Case Study: UNDP Kuwait achieves rapid, reliable vehicle-count and emissions estimates for congested roads with Palisade's @RISK

UNDP Kuwait - Customer Case Study

UNDP Kuwait faced the challenge of estimating the number and mix of vehicles on congested 1‑km roadways to better quantify mobile-source pollution and traffic impacts. Working with Palisade, the team used the @RISK Monte Carlo add‑in for Excel to develop a novel stochastic method that avoids tedious manual counts and complex statistical packages.

Using Palisade’s @RISK, the project modeled four vehicle classes with PERT distributions for vehicle lengths, sampled inter‑vehicle gaps and speeds (5–40 KPH), and ran 5,000 iterations per scenario to produce power‑curve results of expected vehicle counts by speed and class on a 1‑km stretch. The Palisade‑powered solution delivered fast, repeatable estimates that can be linked to emissions data and applied to air‑quality analysis, civil engineering and telecommunications planning, demonstrating clear efficiency gains over traditional counting methods.

UNDP Kuwait

Brian Freeman

Team Leader