SUSTAINABLE TRANSPORTATION SOLUTIONS: THE ROLE OF AI AND CLOUD TECHNOLOGIES

Abstract

This article examines the transformative role of Artificial Intelligence and cloud computing technologies in developing sustainable transportation solutions for modern urban environments. Through comprehensive analysis of implementation cases across major metropolitan areas, the article investigates the integration of smart systems in traffic management, predictive maintenance, and real-time optimization of transportation networks. The article employs a mixed-methods approach, combining quantitative analysis of transportation data with qualitative assessment of implementation frameworks, revealing significant improvements in operational efficiency and environmental sustainability. Key findings demonstrate a 30% reduction in average commute times, a 40% decrease in peak-hour congestion, and a 25% reduction in transportation-related CO2 emissions across studied cities. The article also addresses critical challenges in scalability, data privacy, and infrastructure readiness while providing insights into cost-benefit considerations and implementation strategies. Furthermore, it explores emerging trends and future implications for transportation policy, highlighting the importance of standardized protocols and updated regulatory frameworks. This article contributes to the growing body of knowledge on sustainable urban mobility, offering practical insights for city planners, policymakers, and technology implementers in developing efficient, environmentally conscious transportation systems for future cities.