Analysis of approaches to constructing ontological models in assessing the quality of service of autonomous robotic vehicles

The problem of formalizing the subject area of quality of technical maintenance of vehicles through the development of ontological models is considered. The need for an integrated approach to assessing the quality of service, taking into account the relationships between fi nancial, operational, technical and logistical aspects is emphasized. The main goal of the work is to propose a structured ontological model capable of automating the processes of data analysis, failure prediction and decision-making in the context of servicing autonomous vehicles. Three approaches are analyzed using the example of modeling a truck: hierarchy of classes with instances, multiple inheritance of classes, decomposition into specialized classes. The third approach is recognized as the most effective due to its detailing, scalability and automation. At the same time, a clear separation of models, instances and templates eliminates ambiguities, adding new classes does not require restructuring the existing structure, and support for logical inference allows the model to be used in decision support systems. The prospects for using this approach include integration with IoT sensors for real-time monitoring of an autonomous vehicle and the use of machine learning to predict failures based on ontological data. The article is valuable for specialists in the fi eld of logistics, IT infrastructure and engineers involved in the development of fl eet management systems.