A Task Modeling Method of Intelligent Human–Computer Interaction in Aircraft Cockpits Based on Information Load Flow

Abstract

Defining how tasks should be performed is an essential prerequisite for designing the next-generation aircraft cockpits with multimodal intelligent human–computer interaction (HCI) modes. To this end, a task modeling method based on information load flow is proposed in this article, namely weighted social network analysis (WSNA). In the WSNA method, the node relation complexity in a weighted social network is quantified based on entropy, and composite matrices are established to describe the association frequency and strength between linked nodes. The performance evaluation indicators are proposed to measure the quality of weighted social networks on node centrality, node strength, network density, and network robustness, which contributes to identify the overload nodes and edges. The transformation rules from traditional modes to intelligent modes are also created as guidelines for application. A case study set in an HCI scenario during the approach phase is given for illustration. The information load and overall performance are compared in these two task modes. The results verify the feasibility of WSNA and thereby provide a solution to planning the HCI tasks in next-generation aircraft cockpits.