Modeling the Cognitive Task Load and Performance of Naval Operators

Abstract. Operators on naval ships have to act in dynamic, critical and highdemand task environments. For these environments, a cognitive task load (CTL) model has been proposed as foundation of three operator support functions: adaptive task allocation, cognitive aids and resource feedback. This paper presents the construction of such a model as a Bayesian network with probability relationships between CTL and performance. The network is trained and tested with two datasets: operator performance with an adaptive user interface in a lab-setting and operator performance on a high-tech sailing ship. The “Naïve Bayesian network ” tuned out to be the best choice, providing performance estimations with 86 % and 74 % accuracy for respectively the lab and ship data. Overall, the resulting model nicely generalizes over the two datasets. It will be used to estimate operator performance under momentary CTL-conditions, and to set the thresholds of the load-mitigation strategies for the three support functions

Geovisual Analytics Environment for Supporting the Resilience of Maritime Surveillance System

International audienceThis paper presents an original approach for supporting the resilience in Maritime Domain Awareness, based on geovisual analytics. While many research projects focus on developing rules for detecting anomalies at by automated means, there is no support to visual exploration led by human operators. We investigate the use of visual methods for analyzing mobility data of ships. Behaviors of interest can be known (modeled) or unknown, asking for various ways of visualizing and studying the information. We assume that supporting the use of geovisual analytics will make the exploration and the analysis process easier, reducing the cognitive load of the tasks led by the actors of maritime surveillance. The detection and the identification of threats at sea are improved by using adequate visualization methods, regarding the context of use. Our suggested framework is based on ontologies for maritime domain awareness and geovisual analytics environments, coupled to rules

A simulation-based decision-support system for integration of human cognition into construction operation planning

The mental workload associated with work activities is a key factor affecting the performance of human resources in labor-intensive construction operations, in turn impacting work behavior. While most accidents in construction are caused by unsafe behavior, modeling behavior in construction projects remains challenging and relatively unexplored. Here, human cognition is incorporated into the design of construction operations to analyze the mental task demands associated with various designs. A framework that integrates cognitive modeling with a simulation-based decision-support system capable of analyzing existing and non-existing operations in a simple and automated manner is proposed. The superiority of the proposed framework is that it eliminates the need for prior knowledge of the underlying cognitive theories. Functionality of the developed framework was evaluated following its application to a case study of welding operations, where the proposed method was shown to successfully evaluate the trade-off between mental workload and productivity for different operation scenarios

Human factors consideration in the automation design of a safety-critical installation

M.Ing. (Engineering Management)Abstract: Human factors consideration should form an integral part of any system’s design. The aim is to ensure the designed system is compatible with human skills and limitations. Benefits of this consideration include reduction in the required level of training once the system is deployed. Unfortunately, even though the requirement of humans in systems design is well known, systems are continuously designed with little or no input from the eventual operators. This study aims to investigate the human factors aspect in the automation design of a safety-critical installation. Automation in its noble form is intended to improve factors such as safety, efficiency, and costs. However, this is not always the case. Part of the problem is that human operators are not always adequately considered during the design. It is the aim of this study to elicit the important human factors that must be considered in the automation design. This is done using a case study method. The case study was undertaken at the major radioisotopes production institution in the Republic of South Africa. The use of this study method is adopted as it provides enough in-depth knowledge that can be used in other safety-critical facilities

An evaluation of the effects of simulator training on ice management performance

This research offers practical insights into the relationship between amount of training and ice management performance. In a previous experiment, it was found that, on average, experienced seafarers performed better in an ice management simulator than inexperienced cadets (Veitch, 2018). In a current experiment, two additional groups of inexperienced cadets were trained for ice management in either one or two sessions. The training included viewing examples of expert performance and completing practice scenarios in a simulator. After training, the cadets completed two ice management simulator scenarios, one of which was the same as that used in the previous experiment. Training was found to have a positive effect on ice management performance in most scenarios. In the scenario used in both experiments, ice management performance improved with increasing amounts of training and the results demonstrate a proposed method for estimating the amount of training required to reach a performance target

Formalisation d'un environnement d'aide à l'analyse géovisuelle: Application à la sécurité et sûreté de la maritimisation de l'énergie

The maritime space is still a sensitive area due to many accidents and dangers, such as collisions or pirate attacks. In order to ensure the control of safety and security of this area, it is essential to study near real-time movement information (surveillance) or past events (analysis). Controllers and analysts are then faced to large sets of data, which must be studied with systems using maps and other visualizations. However, these tools are limited in terms of analysis capacities. Using geovisual analytics could be used to improve pattern identification, anomalies detection and knowledge discovery. However, due to the complexity of their use, most methods are still at the stage of research, and are not used yet in the operational word for studying maritime risks.In this context, we propose a geovisual analytics support system to guide users in the visualization and the analysis of maritime risks. Our research methodology is based on the formalization of use cases, of users and of several visualization methods. Ontologies and rules are used to create a knowledge-based system, to select adequate solutions for the visualization and the analysis of ships’ trajectories. Some examples for analyzing maritime risks are then presented to illustrate the use of such a system.L’espace maritime est encore aujourd’hui le contexte de nombreux accidents et dangers, comme des collisions ou des attaques pirates. Afin de garantir le contrôle de la sûreté et de la sécurité de cet espace, il est nécessaire d’étudier les données de mouvement en temps réel (surveillance) et les évènements passés (analyse). Contrôleurs et analystes sont alors confrontés à de grandes quantités de données, qui doivent être étudiées grâce à des systèmes utilisant des cartes et autres visualisations. Cependant, ces outils sont limités en termes de capacités d’analyse. L’utilisation de méthodes d’analyse géovisuelle pourrait alors faciliter la reconnaissance de motifs, la détection d’anomalies et la découverte de connaissances. Toutefois, en raison de leur complexité d’utilisation, plusieurs de ces méthodes n’ont pas dépassé le stade académique, et ne sont pas encore utilisées de manière opérationnelle dans l’étude des risques maritimes.Dans ce contexte, nous proposons un environnement d’aide à l’analyse géovisuelle, qui permet de guider l’utilisateur dans la visualisation et l’analyse d’informations pour l’étude des risques maritimes. Notre démarche de thèse se fonde sur la formalisation des cas d’utilisation, des utilisateurs et des méthodes de visualisation. Le recours à des ontologies et des règles permet de concevoir un système à base de connaissances, afin de proposer des méthodes adéquates pour la visualisation et l’analyse des trajectoires de navires. Nous illustrons cette proposition par plusieurs exemples d’analyse de risques en mer