# A Systematic Literature Review on Safety of the Intended Functionality for Automated Driving Systems

arXiv: https://arxiv.org/abs/2503.02498 · HTML: https://mlsanity.com/paper/2503.02498/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 24 of its 101 references that are in the map.
- First posted on arXiv 4 Mar 2025.

## Builds on (most cited first, 24 of 24)

- [Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks](https://mlsanity.com/paper/2001.08001/) (2020)
- [Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System](https://mlsanity.com/paper/2204.07874/) (2022)
- [Engineering Safety Requirements for Autonomous Driving with Large Language Models](https://mlsanity.com/paper/2403.16289/) (2024)
- [Testing and verification of neural-network-based safety-critical control software: A systematic literature review](https://mlsanity.com/paper/1910.06715/) (2019)
- [Deep Learning Safety Concerns in Automated Driving Perception](https://mlsanity.com/paper/2309.03774/) (2023)
- [A Review of Testing Object-Based Environment Perception for Safe Automated Driving](https://mlsanity.com/paper/2102.08460/) (2021)
- [Safety of the Intended Driving Behavior Using Rulebooks](https://mlsanity.com/paper/2105.04472/) (2021)
- [PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in Long-tail Traffic Scenarios](https://mlsanity.com/paper/2211.03402/) (2022)
- [On the validation of complex systems operating in open contexts](https://mlsanity.com/paper/1902.10517/) (2019)
- [ViSTA: a Framework for Virtual Scenario-based Testing of Autonomous Vehicles](https://mlsanity.com/paper/2109.02529/) (2021)
- [SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving](https://mlsanity.com/paper/2211.04009/) (2022)
- [Self-Aware Trajectory Prediction for Safe Autonomous Driving](https://mlsanity.com/paper/2305.09147/) (2023)
- [Formal Certification Methods for Automated Vehicle Safety Assessment](https://mlsanity.com/paper/2202.02818/) (2022)
- [The Safety Shell: an Architecture to Handle Functional Insufficiencies in Automated Driving](https://mlsanity.com/paper/2311.08413/) (2023)
- [An Industrial Experience Report about Challenges from Continuous Monitoring, Improvement, and Deployment for Autonomous Driving Features](https://mlsanity.com/paper/2403.09474/) (2024)
- [Systematic Modeling Approach for Environmental Perception Limitations in Automated Driving](https://mlsanity.com/paper/2303.04029/) (2023)
- [Rethinking Certification for Higher Trust and Ethical Safeguarding of Autonomous Systems](https://mlsanity.com/paper/2303.09388/) (2023)
- [Is Scenario Generation Ready for SOTIF? A Systematic Literature Review](https://mlsanity.com/paper/2308.02273/) (2023)
- [Scenario-Based Safety Assessment Framework for Automated Vehicles](https://mlsanity.com/paper/2112.09366/) (2021)
- [State of the Art Study of the Safety Argumentation Frameworks for Automated Driving System Safety](https://mlsanity.com/paper/2302.00437/) (2023)
- [Triggering Conditions Analysis and Use Case for Validation of ADAS/ADS Functions](https://mlsanity.com/paper/2302.00551/) (2023)
- [On Quantification for SOTIF Validation of Automated Driving Systems](https://mlsanity.com/paper/2304.10170/) (2023)
- [SOTIF-Compliant Scenario Generation Using Semi-Concrete Scenarios and Parameter Sampling](https://mlsanity.com/paper/2308.07025/) (2023)
- [Safety of the Intended Functionality Concept Integration into a Validation Tool Suite](https://mlsanity.com/paper/2308.16670/) (2023)

## Abstract (arXiv)

In the automobile industry, ensuring the safety of automated vehicles equipped with the Automated Driving System (ADS) is becoming a significant focus due to the increasing development and deployment of automated driving. Automated driving depends on sensing both the external and internal environments of a vehicle, utilizing perception sensors and algorithms, and Electrical/Electronic (E/E) systems for situational awareness and response. ISO 21448 is the standard for Safety of the Intended Functionality (SOTIF) that aims to ensure that the ADS operate safely within their intended functionality. SOTIF focuses on preventing or mitigating potential hazards that may arise from the limitations or failures of the ADS, including hazards due to insufficiencies of specification, or performance insufficiencies, as well as foreseeable misuse of the intended functionality. However, the challenge lies in ensuring the safety of vehicles despite the limited availability of extensive and systematic literature on SOTIF. To address this challenge, a Systematic Literature Review (SLR) on SOTIF for the ADS is performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The objective is to methodically gather and analyze the existing literature on SOTIF. The major contributions of this paper are: (i) presenting a summary of the literature by synthesizing and organizing the collective findings, methodologies, and insights into distinct thematic groups, and (ii) summarizing and categorizing the acknowledged limitations based on data extracted from an SLR of 51 research papers published between 2018 and 2023. Furthermore, research gaps are determined, and future research directions are proposed.