Urban Public Transport Use and Socioeconomic Conditions in Genoa: A Logistic Regression Analysis and the Role of Artificial Intelligence

The introduction of artificial intelligence (AI) in public transportation networks presents a tremendous opportunity for efficiency, access and sustainability, in concert with larger conservation of environment and maximization of resources. Socioeconomic and demographic factors’ contribution toward public transportation use in Genoa, Italy, is examined in an ordered logistic model of analysis in this work. Outcomesmreveal residential location and gender to be the most significant factors, with reduced use of public transportation for suburban residents and increased use for females. With these trends in mobility, AI-facilitated technology can contribute to lessening access inequality in transportation, enhancing fleet efficiency and minimizing environmental footprint. With predictive analysis, real-time scheduling and personalized routing, AI can enhance current ineffectiveness, particularly in residential areas with less developed public transportation infrastructure. Real-time demand forecasting and price-setting through big-data analysis can contribute toward a cleaner and fairer transportation system. This study presents a baseline for AI integration in urban mobility planning, with its role in closing socioeconomic gaps, enhancing efficiency in public transportation and reducing greenhouse emissions. In follow-up studies, AI use in decarbonization in transportation, computerized fleet management and resilient mobility infrastructure can be studied in relation to urban transit planning, in consonance with international objectives for sustainability