Toll modelling asks a harder question than ordinary assignment: not just where traffic
goes, but what drivers will pay to go there. Willingness to pay varies by trip purpose,
time of day, and value of time, and a model that ignores that will misprice the asset.
When you need it
Business cases for tolled infrastructure, lender and investor due diligence, toll pricing
strategy, and independent review of a third party’s patronage forecast.
Method
We implement logit-based toll choice functions with segmented values of time, calibrate
route choice behaviour against observed tolled and untolled movements, and stress-test the
forecast rather than presenting a single number. Where uncertainty is material we quantify
it — Monte Carlo analysis over the drivers rather than a deterministic point estimate.
Deliverables
Patronage and revenue forecasts by scenario, documented assumptions and elasticities,
sensitivity and risk analysis, and a technical report written to withstand lender scrutiny.