Riyadh Urban Transport — EV Adoption Scenarios (20% Fleet Penetration)

This dataset provides the simulation-based results for Figures 5, 6, and 7 of the discussion paper "Urban Transport Policies and Emission Reduction Strategies in Riyadh: Insights from a Multi-Agent Simulation" (2026). Using the METROPOLIS2 multi-agent model, the dataset compares uniform vs. distance-targeted EV incentives at 20% fleet penetration, showing that targeting high-mileage drivers above the 75th percentile achieves a 32.3% CO₂ reduction compared to 20.1% under uniform adoption. It also demonstrates that the same emissions reduction can be achieved with up to 29.7% fewer vehicle switches through better targeting.