Toward Fully Autonomous Driving: AI, Challenges, Opportunities, and Needs

2026-01-30

IEEE Access

AI Summary

This study addresses the core challenges of achieving full autonomy in open, dynamic environments—namely safety, generalization, and real-world deployability. It systematically examines the application of artificial intelligence in perception, decision-making, and control, contrasting AI-driven approaches with traditional methods to elucidate their advantages and inherent limitations. Emphasizing critical issues such as safety assurance and cross-domain transferability, the work identifies essential technical requirements for realizing fully autonomous driving. Furthermore, it outlines a forward-looking trajectory for technological evolution and proposes key research directions to advance AI-enabled autonomous driving systems, offering both theoretical foundations and practical guidance for future development.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Computer Vision: Vision for Robotics & Autonomous Driving
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Security and privacy of machine learning and AI applications

Abstract

Automated driving (AD) is promising, but the transition to fully autonomous driving is, among other things, subject to the real, ever-changing open world and the resulting challenges. However, research in the field of AD demonstrates the ability of artificial intelligence (AI) to outperform classical approaches, handle higher complexities, and reach a new level of autonomy. At the same time, the use of AI raises further questions of safety and transferability. To identify the challenges and opportunities arising from AI concerning autonomous driving functionalities, we have analyzed the current state of AD, outlined limitations, and identified foreseeable technological possibilities. Thereby, various further challenges are examined in the context of prospective developments. In this way, this article reconsiders fully autonomous driving with respect to advancements in the field of AI and carves out the respective needs and resulting research questions.

Problem

• autonomous driving
• artificial intelligence
• safety
• transferability
• open-world challenges

Innovation

• autonomous driving
• artificial intelligence
• safety
• transferability
• open-world challenges