Ethical AI Decision-Making Systems for Autonomous Vehicles: Challenges, Solutions and Regulatory Framework

Autonomous vehicles (AVs) represent a transformative technology with the potential to revolutionize transportation systems worldwide. As these vehicles increasingly rely on artificial intelligence to make complex real-time decisions, significant ethical challenges emerge, particularly in scenarios where harm is unavoidable and ethical trade-offs must be considered. This paper provides a comprehensive analysis of ethical AI decision-making systems for autonomous vehicles, examining the philosophical foundations, technical implementation challenges, proposed solutions, and regulatory frameworks. We identify key ethical dilemmas including the trolley problem variants, vulnerable road user prioritization, and data bias concerns. Technical approaches to ethical implementation are evaluated, including rule-based systems, utilitarian frameworks, virtue ethics implementations, and hybrid models. The paper further examines current regulatory initiatives across major jurisdictions, highlighting gaps in existing frameworks. We propose a multi-stakeholder governance model that balances innovation with ethical safeguards through harmonized international standards, adaptive regulation, mandatory ethics reviews, and transparent accident investigation protocols. Our analysis suggests that successful ethical AI for autonomous vehicles requires not only sophisticated technical solutions but also carefully crafted regulatory frameworks that can adapt to rapidly evolving technology while maintaining clear accountability mechanisms and public trust.

Keywords:

autonomous vehicles , ethical AI , decision-making systems , trolley problem , regulatory frameworks , machine ethics