Artificial Intelligence and Machine Learning Applications in Decarbonized Transport
Abstract
The transportation sector accounts for approximately 24% of global energy-related carbon dioxide emissions, making it a critical domain for decarbonization efforts. Artificial intelligence and machine learning technologies have emerged as transformative tools for achieving sustainable transport systems through intelligent optimization of energy management, traffic flow, route planning, and predictive maintenance. This chapter provides a comprehensive examination of AI and ML applications across multiple transport modalities, including electric vehicles, autonomous driving systems, urban traffic management, and multimodal logistics. Through systematic analysis of recent innovations in reinforcement learning, deep neural networks, and predictive analytics, the chapter demonstrates how these technologies enable significant reductions in energy consumption and emissions while improving operational efficiency.