Abstract
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).
The reported study was supported by the Russian Science Foundation within the project 18-71-10034.
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Sysoev, A., Galkin, A., Khabibullina, E. (2021). Hybrid Model of Controlling Traffic Flows Within Regional Intelligent Transportation System. In: Kabashkin, I., Yatskiv, I., Prentkovskis, O. (eds) Reliability and Statistics in Transportation and Communication. RelStat 2020. Lecture Notes in Networks and Systems, vol 195. Springer, Cham. https://doi.org/10.1007/978-3-030-68476-1_49
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DOI: https://doi.org/10.1007/978-3-030-68476-1_49
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