This research is based on scheduling theory in practical use with neural network controller training to control intelligent electric transport system. On neural network based intelligent electronic units for DC drive control give possibility to analyze input data and generate signals without human factor. Dc drives are widely used in public transport, such as trams, trolleys and electric trains. Modeling of such system in virtual laboratory give possibility to avoid creating a physical model, replacing it by DC drive model and neural network controller with all real electric object properties. Neural network controller may be used as for control as for forecasting and warning about dangerous situation. Simulink environment may be used for modeling electric part of public transport in virtual laboratory. Over the research developing programs in Matlab environment may be used for neural network training and for adjusting schedule for public transport.