Naslov
Travel Time Estimation Results with Supervised Non- parametric Machine Learning Algorithms

Autori
Ćavar, Ivana ; Kavran, Zvonko ; Rapajič, Ruđer Michael

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
DATA ANALYTICS 2012 / Sandjai Bhulai, VU University Amsterdam, The Netherlands Joseph Zernik, Human Rights Alert (NGO), USA Petre Dini, Concordia University, Canada / China Space Agency Center, China - Barcelona : International Academy, Research, and Industry Association (IARIA), 2012, 49-56

ISBN
978-1-61208-242-4

Skup
DATA ANALYTICS 2012

Mjesto i datum
Barcelona, Španjolska, 23.09.2012. - 28.09.2012

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
GPS vehicle track; travel time estimation; k-nearest neighbours; iterative regression model; urban traffic

Sažetak
Paper describes urban travel time estimation procedure based on non-parametric machine learning algorithms and three data sources (GPS vehicle tracks, meteorological data and road infrastructure data base). After data fusion and dimensionality reduction, new road classification is defined and for four different time intervals and five different road categories travel time estimation is conducted. For travel time estimation, k nearest neighbors (kNN) and IRM- based (Iterative Regression Method) approaches were applied. Best results for two hour forecasting period are achieved for road class with highest traffic flow.

Izvorni jezik
Engleski

Znanstvena područja
Tehnologija prometa i transport

POVEZANOST RADA