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Using bayesian networks to model competence of lifeboat coxswains

Billard R., Smith J., Masharraf M., Veitch B.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2020

Vol. 14. no. 3

585--594

The assessment of lifeboat coxswain performance in operational scenarios representing offshore emergencies has been prohibitive due to risk. For this reason, human performance in plausible emergencies is difficult to predict due to the limited data that is available. The advent of lifeboat simulation provides a means to practice in weather conditions representative of an offshore emergency. In this paper, we present a methodology to create probabilistic models to study this new problem space using Bayesian Networks (BNs) to formulate a model of competence. We combine expert input and simulator data to create a BN model of the competence of slow-speed maneuvering (SSM). We demonstrate how the model is improved using data collected in an experiment designed to measure performance of coxswains in an emergency scenario. We illustrate how this model can be used to predict performance and diagnose background information about the student. The methodology demonstrates the use of simulation and probabilistic methods to increase domain awareness where limited data is available. We discuss how the methodology can be applied to improve predictions and adapt training using machine learning.

Using the FRAM to Understand Arctic Ship Navigation: Assessing Work Processes During the Exxon Valdez Grounding

Smith D., Veitch B., Khan F., Taylor R.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2018

Vol. 12, no. 3

447--457

Arctic shipping involves a complex combination of inter-related factors that need to be managed correctly for operations to succeed. In this paper, the Functional Resonance Analysis Method (FRAM) is used to assess the combination of human, technical, and organizational factors that constitute a shipping operation. A methodology is presented on how to apply the FRAM to a domain, with a focus on ship navigation. The method draws on ship navigators to inform the building of the model and to learn about practical variations that must be managed to effectively navigate a ship. The Exxon Valdez case is used to illustrate the model’s utility and provide some context to the information gathered by this investigation. The functional signature of the work processes of the Exxon Valdez on the night of the grounding is presented. This shows the functional dynamics of that particular ship navigation case, and serves to illustrate how the FRAM approach can provide another perspective on the safety of complex operations.