The development of cognitive workload management framework based on neuronal dynamics principle to maintain train driver’s health and railway safety

Fatigue increases the tendency of poor train driving strategy decision. Decision making in cognitive overload and underload situation mostly outputs bad decisions. Accordingly, driver’s function is required to be sTable during travel so that they can give correct response at a given situation. This study constructs conceptual framework for workload management (CWM) driver by taking energy expenses from cognition into account. combines objective subjective analysis evaluate duty readiness. The load was performed through level approximation based on neuronal dynamics simulation 76 brain regions. expenditure (CEE) calculated neuron action potential (NAP) ion-membrane current (IMC) results. (CL) approximated converts continuous time-based CEE discrete frequency-based CL using Fourier series. obtained results followed 27 participants. participants fill questionnaire their simulated journey experience. evaluation used build readiness classifier control chart. chart helps determine weekly rest period daily short treatment base each workload. CWM allows different recovery applied driver. impact application performance drivers are kept stable. Thus, useful prevent physical mental fatigue