Intelligent traffic management system of a big city: ontology concept “decision models”

Abstract

The problem of traffic jams is still relevant for the transport system of many large cities on different continents. The work is aimed at the formation of an ontologically controlled technology, which is based on the use of available means of data production, information resources, modelling of traffic forecasting of large cities and traffic management based on these forecasts. That is why it pays great attention to the research of innovative solutions to the problem of optimizing traffic through the city network using big data, artificial intelligence models, and Internet of Things technologies. At the same time, the main aspects that require human intervention in the development of the reference ontology of the “Road Traffic” domain are defined. The scientific novelty of the work arises in the creation of the ontology concept “Decision Model”, which will later become the basis of intelligent informational technology for effective traffic management in large cities. This development is crucial for solving traffic congestion problems by intelligently distributing traffic flows through the city road network, as it unifies the knowledge representation. The attention is focused on the scheme of formation of a hybrid model of decisions, which are at various stages of execution of the control actions of the system. The task that will be solved by the artificial intelligence model is defined. The possibility of using the ant colony algorithm to find the shortest path is also shown.