Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

Machine Learning in Urban Traffic Control (CROSBI ID 709912)

Prilog sa skupa u zborniku | prošireni sažetak izlaganja sa skupa | međunarodna recenzija

Ivanjko, Edouard ; Gregurić, Martin ; Čakija, Dino ; Kušić, Krešimir ; Miletić, Miletić ; Vrbanić, Filip Machine Learning in Urban Traffic Control // Fifth International Workshop on Data Science. 2020. str. 51-54

Podaci o odgovornosti

Ivanjko, Edouard ; Gregurić, Martin ; Čakija, Dino ; Kušić, Krešimir ; Miletić, Miletić ; Vrbanić, Filip

engleski

Machine Learning in Urban Traffic Control

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.

Intelligent Transport Systems ; Traffic Signal Control ; Machine Learning ; Reinforcement Learning ; Connected and Automated Vehicles ; Variable Speed Limit

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o prilogu

51-54.

2020.

objavljeno

Podaci o matičnoj publikaciji

Fifth International Workshop on Data Science

Podaci o skupu

5th International Workshop on Data Science (IWDS 2020)

poster

24.11.2020-24.11.2020

Zagreb, Hrvatska

Povezanost rada

Tehnologija prometa i transport