In:
Современные тенденции инновационного развития науки и образования в глобальном мире, inScience LLC, Vol. 1, No. 1 ( 2023-03-13), p. 282-287
Abstract:
As with many other fields where the involvement of intelligent systems with the help of Artificial Intelligence is prevalent, transportation system cannot be ignored when it comes to incorporating AI and automation in order to improve the current transportation system by using new advanced technologies. There have been a lot of new tech nologies have been implemented in transportation systems especially in public transportation, making it convenient to use for commuters and other users. Having said that, de spite the fact that new technologies have been used to tackle some of the existing issues,there are some problems that are still persisting. For instance, traffc jams can be seen even in developed cities around the world, making specialists think deeply and push the boundaries of technology to come up with innovative solutions to cure existing hurdles in transportation. In terms of easing the heavy traffc flow, intelligent traffc lights powered with AI have their own role to play and huge progress can be seen in this area of research.Some of the technologies that are used in smart traffc lights are induction loops, microwave radar, and video detection. What has been done in this work is quite different from previous technologies and methods and proposes a new methodology to be used in traffic lights and with help of this method, traffc jams can be reduced significantly. Precisely, an algorithm based on a convolutional neural network is used to detect vehicles, and depending on the traffc density determined by live video footage, traffc lights make a smart decision about which road should be opened more while other another road should be closed for less time. From the environmental and economic perspective, this technology with the proposed methodology reduces greatly gasoline use by cars, thus reducing carbon dioxide emissions and saving the time passengers waste when stuck in traffc jams.
Type of Medium:
Online Resource
ISSN:
2250-3811
DOI:
10.47689/STARS.university-pp282-287
Language:
Unknown
Publisher:
inScience LLC
Publication Date:
2023
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