The Allocation of Maintenance Workforce in a Dynamic Human-Automation Interaction System

In this paper, we addressed the issue of maintenance workforce allocation (WA) for a human-automation interaction (HAI) in dynamic situations. We performed in parallel a traditional method for workload analysis and a mental workload assessment for the workforce in the Control and Maintenance Center (CMC) of a driverless metro. A triangulation among data and results has allowed us to confirm the impact of mental effort on the workload and it has even uncovered the role played by objective dimensions. Findings suggest some organizational decisions mostly impacting on WA.