A model of the vessel traffic process

A model of the total vessel traffic control process that includes the functioning of the human operator (HO) is presented. The vessel traffic services (VTSs) are modeled in their possible role of monitor, conflict detector, and advisor for the total vessel traffic system. The model assumes a number of ships, with a given planned route, in a given confined area. The navigation of each ship is based on a planned route, which is updated by information about the visual scene, instruments, and the VTS. Both normal operation and collision avoidance are modeled. The model is implemented in a C program. Typical traffic situations have been simulated to showing the ability of the model to address realistic vessel traffic scenarios. The model can answer questions related to safety and efficiency, the effect of HO functioning, information necessary to perform tasks, communication between ships and VTS, the optimization of procedures, automation of the total vessel traffic process, et

Model of large scale man-machine systems with an application to vessel traffic control

Mathematical models are discussed to deal with complex large-scale man-machine systems such as vessel (air, road) traffic and process control systems. Only interrelationships between subsystems are assumed. Each subsystem is controlled by a corresponding human operator (HO). Because of the interaction between subsystems, the HO has to estimate the state of all relevant subsystems and the relationships between them, based on which he can decide and react. This nonlinear filter problem is solved by means of both a linearized Kalman filter and an extended Kalman filter (in case state references are unknown and have to be estimated). The general model structure is applied to the concrete problem of vessel traffic control. In addition to the control of each ship, this involves collision avoidance between ship

Modeling cluster-level constructs measured by individual responses:Configuring a shared approach

When multiple items are used to measure cluster-level constructs with individual-level responses, multilevel confirmatory factor models are useful. How to model constructs across levels is still an active area of research in which competing methods are available to capture what can be interpreted as a valid representation of cluster-level phenomena. Moreover, the terminology used for the cluster-level constructs in such models varies across researchers. We therefore provide an overview of used terminology and modeling approaches for cluster-level constructs measured through individual responses. We classify the constructs based on whether (a) the target of measurement is at the cluster level or at the individual level and (b) the construct requires a measurement model. Next, we discuss various two-level factor models that have been proposed for multilevel constructs that require a measurement model, and we show that the so-called doubly latent model with cross-level invariance of factor loadings is appropriate for all types of constructs that require a measurement model. We provide two illustrations using empirical data from students and organizational teams on stimulating teaching and on conflict in organizational teams, respectively.</p