A Generalized Framework for Human-Machine Function Allocation

Abstract

Human-machine function allocation is the process of determining how a system functions or tasks are distributed between humans and machines. Reasonable human-machine function allocation is a key factor in ensuring system safety and performance. Considering the deficiency of existing methods of human-machine function allocation, this paper proposes a generalized framework for human-machine function allocation covering the static and dynamic function allocation phases. The functional units formed by task decomposition engage in the framework as input. The function allocation solution space is first established based on the consideration of strengths and weaknesses of humans and machines and the task requirements to their capabilities. Then feasible solution space is formed in response to situational factors to implement a flexible human-machine function allocation, so as to provide more possibilities for timely and effective response to various possible safety problems. Finally, optimal solution is determined by comprehensive evaluation with trade-off criteria and relative suitability rules of humans and machines to realize safer and more efficient human-machine collaboration. In addition, the limitation and preference rules in terms of human and machine capabilities, situational feasibility rules established with situational triggering indicators, a comprehensive evaluation with trade-off criteria and relative suitability rules of humans and machines are summarized to illustrate the application of the framework.

Keywords: Human-Machine Interaction, Human-Machine Collaboration, Function Allocation, Generalized Framework

DOI: 10.54941/ahfe1004860