SOTIF (ISO 21448) for Heavy-Duty Commercial Vehicle ADAS: A Practical Implementation Framework

Authors

  • Mahesh Kumar Shanmugam

Keywords:

SOTIF, ISO 21448, ISO 26262, Class 8 trucks, heavy-duty vehicles, ADAS, AEBS, ACC, LDW, TSR, triggering conditions, commercial vehicle safety

Abstract

ISO 21448, formally addressing the Safety of the Intended Functionality (SOTIF), was published in 2022 to address safety risks arising from functional insufficiencies in advanced driver assistance systems and automated driving functions, even when no system malfunction has occurred [1]. This distinguishes SOTIF from ISO 26262, which primarily addresses hazards caused by electrical and electronic system faults [2]. As of 2023, practical SOTIF implementation guidance for heavy-duty commercial vehicle Advanced Driver Assistance Systems (ADAS) remained limited in public literature. The only publicly available heavy-truck SOTIF example was a concept-level platooning hazard analysis, not a production-oriented methodology for Class 8 ADAS features [5]. This paper proposes a six-phase SOTIF implementation framework for Class 8 commercial vehicle ADAS, covering item definition, hazard identification, triggering-condition analysis, functional modification, verification and validation evidence generation, and release-operation feedback. The framework addresses truck-specific SOTIF challenges including variable payload, trailer articulation, pneumatic brake response, sensor mounting height, maintenance variability, and commercial duty cycles. The proposed approach provides original practical guidance for applying SOTIF to production-relevant heavy-duty ADAS features such as Adaptive Cruise Control, Automatic Emergency Braking Systems, Lane Departure Warning, and Traffic Sign Recognition. The contribution of this paper is a truck-specific, implementation-oriented SOTIF framework that bridges the gap between ISO 21448 process principles and the operational realities of Class 8 commercial vehicle safety engineering.

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References

International Organization for Standardization. (2022). ISO 21448: Road vehicles—Safety of the intended functionality. ISO.

International Organization for Standardization. (2018). ISO 26262: Road vehicles—Functional safety. ISO.

Burton, S., Gauerhof, L., & Heinzemann, C. (2012). Making the case for safety of machine learning in highly automated driving. Lecture Notes in Computer Science, 7613, 5–16.

Burton, S., Herd, B., Lünstedt, S., & Schaefer, I. (2023). Addressing uncertainty in the safety assurance of machine-learning. Frontiers in Computer Science, 5, 1–16.

Birkemeyer, L., King, C., & Schaefer, I. (2023). Is scenario generation ready for SOTIF? A systematic literature review. arXiv Preprint, arXiv:2308.02273.

Koné, A., Espié, S., & Gruyer, D. (2023). An approach to guide the search for potentially hazardous scenarios for autonomous vehicle safety validation. Applied Sciences, 13(11), 6717.

Putze, L., Westhofen, L., Koopmann, T., Böde, E., & Neurohr, C. (2023). On quantification for SOTIF validation of automated driving systems. arXiv Preprint, arXiv:2304.10170.

Ulbrich, S., Menzel, T., Reschka, A., Schuldt, F., & Maurer, M. (2015). Defining and substantiating the terms scene, situation, and scenario for automated driving. In 2015 IEEE 18th International Conference on Intelligent Transportation Systems (pp. 982–988). IEEE.

Bagschik, G., Menzel, T., & Maurer, M. (2018). Ontology based scene creation for the development of automated vehicles. In 2018 IEEE Intelligent Vehicles Symposium (pp. 1813–1820). IEEE.

Riedmaier, S., Ponn, T., Ludwig, D., Schick, B., & Diermeyer, F. (2020). Survey on scenario-based safety assessment of automated vehicles. IEEE Access, 8, 87456–87477.

Koopman, P., & Wagner, M. (2017). Autonomous vehicle safety: An interdisciplinary challenge. IEEE Intelligent Transportation Systems Magazine, 9(1), 90–96.

Kalra, N., & Paddock, S. M. (2016). Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? RAND Corporation.

SAE International. (2021). SAE J3016: Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. SAE International.

International Organization for Standardization. (2022). ISO 34502: Road vehicles—Scenario-based safety evaluation framework. ISO.

National Highway Traffic Safety Administration & Battelle Memorial Institute. (2021). Hazard analysis of concept heavy-truck platooning systems. U.S. Department of Transportation.

National Highway Traffic Safety Administration & Federal Motor Carrier Safety Administration. (2023). Heavy vehicle automatic emergency braking; AEB test devices: Notice of proposed rulemaking. Federal Register, 88(128).

United Nations Economic Commission for Europe. (2013). UN Regulation No. 131: Advanced Emergency Braking Systems (AEBS).

United Nations Economic Commission for Europe. (2013). UN Regulation No. 130: Lane Departure Warning Systems (LDWS).

U.S. Code of Federal Regulations. (2023). Federal Motor Vehicle Safety Standard No. 121: Air brake systems (49 CFR §571.121).

U.S. Code of Federal Regulations. (2023). Federal Motor Vehicle Safety Standard No. 136: Electronic stability control systems for heavy vehicles (49 CFR §571.136).

PEGASUS Project Consortium. (2019). PEGASUS method: An overview of the PEGASUS project results. German Aerospace Center (DLR).

Adee, R., et al. (2023). Systematic modeling approach for environmental perception limitations in automated driving. arXiv Preprint, arXiv:2303.04029.

ASAM e.V. (2022). ASAM test specification study group report 2022. ASAM.

TÜV SÜD. (2023). Safety in ADAS/AD—SOTIF: A risk-based approach. TÜV SÜD White Paper.

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Published

27.12.2023

How to Cite

Mahesh Kumar Shanmugam. (2023). SOTIF (ISO 21448) for Heavy-Duty Commercial Vehicle ADAS: A Practical Implementation Framework. International Journal of Intelligent Systems and Applications in Engineering, 11(11s), 1113 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/8340

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Section

Research Article