title: ÐÐ½Ð°Ð»Ð¸Ð· Ð¸ ÑÐ»ÑÑÑÐµÐ½Ð¸Ðµ Ð¾ÑÐ³Ð°Ð½Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÑÐ°ÑÐ¸ÐºÐ° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Analysis and improvement of traffic organization using artificial neural networks
Creators: name: Ð¡Ð»ÑÑÐ°ÑÐµÐ², ÐÐ½ÑÐ¾Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐ¸
ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð´Ð¾ÑÐ¾Ð¶Ð½ÑÐ¼ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸ÐµÐ¼
ÑÐ²ÐµÑÐ¾ÑÐ¾ÑÑ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼
neural networks
road traffic management
traffic lights
reinforcement learning

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ½Ð°Ð»Ð¸Ð· Ð¸ ÑÐ»ÑÑÑÐµÐ½Ð¸Ðµ Ð¾ÑÐ³Ð°Ð½Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÑÐ°ÑÐ¸ÐºÐ° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹Â».
Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÐµÑÑÑ Ð²Ð¾Ð¿ÑÐ¾Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ¼Ð½ÑÑ ÑÐ²ÐµÑÐ¾ÑÐ¾ÑÐ¾Ð², Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ñ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ ÑÐµÐ³ÑÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð¾ÑÐ¾Ð¶Ð½Ð¾Ð³Ð¾ ÑÑÐ°ÑÐ¸ÐºÐ°.
Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ: ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ ÑÐ²ÐµÑÐ¾ÑÐ¾ÑÐ°Ð¼Ð¸.
Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð±Ð¾ÑÑ: ÑÐ°Ð±Ð¾ÑÐ° Ð±ÑÐ»Ð° Ð¿Ð¾Ð´ÐµÐ»ÐµÐ½Ð° Ð½Ð° Ð´Ð²Ð° Ð±Ð¾Ð»ÑÑÐ¸Ñ ÑÑÐ°Ð¿Ð°. ÐÐ° Ð¿ÐµÑÐ²Ð¾Ð¼, Â«Ð»Ð¾ÐºÐ°Ð»ÑÐ½Ð¾Ð¼Â», ÑÑÐ°Ð¿Ðµ Ð±ÑÐ»Ð° ÑÐ¾Ð·Ð´Ð°Ð½Ð° Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ Ð´Ð»Ñ Ð¾Ð´Ð½Ð¾Ð³Ð¾ ÑÐ²ÐµÑÐ¾ÑÐ¾ÑÐ°, ÐºÐ¾Ð½ÑÑÐ¾Ð»Ð¸ÑÑÑÑÐµÐ³Ð¾ ÑÐ¾Ð»ÑÐºÐ¾ Ð¾Ð´Ð¸Ð½ Ð¿ÐµÑÐµÐºÑÐµÑÑÐ¾Ðº. ÐÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ Ð¾Ð±ÑÑÐ¸Ð»Ð°ÑÑ Ð¸ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð¼ ÑÑÐ°Ð¿Ð° ÑÑÐ°Ð»Ð¾ ÑÐ½Ð¸Ð¶ÐµÐ½Ð¸Ðµ Ð²ÑÐµÐ¼ÐµÐ½Ð¸ Ð¿ÑÐ¾ÑÑÐ¾Ñ Ð½Ð° 37% Ð¿Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ ÑÐ¾ ÑÑÐ°Ð½Ð´Ð°ÑÑÐ½ÑÐ¼ ÑÐ²ÐµÑÐ¾ÑÐ¾ÑÐ¾Ð¼ Ñ ÑÐ¸ÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐ¼ Ð²ÑÐµÐ¼ÐµÐ½ÐµÐ¼ ÑÐ¼ÐµÐ½Ñ ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð². ÐÑÐ¾ÑÐ¾Ð¹ ÑÑÐ°Ð¿ Ð·Ð°ÐºÐ»ÑÑÐ°Ð»ÑÑ Ð² ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ð¸ Ð¿Ð¾Ð»Ð½Ð¾ÑÐµÐ½Ð½Ð¾Ð¹ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð¹ ÑÐµÑÐ¸. ÐÐ° Ð²ÑÐ¾ÑÐ¾Ð¼ ÑÑÐ°Ð¿Ðµ ÑÐ°Ð±Ð¾ÑÑ ÑÐ¼Ð½ÑÐµ ÑÐ²ÐµÑÐ¾ÑÐ¾ÑÑ (ÑÐ¾Ð·Ð´Ð°Ð½Ð½ÑÐµ Ð½Ð° Ð¿ÐµÑÐ²Ð¾Ð¼ ÑÑÐ°Ð¿Ðµ) Ð±ÑÐ»Ð¸ Ð¾Ð±ÑÐµÐ´Ð¸Ð½ÐµÐ½Ñ Ð² ÐµÐ´Ð¸Ð½ÑÑ ÑÐµÑÑ. Ð ÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð° Ð¾Ð±ÑÐµÐµ ÑÐ»ÑÑÑÐµÐ½Ð¸Ðµ ÑÐ¾ÑÑÐ¾ÑÐ½Ð¸Ñ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð¹ ÑÐµÑÐ¸. ÐÑÐ¸ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð¸Ð¸ 6-Ð¸ ÑÐ°ÑÐ¾Ð²Ð¾Ð³Ð¾ Ð¿ÐµÑÐ¸Ð¾Ð´Ð° ÑÑÐµÐ´Ð½ÑÑ Ð·Ð°Ð´ÐµÑÐ¶ÐºÐ° ÐºÐ°Ð¶Ð´Ð¾Ð³Ð¾ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð³Ð¾ ÑÑÐµÐ´ÑÑÐ²Ð° Ð±ÑÐ»Ð° ÑÐ½Ð¸Ð¶ÐµÐ½Ð° Ð½Ð° 26%, Ð° ÑÑÐµÐ´Ð½ÑÑ ÑÐºÐ¾ÑÐ¾ÑÑÑ Ð²ÑÑÐ¾ÑÐ»Ð° Ð½Ð° 19%. ÐÐ°Ðº Ð¸ÑÐ¾Ð³, Ð±ÑÐ»Ð¸ Ð´Ð¾ÑÑÐ¸Ð³Ð½ÑÑÑ Ð¼Ð½Ð¾Ð³Ð¾Ð¾Ð±ÐµÑÐ°ÑÑÐ¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ, Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑÐ¸Ðµ Ð²ÑÑÐ¾ÐºÑÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð´Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ðº ÑÐµÑÐµÐ½Ð¸Ñ Ð¿Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½Ð¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸. 
ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ: ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð¿Ð¾ÑÐ¾ÐºÐ°Ð¼Ð¸ Ð´Ð¾ÑÐ¾Ð¶Ð½Ð¾Ð³Ð¾ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ° Ð² ÑÑÐ»Ð¾Ð²Ð¸ÑÑ Ð³Ð¾ÑÐ¾Ð´ÑÐºÐ¾Ð¹ ÑÑÐµÐ´Ñ.
description: Theme of this final qualifying work is "Analysis and improvement of traffic organization using artificial neural networks."
This paper considers the issue of creating a system of smart traffic lights that use neural network technology to regulate and optimize road traffic.
The aim of the work: development of a neural network for controlling traffic lights.
The results: the work was divided into two large phases. At the first, âlocalâ, phase a neural network was created for one traffic light (that controls only one crossroad). The neural network was trained and the result of the first phase was a 37% reduction in downtime (at a crossroad) compared to a standard traffic light with a fixed signal change time. At the second phase of work, smart traffic lights (those were created at the first stage) were combined into a network. The implemented system showed an overall improvement in the state of the transport network. Considered a 6-hour period, the average delay of a vehicle was reduced by 26%, and the average speed increased by 19%. In conclusion, promising results were achieved, showing the high efficiency of this approach for solving the problem.
Scope of application: management of streams of road transport in the conditions of the urban environment.â