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

Authors:
Ivana Cavar
Zvonko Kavran
Ruder Michael Rapajic

Keywords: vehicle track; travel time estimation; k-nearest neighbours; iterative regression model; urban traffic

Abstract:
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.

Pages: 49 to 56

Copyright: Copyright (c) IARIA, 2012

Publication date: September 23, 2012

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-242-4

Location: Barcelona, Spain

Dates: from September 23, 2012 to September 28, 2012