Pregled bibliografske jedinice broj: 1155815
Machine Learning in Urban Traffic Control
Machine Learning in Urban Traffic Control // Fifth International Workshop on Data Science
Zagreb, Hrvatska, 2020. str. 51-54 (poster, međunarodna recenzija, prošireni sažetak, znanstveni)
CROSBI ID: 1155815 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Machine Learning in Urban Traffic Control
Autori
Ivanjko, Edouard ; Gregurić, Martin ; Čakija, Dino ; Kušić, Krešimir ; Miletić, Miletić ; Vrbanić, Filip
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, prošireni sažetak, znanstveni
Izvornik
Fifth International Workshop on Data Science
/ - , 2020, 51-54
Skup
5th International Workshop on Data Science (IWDS 2020)
Mjesto i datum
Zagreb, Hrvatska, 24.11.2020
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Intelligent Transport Systems ; Traffic Signal Control ; Machine Learning ; Reinforcement Learning ; Connected and Automated Vehicles ; Variable Speed Limit
Sažetak
The increase of the human population and the availability of vehicles created mega-cities with a significant need for daily mobility. The result is traffic congestion, increased pollution, and decreased life quality. Many research efforts are put into Intelligent Transport Systems (ITS) to cope with these problems. One of the ITS services is traffic control, where the availability of various data (inductive loops, traffic cameras, Bluetooth detectors, mobile phone data) is used as input to improve the Level of Service (LoS) of the urban road network.
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport
POVEZANOST RADA
Projekti:
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
Ustanove:
Fakultet prometnih znanosti, Zagreb
Profili:
Martin Gregurić
(autor)
Dino Čakija
(autor)
Edouard Ivanjko
(autor)
Filip Vrbanić
(autor)
Krešimir Kušić
(autor)