Build demand forecasts for roads, rail, and air. Blend data with growth and elasticity drivers. Adjust scenarios, validate fit, and share results fast today.
| Segment | Base trips | Pop change | GDP change | Fare change | Service change |
|---|---|---|---|---|---|
| Urban peak | 850,000 | +8% | +10% | +4% | +12% |
| Urban off‑peak | 430,000 | +8% | +10% | +4% | +8% |
| Intercity | 320,000 | +6% | +12% | +6% | +5% |
This calculator blends two demand models: an elasticity-based driver model and an optional historical trend model. The elasticity model applies baseline growth and driver elasticities:
D(t) = D0 × (1+g)^t × Πᵢ (Xᵢ(t)/Xᵢ0)^(eᵢ)
The trend model fits a least-squares line to historical observations (and reports R²). The final forecast is a weighted blend: Forecast = w·Elasticity + (1−w)·Trend.
Over multi‑year horizons, small growth assumptions compound quickly\. For example, a 3\.00% baseline growth rate produces about 34\.4% cumulative growth over 10 years before driver elasticities are applied\. Use a shorter horizon for tactical service planning and a longer horizon for corridor capacity and investment evaluation\. In corridor studies, report the base year clearly and keep units consistent\. If you model vehicle‑kilometres, pair demand with average trip length assumptions elsewhere\. For peak forecasting, run separate inputs for peak and daily totals, then compare growth rates to observed screening counts and occupancy surveys before finalizing the investment case and design\.
Population and GDP typically push demand upward, while higher generalized cost (fare or toll) reduces demand. If population rises from 3.5 to 3.9 with elasticity 0.85, the population multiplier becomes roughly (3.9/3.5)^0.85 ≈ 1.09. Pair this with GDP and service multipliers to reflect development and quality improvements.
A fare elasticity of −0.35 means a 10% increase in fare reduces trips by about 3.5%, holding other drivers constant. A service elasticity of 0.50 means a 10% improvement in service index increases trips by roughly 5%. Keep elasticities mode‑specific; rail and air often differ from urban road traffic.
When you enter at least two historical observations, the calculator fits a linear trend and reports R². Higher R² indicates that a straight‑line model explains more of the observed variation. If R² is low, rely more on driver elasticities, or use segmented history to separate disruptions from stable periods.
The blend slider weights the elasticity model against the historical trend. A 65% elasticity weight emphasizes explanatory variables and policy levers, while 35% trend weight anchors results to observed behavior. If the trend projects negative values, it is automatically excluded to avoid invalid demand.
Scenario spread creates Low/High bands around the blended forecast, such as ±10%. Use these bands for stress testing: capacity design can reference the High path, while financial assessments may use the Base and Low paths. Export tables to share assumptions and maintain auditability across project teams.
It combines the effect of population, GDP, fare, and service changes into one factor. A value of 1.10 means demand is 10% higher at the horizon end due to those drivers.
Yes, but avoid double counting. Use annual growth for structural trends not explained by drivers, and GDP elasticity for the specific economic effect captured by your GDP index.
The trend model needs at least two valid historical year–trip points. If values are missing, non‑numeric, or zero/negative, they are skipped and the trend line cannot be computed.
Start near 50–70% elasticity when you trust drivers and want policy responsiveness. Increase the trend share when historical data is stable and recent, and when R² is reasonably high.
Many feasibility studies use ±5% to ±20%. Use smaller spreads for well‑observed mature corridors and larger spreads for disruptive projects, new pricing schemes, or uncertain land‑use changes.
Yes. Change the units label and enter base trips per day. Keep driver ratios and elasticities consistent with your time scale, and interpret results as average daily demand.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.