Open AccessFunctional model of expert traffic flow control system within high-speed transportation corridors
Author(s) -
Anton Sysoev,
Elena Khabibullina
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1479/1/012084
Subject(s) - intelligent transportation system , transport engineering , traffic flow (computer networking) , advanced traffic management system , computer science , fuzzy logic , control (management) , traffic system , conceptual model , order (exchange) , sensitivity (control systems) , operations research , engineering , business , artificial intelligence , computer security , finance , database , electronic engineering
Recently, the number of vehicles on the roads has increased significantly, including within high-speed transportation corridors. Furthermore, the volume of cargo transportation increases annually not only within the country, but also between different countries. Taking into account these factors, as well as the possibility that unmanned vehicles will soon appear within high-speed transportation corridors, it is necessary to develop intelligent transportation systems that will effectively control traffic flows. Traffic flows are controlled by directional changes in its capacity. In order to interact with road users and road infrastructure, it is necessary to develop an expert system that will make recommendations using the predicted capacity value and information about the current value of the parameters describing the high-speed transport corridor. The article presents a neuro-fuzzy model for predicting capacity by known system parameters and conditions of its functioning, built using the concept of mathematical remodeling. There is also given the results of Sensitivity Analysis based on applying Analysis of Finite Fluctuations depending on external factors. In addition the conceptual and functional models of the developed expert system for regional intelligent transportation system module are proposed.