Artificial Intelligence in Autonomous Vehicles - A Comprehensive Review

Abstract

The rapid rise of Artificial Intelligence (AI) pushes self-driving cars from concept toward regular use - bringing opportunities along with serious challenges. To ensure these vehicles operate safely, equitably, and reliably, society must face complex technical, legal, and ethical issues.. This overview pulls together new studies on key parts of driverless driving, revealing how Explainable AI (XAI) helps show what machines are thinking and makes their choices easier to follow - understanding matters more once code takes control. Meanwhile, it looks at safety models like ISO/PAS 8800 that offer organized ways to spot dangers, judge risks, yet test AI behavior during regular situations. Moral dilemmas - such as snap choices in crashes or sorting out blame after breakdowns - show up along with digital threats able to mess with command systems or information flow, putting riders at risk. Besides this, linking smart robots through team strategies - combined with vehicle-to-everything setups and edge computing - boosts situational awareness, speeds up decisions, cuts response delays. The analysis wraps up by stressing that complete autonomy depends on a mix: reliable tech working alongside forward-thinking ethics, people teaming up with AI, plus consistent safety rules - to create driverless vehicles we can trust and that care about society.