Enhancing maritime autonomous surface ship navigation safety: A dynamic risk assessment framework integrating system theoretic process analysis and stochastic Petri nets

Zou, C, Chen, L, Fan, H ORCID: 0000-0002-1019-2099, Tian, X, Liu, L and Yang, Z ORCID: 0000-0003-1385-493X (2026) Enhancing maritime autonomous surface ship navigation safety: A dynamic risk assessment framework integrating system theoretic process analysis and stochastic Petri nets. Reliability Engineering and System Safety, 277. ISSN 0951-8320

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Abstract

The transition of maritime autonomous surface ships toward complex digital architectures has shifted navigation safety from a component reliability issue to a systemic control problem. Traditional failure-centric models struggle to capture non-linear interactions within complex network-featured control loops. This study proposes a control-centric hybrid framework integrating system-theoretic process analysis and stochastic Petri nets to bridge qualitative hazard identification with quantitative dynamic simulation. Initially, system-theoretic process analysis maps functional dependencies within the control loop, identifying risk-influencing factors and unsafe control actions. Subsequently, three critical propagation paths leading to system-level accidents are mapped onto an isomorphic stochastic Petri nets model to simulate dynamic risk evolution. A case study of the Yangtze River's Taicang section, utilizing automatic identification system records and meteorological data, is conducted to demonstrate the feasibility of the approach. The results reveal significant path dependence and systemic lock-in effects among environmental stressors, perceptual fidelity, and autonomous decision-making. Notably, the intelligent integration platform and autonomous ship control system serve as global risk convergence hubs, accounting for over 70% of steady-state risk in collision scenarios. Sensitivity analysis shows that improving environmental perception can cut overall risk by 55.5%. This framework provides a rigorous quantitative basis for systemic risk characterization and resilience enhancement.

Item Type:	Article
Uncontrolled Keywords:	Maritime autonomous surface ship; System-theoretic process analysis; Stochastic petri nets; Risk assessment; Maritime risk; 4007 Control Engineering, Mechatronics and Robotics; 40 Engineering; 01 Mathematical Sciences; 09 Engineering; 15 Commerce, Management, Tourism and Services; Strategic, Defence & Security Studies; 35 Commerce, management, tourism and services; 40 Engineering; 49 Mathematical sciences
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering and Built Environment
Publisher:	Elsevier
Date of acceptance:	5 July 2026
Date of first compliant Open Access:	2 September 2026
Date Deposited:	01 Sep 2026 15:15
Last Modified:	02 Sep 2026 00:50
DOI or ID number:	10.1016/j.ress.2026.113125
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29236

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