The paper considers the problem of building a hybrid model of regional intelligent transportation system (ITS) controlling traffic flows within high-speed transportation corridors for unmanned and manned vehicles, which could be adopted to different regions taking into account their economic situation and geographical location. The study presents a scheme of regional ITS consisting of high-speed transportation corridors and the algorithm of access to corridors. This task is based on optimization problem consisting of searching the minimum waiting time and time of movement for all participants within the current section of the system (using ramp-metering system as a control). The stochastic nature of freeway section capacity is considered. To define the most important factors affecting capacity it was proposed the approach to Sensitivity Analysis based on applying Analysis of Finite Fluctuations. Obtained results of the proposed analysis were used to form productive rules to control variable parameters of the system. According to the results of the analysis, the structure of the expert system was determined, which makes it possible to form recommendations for connected vehicles. The neuro-fuzzy algorithm for production rules formation provides building ITS based on observed big data and with minimal expert participation (only at the stage of evaluating the quality of the knowledge base).
Hybrid Model of Controlling Traffic Flows Within Regional Intelligent Transportation System
Lect. Notes in Networks, Syst.
International Conference on Reliability and Statistics in Transportation and Communication ; 2020 ; Riga, Latvia October 14, 2020 - October 17, 2020
Reliability and Statistics in Transportation and Communication ; Kapitel : 49 ; 528-537
07.02.2021
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Hybrid model , Intelligent transportation system , Stochastic freeway capacity , Ramp-metering Engineering , Computational Intelligence , Transportation Technology and Traffic Engineering , Operations Research/Decision Theory , Communications Engineering, Networks , Data Mining and Knowledge Discovery
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