That’s a solid proposition, but I’ll need the data on how it scales with peak loads and the impact on existing infrastructure. Let’s sketch a quick feasibility outline and see if the projected 30% cut holds up under real‑world variability.

Here’s a streamlined approach: 1) Collect current traffic volumes, average speeds, and accident data. 2) Model rush‑hour and off‑peak conditions with typical demand curves. 3) Use a validated traffic simulation platform—e.g., SUMO or VISSIM—to run scenarios. 4) Map integration with existing road network and traffic signal controllers, noting required API hooks. 5) Track metrics: average travel time, queue lengths, emissions, and throughput. 6) Identify risks: data gaps, implementation lag, driver compliance, and system resilience to failures. That keeps us focused on scalability and real‑world impact.