# Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM)

arXiv: https://arxiv.org/abs/2501.10839 · HTML: https://mlsanity.com/paper/2501.10839/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Large language models for driving, one of 9 directions in End-to-end autonomous driving.
- Builds on 13 of its 28 references that are in the map.
- First posted on arXiv 18 Jan 2025.

## Placed in

- End-to-end autonomous driving / [Large language models for driving](https://mlsanity.com/driving/large-language-models-for-driving/)

## Builds on (most cited first, 13 of 13)

- [MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction](https://mlsanity.com/paper/2111.14973/) (2021)
- [Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving](https://mlsanity.com/paper/2310.01957/) (2023)
- [A Survey on the Explainability of Supervised Machine Learning](https://mlsanity.com/paper/2011.07876/) (2020)
- [A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems](https://mlsanity.com/paper/2005.02979/) (2020)
- [Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving](https://mlsanity.com/paper/2210.09539/) (2022)
- [Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs](https://mlsanity.com/paper/2310.13976/) (2023)
- [Probabilistic Prediction of Vehicle Semantic Intention and Motion](https://mlsanity.com/paper/1804.03629/) (2018)
- [Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula](https://mlsanity.com/paper/2212.01375/) (2022)
- [Waymo's Safety Methodologies and Safety Readiness Determinations](https://mlsanity.com/paper/2011.00054/) (2020)
- [Lessons from the Use of Natural Language Inference (NLI) in Requirements Engineering Tasks](https://mlsanity.com/paper/2405.05135/) (2024)
- [Autonomous Systems -- An Architectural Characterization](https://mlsanity.com/paper/1811.10277/) (2018)
- [Normative Requirements Operationalization with Large Language Models](https://mlsanity.com/paper/2404.12335/) (2024)
- [Compositionally Safe Construction of Autonomous Driving Systems](https://mlsanity.com/paper/2405.11995/) (2024)

## Abstract (arXiv)

Generative Artificial Intelligence (GAI) and the idea to use hierarchical models has been around for some years now. GAI has proved to be an extremely useful tool for Autonomous Vehicles (AVs). AVs need to perform robustly in their environment. Thus the AV behavior and short-term trajectory planning needs to be: a) designed and architected using safeguarding and supervisory systems and b) verified using proper Systems Engineering (SysEng) Principles. Can AV Systems Engineering also use Large Language Models (LLM) to help Autonomous vehicles (AV) development? This reader-friendly paper advocates the use of LLMs in 1) requirements (Reqs) development and 2) Reqs verification and 3) provides a proof-of-concept of AV supervisory control. The latter uses a simulation environment of a simple planar (bicycle) vehicle dynamics model and a Linear Quadratic Regulator (LQR) control with an LLM Application Interface (API). The Open-Source simulation SW is available from the author accessible to the readers so that they can engage into the AV stack, LLM API and rules, SysEng and Reqs and fundamental vehicle dynamics and control.