Short-term travel speed prediction models in car navigation systems

Seungjae Lee, Young Ihn Lee, Bumcheol Cho

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The objective of this study is the development of the short-term prediction models to predict average spot speeds of the subject location in the short-term periods of 5, 10 and 15 minutes respectively. In this study, field data were used to see the comparison of the predictability of Regression Analysis, ARIMA, Kalman Filtering and Neural Network models. These field data were collected from image processing detectors at the urban expressway for 17 hours including both peak and non-peak hours. Most of the results were reliable, but the results of models using Kalman Filtering and Neural Networks are more accurate and realistic than those of the others.

Original languageEnglish
Pages (from-to)122-139
Number of pages18
JournalJournal of Advanced Transportation
Volume40
Issue number2
DOIs
StatePublished - 2006

Fingerprint

Dive into the research topics of 'Short-term travel speed prediction models in car navigation systems'. Together they form a unique fingerprint.

Cite this