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Quantitative risk influencing factors (RIFs) are proposed, using the Conjugate Bayesian update approach to analyze 945 collision accidents and incidents cases from the Jiangsu Segment of the Yangtze River over five years from 2012 to 2016. The accident probability is compared under a pairwise comparison mode in order to reflect the relative risk between accidental situations. The Bayesian update mode is constructed to quantitatively evaluate the relative importance of different RIFs. The riskiest segment of Jiangsu Waterways as well the main causations of collisions are identified based on the distributions of collision risk in the six segments of the waterways. The results can support managers to develop the most effective policies to mitigate the collision risk. [ABSTRACT FROM AUTHOR]

Global research interest in the domain of maritime autonomous surface ships (MASS) is dramatically increasing. With new prototypes planned to be set to the seas where various operational modes (OMs) are claimed, the issue of the safety evaluation of an MASS, and criteria for selecting the appropriate OM for given conditions remain open questions. This paper proposes a four-step risk-informed framework to assess risk in a scenario for an MASS operating at one of three OMs: manual control (MC), remote control (RC), and autonomous control (AC). To this end, the concept of risk priority numbers (RPNs), adopted from failure mode and effects analysis (FMEA), is utilized. The required parameters to defined RPNs are obtained in the course of analyzing a model MASS accident with expert knowledge. The applicability of the proposed framework is demonstrated via a model MASS case study. Results reveal that, in the same scenario, the risk of MASS varied across the analyzed OMs. On the basis of the aggregated results for each operational mode, suggestions for OM switching are put forward. [ABSTRACT FROM AUTHOR]

Maritime Autonomous Surface Ships (MASS) have recently drawn significant attention throughout academia, governments, and industry. One of the requirements for MASS is that they should at least be as safe as conventional ships. Often, to measure their level of safety, the concept of risk is adopted, and risk influencing factors are determined. This paper proposes a framework for the identification of factors that influence the navigational risk of remotely controlled MASS without crews on board. Therein, four operational phases are considered: voyage planning, berthing and unberthing, port approaching and departing, as well as open sea navigation. For each phase, four types of factors are assigned related to human, ship, environment, and technology. To populate the framework, a thorough literature review is conducted, which is further supported by the elicitation of expert knowledge. As a result, 23 human-related factors, 12 ship-related factors, 8 environment-related factors, and 12 technology-related factors were defined. The proposed framework can be employed for any risk and safety analysis related to remote-controlled MASS. This, in turn, may assist the processes of design and operational planning of maritime transportation systems accommodating MASS and its remote-control center, e.g., the shore control center. •Risk influencing factors (RIF) for Maritime Autonomous Surface Ship operating at third degree of autonomy (MASS DoA3) is investigated. •A 4P4F framework is proposed to identify RIF on MASS DoA3, focusing on 4 operational phases and 4 types of factors. •Literature and experts' experience are utilized for identifying RIF and assigning them into 4 operational phases. •23 human factors, 12 ship factors, 8 environment factors, and 12 technology factors are identified as RIFs related to MASS DoA3 navigation. [ABSTRACT FROM AUTHOR]