Towards Carbon-Free Automotive Futures: Leveraging AI And ML For Sustainable Transformation

Abstract

This paper delves into the transformative role of artificial intelligence (AI) and machine learning (ML) in reshaping the automotive industry towards sustainability and environmental consciousness. It begins by examining the integration of intelligent infrastructure, such as sensor-equipped traffic signal lights and cameras, aimed at enhancing road safety and efficiency. Furthermore, the development of autonomous driving and connected vehicle technologies, in conjunction with advancements in V2X communication and 5G technology, presents promising avenues for reducing energy consumption and CO2 emissions in transportation. A critical analysis of the current state of carbon emissions in the automotive industry underscores the pressing need to transition towards carbon-free alternatives, with AI and ML identified as essential tools for predicting emissions, optimizing energy demand, managing electric vehicles, and implementing eco-driving strategies to achieve zero-carbon emissions. Additionally, the paper explores various AI/ML applications for vehicle efficiency improvement, battery optimization, electric vehicle charging, and intelligent traffic management, highlighting their contributions to emissions reduction and improved traffic flow. Nonetheless, the integration of AI/ML into carbon-free automotive futures poses challenges such as regulatory hurdles, infrastructure development, and ethical considerations. Despite these challenges, AI and ML offer promising solutions to mitigate climate change and drive towards a sustainable automotive industry.