffic study's volume and toll/tariff outputs
- Competing facility analysis reflects committed and funded projects, not speculative proposals
- Any assumption inherited from the sponsor without independent verification is explicitly marked