Smart technology implementation for road traffic management

Внедрение интеллектуальных технологий для управления дорожным движением
Natalia Zhuravleva, Elena Volkova, Daniil Solovyev
2020-01-01

AnyLogic modelingagent-based traffic simulationintersection congestionsmart traffic managementsmart traffic regulation
The escalation of road traffic appears to be a tremendous problem. Various metropolises are influenced by traffic flow congestion and the growth of emissions from petrol usage. In big agglomerations, the expanding quantity of private cars and public transport has caused traffic problems. They have a harmful effect on economy, ecosystem, and on the quality of life in general. It is vital to obtain smart solutions for road traffic management. In this paper, authors propose a way to solve this problem by using smart traffic regulation, which is a part of the bigger smart logistics concept. Agent-based traffic simulation has been chosen to perform this research. This type of modeling is related to the object-oriented way of coding. For modeling and experimental simulation of the intersection in St. Petersburg, AnyLogicmodeling software was used. The results show that proposed algorithm allowed to reduce the average waiting time by 37%. Moreover, the average waiting car number at the intersection has been dropped by 2.5 times after applying the new solution. Thus, projected way of reducing road overload on the selected intersection in St. Petersburg displayed excellent outcomes. However, implementation of the algorithm on other infrastructure objects requires further investigation and analysis.
1
An agent-based traffic simulation approach was used to model and experimentally evaluate an intersection in St. Petersburg using AnyLogic software.
2
Applying the algorithm decreased the average number of waiting cars at the intersection by 2.5 times.
3
The method showed strong results at the studied intersection, but its applicability to other infrastructure objects requires further investigation.
4
The proposed traffic-management algorithm reduced average vehicle waiting time at the selected intersection by 37%.
5
The study proposes smart traffic regulation within a broader smart logistics framework to address urban congestion and vehicle-emission-related impacts.

the selected road intersection in St. Petersburg and its traffic flow

the effects of smart traffic regulation on average vehicle waiting time and queue size

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2020-01-01
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Authors
Natalia Zhuravleva
Elena Volkova
Daniil Solovyev
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