DECODING URBAN MOBILITY
ABSTRACT; Decoding Urban Mobility: This project evaluates the impact of AI-driven traffic management versus conventional fixed-timing methods on urban congestion. It analyzes real-time and historical data—including traffic patterns, weather, demographics, and incident reports—from cities like London, Barcelona, and Los Angeles and compares machine learning models (e.g., LSTM, GRU, XGBoost) with traditional techniques. The study identifies … Read more