Open AccessDEVELOPMENT OF A SYSTEM FOR ANALYZING AND UNLOADING ROAD TRAFFIC USING ARTIFICIAL INTELLIGENCE
Author(s) -
Linar M. Akhmetov,
Danir I. Bikov,
Marat R. Khamidullin
Publication year - 2021
Publication title -
international journal of advanced studies
Language(s) - English
Resource type - Journals
eISSN - 2328-1391
pISSN - 2227-930X
DOI - 10.12731/2227-930x-2021-11-1-87-98
Subject(s) - intersection (aeronautics) , automotive industry , python (programming language) , artificial neural network , computer science , traffic bottleneck , track (disk drive) , scope (computer science) , transport engineering , traffic signal , floating car data , arduino , artificial intelligence , traffic optimization , simulation , engineering , real time computing , traffic congestion , embedded system , operating system , programming language , aerospace engineering
Every year the growth rate of cars in Russia will continue to grow, which will complicate the organization of road traffic. Therefore, innovations in the automotive industry, such as smart traffic lights, are needed to regulate traffic more efficiently.
Purpose – development of a system for analyzing and unloading road traffic to improve the situation at intersections, automating road traffic by introducing artificial intelligence, assembling a working model of a traffic light based on Arduino.
Method or methodology of work: the article considers a project to analyze and track and unload vehicles at an intersection.
Results: a mock-up of a traffic light based on an Arduino UNO microcontroller was assembled and a neural network was developed for analyzing and unloading road traffic in real time in Python.
Scope of the results: the results obtained should be applied to the most congested road sections.