video1.0<iframe src="https://www.loom.com/embed/41499761218f44b089ffaa9d3eb79b08" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/41499761218f44b089ffaa9d3eb79b08-f9d681f18bcda456.gif82.996In this video, I explain how traffic simulation models vehicle movements to analyze congestion and optimize traffic flow. I specifically focus on using SimPy, a Python-based framework, to create a traffic model that records important metrics like wait times and queue lengths. By analyzing these results, we can identify bottlenecks and develop strategies for improving traffic efficiency. I encourage you to explore the app I demonstrate and think about how we can apply these insights to our projects.