Framework for Modeling Human Spatial Information Processing in Command and Control Systems.

摘要

One of the most important basic cognitive tasks of military operators the processing of spatial information. Soldiers involved in urban warfare need to be aware of the locations of red and blue forces. Local restrictions resulting from the topography of the urban battle space are taken into consideration when planning the next actions to complete a mission. Within a command and control system a number of tools exist to support the operator in processing spatial information. For the prospective design of human-machine interfaces of these tools in an engineering process, core principles of human performance need to be formulated into a computational theory. The proposed contribution will present a framework we developed to model human spatial information processing within a symbolic architecture of cognition. Within a sub-symbolic layer, spatial relations are represented as probability density functions modelling the uncertainty of their cognitive representation. Reasoning about spatial relations perceived from an external graphical display and their relation to internal cognitive spatial relations is reflected within the framework by the principle of Bayesian inference. In this way the cognitive processes of the human operator interacting with the visually perceived spatial information from an operational picture can be modelled and the graphical representation within the human-machine interface can be optimized. This contribution will discuss the theory for an application in an Anti-Air Warfare (AAW) scenario.