Identification of Collision Situations for Higher Efficiency of Traffic Control System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00375589" target="_blank" >RIV/68407700:21260/24:00375589 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/SCSP61506.2024.10552688" target="_blank" >http://dx.doi.org/10.1109/SCSP61506.2024.10552688</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SCSP61506.2024.10552688" target="_blank" >10.1109/SCSP61506.2024.10552688</a>
Alternative languages
Result language
angličtina
Original language name
Identification of Collision Situations for Higher Efficiency of Traffic Control System
Original language description
An integral part of modern cities within Smart City concepts is the development and related innovations in traffic control systems. New proposals need to be carried out in accordance with the applicable legislation and at the same time on a sufficient data base. This paper reflects the first conclusions of the research project SENDER, the aim of which is to develop, using deep learning methods, such a system that will warn drivers of impending danger in front of selected traffic intersections based on recognized data in the image from installed cameras. The paper mainly describes the process of selecting traffic situations in the area of intersections, which it is appropriate to warn the driver about. As part of the research, a state-of-the-art analysis was first carried out, which summarizes knowledge from current traffic control systems and the possibility of identifying collision situations, then the expert team defined collision situations that may occur in the node, including accompanying prioritization. On the basis of this identification, a specific intersection in the city of Brno was selected, which was fitted with cameras, and a test was conducted to determine whether the defined collision situations at the intersection actually occur. For the purposes of the developed system, this results in the specification of preferred collision situations, and these will then be simulated in variants with minor changes in the input parameters, in order to create a large enough database for learning the neural network.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10700 - Other natural sciences
Result continuities
Project
<a href="/en/project/CK04000027" target="_blank" >CK04000027: Traffic controll system of new generation (SENDER)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2024 Smart City Symposium Prague - IEEE PROCEEDINGS
ISBN
979-8-3503-6096-7
ISSN
2831-5618
e-ISSN
2691-3666
Number of pages
6
Pages from-to
—
Publisher name
IEEE Press
Place of publication
New York
Event location
Prague
Event date
May 23, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001258546700008