SAE J3312_202502

This SAE Technical Information Report identifies use cases for AI technology applications to ground vehicles and transportation infrastructure. Whenever applicable, functional definitions and noted issues and concerns are provided in consistent with the current industry mobility practices and published peer-reviewed literature. This SAE Technical Information Report prepared by SAE Ground Vehicle Artificial Intelligence (AI) Use Cases Task Force outlines the key applications and use cases of AI in ground vehicles and transportation infrastructure. It categorizes AI applications that improve safety, security, and efficiency in various vehicle operations. Examples include emissions control, battery health monitoring, vehicle automation, and advanced driver-assistance systems (ADAS). These AI technologies address challenges such as modeling complex vehicle behaviors, optimizing energy use in electric and hybrid vehicles, and enhancing real-time decision-making in autonomous systems. The report also discusses emerging AI trends, such as federated learning, which improves data security and privacy in connected vehicles, and physics-informed machine learning, which integrates physical principles into AI models for improved accuracy and reliability. Additionally, generative AI is highlighted as a tool for accelerating vehicle design, software development, and in-car personalization, showcasing its potential for revolutionizing the automotive industry. A roadmap for the adoption of these AI technologies includes recommendations for standardization, integration with existing vehicle systems, and addressing challenges like cybersecurity, data privacy, and continuous learning. AI-driven solutions are expected to play a crucial role in the future of vehicle design, operation, and maintenance, leading to more efficient, reliable, and safe ground transportation systems.