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IntroductionOperational quality measures of motor vehicles are used, among the others, to evaluate the performance of transport services. An important group of problems in making such an assessment is selection of the appropriate method. The operational evaluation of an object requires defining the measures (measurements, indicators) and the determining their values. The appropriate value allocation of the vehicles performance measures is one of the key criteria for the proper functioning of the whole transport system [9]. The numerical evaluation of the efficiency of the equipment is based on the values derived from the observation of the equipment during operation [10]. The variety of operational measures depends, of course, on the type of object (process), and usually these measures have different denominations and orders of scale, making them mutually incomparably [6,11].Comparing the measures describing an object (process) is only possible after normalization. Among the groups of technical objects' features relevant for their operational evaluation (determination of their measures and indicators) were distinguished, among the others [8]:technical condition of the object, being a measure of the ability • to use the object over time, reliability in statistical terms, • quality, understood as the ability of an object to meet specific • needs, functionality describing the object in the sphere of human con-• tact, efficiency characterizing the performance of an object, • serviceability characterizing the object's suitability to be serv-ŚWIDERSKI A, JÓŹWIAK A, JACHIMOWSKI R. Operational quality measures of vehicles applied for the transport services evaluation using artificial neural networks.