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Empirical Study on Discrete Modeling of Urban Intersection Management System

Empirical Study on Discrete Modeling of Urban Intersection Management System

Sergey Chuprov, Ilia Viksnin, Iuliia Kim, Nikita Tursukov, Gleb Nedosekin
Copyright: © 2020 |Volume: 11 |Issue: 2 |Pages: 23
ISSN: 1947-3176|EISSN: 1947-3184|EISBN13: 9781799807001|DOI: 10.4018/IJERTCS.2020040102
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MLA

Chuprov, Sergey, et al. "Empirical Study on Discrete Modeling of Urban Intersection Management System." IJERTCS vol.11, no.2 2020: pp.16-38. http://doi.org/10.4018/IJERTCS.2020040102

APA

Chuprov, S., Viksnin, I., Kim, I., Tursukov, N., & Nedosekin, G. (2020). Empirical Study on Discrete Modeling of Urban Intersection Management System. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 11(2), 16-38. http://doi.org/10.4018/IJERTCS.2020040102

Chicago

Chuprov, Sergey, et al. "Empirical Study on Discrete Modeling of Urban Intersection Management System," International Journal of Embedded and Real-Time Communication Systems (IJERTCS) 11, no.2: 16-38. http://doi.org/10.4018/IJERTCS.2020040102

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Abstract

With the growing number of cars in the world, there are corresponding problems that society needs to solve. In metropolises, intersections are generators of traffic jams and traffic accidents. The introduction of unmanned autonomous vehicles is one of the solutions to increase safety on the road. To avoid traffic jams, it is necessary to optimize road traffic. This article proposes a model of the intersection management system. The system aims to organize a conflict-free, safe, and optimal traversal of AVs within the framework of the intelligent transport system of a smart city. The model assumes that at each intersection there are objects of transport infrastructure responsible for building routes at the intersection. To assess the feasibility of the presented model, the authors developed a custom software simulator of a network of urban intersections and conducted experiments. Based on simulation experiments, the use of the developed model can significantly reduce the time spent by unmanned vehicles to overcome the intersection compared to traffic lights.

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