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EcoLight : Eco-friendly traffic signal control driven by urban noise prediction

author
Ounoughi, Chahinez
Touibi, Ghofrane
Ben Yahia, Sadok
statement of authorship
Chahinez Ounoughi, Ghofrane Touibi & Sadok Ben Yahia
source
Database and Expert Systems Applications : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022 : proceedings, Part I
location of publication
Cham
publisher
Springer
year of publication
2022
pages
p. 205–219
series
Lecture notes in computer science ; 13426
conference name, date
33rd International Conference, DEXA 2022, 22-24 August, 2022
conference location
Vienna, Austria
url
https://doi.org/10.1007/978-3-031-12423-5_16
subject term
CO2 emissioon
liiklusummikud
mootorikütused
liiklus
müra
valgusfoorid
linnaliiklus
Scopus
Conference Proceedings at Scopus
Article at Scopus
WOS
Conference Proceedings at WOS
Article at WOS
kvartiil
Q3
category (general)
Computer science
Mathematics
category (sub)
Computer science. General computer science
Mathematics. Theoretical computer science
keyword
CO2 emissions
congestion
fuel consumption
reinforcement learning
SUMO simulation
traffic signal control
urban noise
ISSN
0302-9743
ISBN
978-3-031-12422-8
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
TTÜ department
tarkvarateaduse instituut
language
inglise
Uurimisrühm
Data science group
Ounoughi, C., Touibi, G., Ben Yahia, S. EcoLight : Eco-friendly traffic signal control driven by urban noise prediction // Database and Expert Systems Applications : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022 : proceedings, Part I. Cham : Springer, 2022. p. 205–219. (Lecture notes in computer science ; 13426). https://doi.org/10.1007/978-3-031-12423-5_16