Exploring spatio-temporal features for traffic estimation on road networks

Ling Y. Wei*, Wen-Chih Peng, Chun Shuo Lin, Chen H. Jung

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In this paper, given a query that indicates a query road segment and a query time, we intend to accurately estimate the traffic status (i.e., the driving speed) on the query road segment at the query time from traffic databases. Note that a traffic behavior in the same time usually reflects similar patterns (referring to the temporal feature), and nearby road segments have the similar traffic behaviors (referring to the spatial feature). By exploring the temporal and spatial features, more GPS data points are retrieved. In light of these GPS data retrieved, we exploit the weighted moving average approach to estimate traffic status on road networks. Experimental results show the effectiveness of our proposed algorithm.

Original languageEnglish
Title of host publicationAdvances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings
Pages399-404
Number of pages6
DOIs
StatePublished - 2 Nov 2009
Event11th International Symposium on Spatial and Temporal Databases, SSTD 2009 - Aalborg, Denmark
Duration: 8 Jul 200910 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5644 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Symposium on Spatial and Temporal Databases, SSTD 2009
CountryDenmark
CityAalborg
Period8/07/0910/07/09

Keywords

  • Data Mining
  • Traffic Patterns
  • Trajectory Data

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