МОДЕЛИРОВАНИЕ ОТКАЗОВ ИНСТРУМЕНТАЛЬНОЙ ПОДСИСТЕМЫ И ПРИДОРОЖНОЙ ИНФРАСТРУКТУРЫ СВЯЗИ ИНТЕЛЛЕКТУАЛЬНЫХ ТРАНСПОРТНЫХ СИСТЕМ НА ОСНОВЕ ОНТОЛОГИИ
Authors: Гребешков А.Ю. 
Published: February 2025

В настоящее время активно внедряются интеллектуальные транспортные системы, поэтому тяжесть последствий их отказов существенно увеличивается. Целью работы является повышение эффективности управления последствиями отказов интеллектуальных транспортных систем на основе онтологического подхода, который применяется для идентификации и классификации источников сообщений об отказах инструментальной подсистемы. Это необходимо для создания единого семантического пространства, позволяющего достаточно точно описать сведения о выходе из строя подсистем интеллектуальных транспортных систем. Методологически создаётся онтологическая модель предметной области отказов подсистем, чтобы впоследствии использовать полученную модель для оценок текущего состояния и прогнозов с помощью методов машинного обучения.
Introduction. Currently, intelligent transport systems (ITS) are being actively employed, so the damage from their failures increases significantly. To improve the efficiency of management of intelligent transport systems, taking into account their failures, it is crucial to evolve from management systems based on rules to management systems based on knowledge. This allows one to use state-of-the-art methods of proactive or predictive management. At the same time, various sources of data on the state of ITS elements are used. Thus, introducing proactive management technologies requires creation of an information architecture that allows structuring, linking and integrating data on the state of heterogeneous elements of the ITS at a content-related level. The aim of the work was to increase the efficiency of management based on ontological modeling, by solving the problem of identification and classification of sources of information on failures of the instrumental subsystem of the ITS. This will support the creation of a unified semantic space that allows one to accurately describe information about the failure of ITS subsystems by formalizing the definition of all used concepts and links between these concepts. In terms of methodology, an ontological model of the domain of failures of ITS subsystems was created in order to subsequently use the model for estimating the current state and anticipating with the use of machine learning methods. The ontological model allows one to describe the relationship between the elements and subsystems of ITS, regardless of the types of network elements and other devices. As a result, it allows to form a single semantic space of information sources of messages about failures, where each source can be uniquely identified and described. Furthemore, axioms and rules that can be used to describe a fault tree and determine the source of a fault message were proposed. In conclusion, there is proposed a generalized scheme for the combined application of machine learning methods and the proposed failure model to move to predictive management of the consequences of failures. This will allow to carry out preventive maintenance and repairing of equipment until its failure, which will increase the total reliability of the ITS.