Towards a reverse world in automation: human as a sensor

Abstract

Automation is more and more shifting towards a technologic world where the human component is however still involved. The autonomous cars represent an example where the shift towards a fully automated vehicle still requires the presence of the human component, that is a human-in-the-loop, which may represent the failure or the added value of such systems. Stress and fatigue represent the main concerns in safety issues during workloads, above all, in situations where the person’s behaviour represents a potential source of harm in human–computer interaction. After a brief survey of the recent literature on the human as a sensor concept, in this paper, some examples of an electroencephalography (EEG) based brain-computer interface showing the still limited but potentially challenging effectiveness of such an approach in systems engineering. The aim is to explore brain activities when a subject is conditioned by external stimuli during the execution of a cognitive task and to evaluate the human capability to react to the unexpected event faster than a machine.Different experiment tests have been designed to evaluate the human reactions under simulated driving scenarios and workload sessions. Accordingly, different methodologies to use this information are shown. Driver’s performance has been evaluated by EEG power spectrum analysis when unpredicted acoustic stimuli or breaking emergency situations are simulated during the driving session. A Fine Gaussian Support Vector Machine (SVM) approach has been carried out to classify the human’s brain activities when the participant has to drive a car along a challenging curvilinear path in a virtual simulated scenario or when he is exposed to visual disturbances while performing a common task.The results demonstrate an interesting potential correlation between external stimuli and driver’s brain wave activities in virtual driving environment. In addition, the EEG pattern recognition in the visual external stimulus test and in the driver’s stress simulation to tackle a road with different curve angles generated promising outcomes. However, despite the wide literature on the subject, the effective use of such signal still represents a hard although challenging task.