Traffic Flow Modeling in Meskel Square Road, Addis Ababa, Ethiopia

This project analyzes traffic flow dynamics at Meskel Square, one of Addis Ababa's most congested intersections, using vehicle flow rate and travel time data collected over four days. Data was gathered in 5-minute intervals along a 60-meter road segment at peak and off-peak hours, capturing vehicle count, average speed, traffic density, flow rate, and rate of change.

The study employed Python and Matplotlib to convert raw collected data into meaningful visualizations, including flow rate vs. time graphs, speed vs. density scatter plots, and comparative multi-day charts. Additionally, the team developed a live AI-integrated camera system capable of tracking real-time vehicle movement and pedestrian activity at the intersection, enabling dynamic traffic monitoring beyond manual observation.

Observational data on pedestrian crossings, informal stopping behavior, and manual traffic police intervention were incorporated to explain anomalies in the quantitative results. The findings provide a quantitative foundation for recommending traffic management interventions such as signal timing optimization, infrastructure modifications, and intelligent traffic systems for Addis Ababa's urban core.