Automation Technology and Human Performance: Current Research and Trends

By Mark W. Scerbo | Go to book overview

Dynamic Function Allocation for Naval Command and Control

Catherine A. Morgan, Catherine A. Cook and Colin Corbridge DERA Centre for Human Sciences, UK


INTRODUCTION

Dynamic function allocation (DFA) refers to the variable distribution of functions in real time between the system and the human operator(s) to achieve optimal system performance. In the majority of complex man-machine systems, the allocation of functions between the system and operator are decided during the design process, and remain fixed for the life of the system. DFA would enable variable distribution of functions between the system and human according to operational demands and the current human and system resources available. Thus, a dynamic method of allocating functions would enable those tasks that can be performed equally well by both the human and system to be allocated to the entity (human or system) that has the resources available to best deal with the task or part of the task at that particular point in time. DFA has been proposed as a potential design option in future Naval Command and Control systems, for several reasons ( Cook et al., 1997). Future threat capabilities mean that system demands will be such that they may exceed human capabilities. Thus, the human operator may be unable to cope with such demands without some form of additional automation. Total system automation in military systems such as Naval Command and Control is unfeasible as the human operator is ultimately accountable for any decision to deploy weapons against a perceived threat. It is therefore essential that the human decision maker is maintained within the decision-making loop and provided with a cohesive set of functions which facilitate the operator's role within the total system, as well as enabling him/her to maintain a high degree of situational awareness. Theoretically DFA can achieve these system requirements. In addition, it has been proposed that DFA may also reduce the longer term adverse consequences of system over-automation such as operator deskilling and reduced job satisfaction ( Lockhart et al., 1993). Another advantage of DFA, compared to non-adaptive systems is that it offers a potential solution for optimal manning of complex systems. The UK Ministry of Defence is under increasing pressure to reduce the through life costs of future platforms, with manpower being one of the largest of these costs. Operator workload in Naval Command systems is characterised by long periods of relative inactivity or steady workload followed by bursts of intense activity. However, the requirements for such systems are that manning levels are high enough to cope with the peak demand. It seems reasonable to propose that in situations of intense workload, functions could be offloaded from the operator to the machine, so maintaining the operators workload at an optimal level that is neither too high nor too low. In this way the system could be manned by fewer operators who would not be underloaded during normal situations yet could cope with excessive task demands through the dynamic allocation of tasks to the system. CHS has been investigating whether DFA is a potential option for future Naval Command and Control systems.


The Research Environment

The research testbed is an abstraction of Force/Platform Threat Evaluation Weapon Assignment in which the subject assumes the role of force Anti-Air Warfare Co-ordinator, and is fully described in ( Cook et al. , 1997). Naval Command and Control comprises three major stages; compilation of the tactical picture; situation assessment and threat prioritisation; allocation of resources to meet the assessed threat. Automation is already being introduced to some degree in the first two stages. Thus these two stages are fully automated within the Naval Testbed. However as the human operator is ultimately accountable for the deployment of weapons it is unrealistic and unfeasible to fully automate the third stage, i.e. allocation of resources. The

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