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

arXiv: https://arxiv.org/abs/2601.22927 · HTML: https://mlsanity.com/paper/2601.22927/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2026.

## Built on by (most cited first, 1 of 1)

- [MAGNIFIED: RL Fine-tuning of Multimodal Large Language Models for Motion Planning](https://mlsanity.com/paper/2606.20641/) (2026)

## Abstract (arXiv)

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.