Traffic velocity prediction using GPS data: IEEE ICDM Contest task 3 report

Wei Shen, Yiannis Kamarianakis, Laura Wynter, Jingrui He, Qing He, Rick Lawrence, Grzegorz Swirszcz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

This report summarizes the methodologies and techniques we developed and applied for tackling task 3 of the IEEE ICDM Contest on predicting traffic velocity based on GPS data. The major components of our solution include 1) A pre-processing procedure to map GPS data to the network, 2) A K-nearest neighbor approach for identifying the most similar training hours for every test hour, and 3) A heuristic evaluation framework for optimizing parameters and avoiding over-fitting. Our solution finished Second in the final evaluation.

Original languageEnglish (US)
Title of host publicationProceedings - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
Pages1369-1371
Number of pages3
DOIs
StatePublished - 2010
Event10th IEEE International Conference on Data Mining Workshops, ICDMW 2010 - Sydney, NSW, Australia
Duration: Dec 14 2010Dec 17 2010

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
Country/TerritoryAustralia
CitySydney, NSW
Period12/14/1012/17/10

Keywords

  • Cross validation
  • Map-matching
  • Nearest neighbor

ASJC Scopus subject areas

  • Engineering(all)

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