# Decomposition and Quantification of SOTIF Requirements for Perception Systems of Autonomous Vehicles

arXiv: https://arxiv.org/abs/2501.10097 · HTML: https://mlsanity.com/paper/2501.10097/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Jan 2025.

## Built on by (most cited first, 2 of 2)

- [DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models](https://mlsanity.com/paper/2505.07084/) (2025)
- [A Task-Agnostic Algebraic Integrity Metric for Event-Camera Streams Toward SOTIF-Compliant Perception using Pearson Correlation Coefficient](https://mlsanity.com/paper/2605.21500/) (2026)

## Abstract (arXiv)

Ensuring the safety of autonomous vehicles (AVs) is paramount before they can be introduced to the market. More specifically, securing the Safety of the Intended Functionality (SOTIF) poses a notable challenge; while ISO 21448 outlines numerous activities to refine the performance of AVs, it offers minimal quantitative guidance. This paper endeavors to decompose the acceptance criterion into quantitative perception requirements, aiming to furnish developers with requirements that are not only understandable but also actionable. This paper introduces a risk decomposition methodology to derive SOTIF requirements for perception. More explicitly, for subsystemlevel safety requirements, we define a collision severity model to establish requirements for state uncertainty and present a Bayesian model to discern requirements for existence uncertainty. For component-level safety requirements, we proposed a decomposition method based on the Shapley value. Our findings indicate that these methods can effectively decompose the system-level safety requirements into quantitative perception requirements, potentially facilitating the safety verification of various AV components.