Short-term travel time estimation and prediction for long freeway corridor using NN and regression

Jin-Yuan Wang, Ka-Io Wong*, Y. Y. Chen

*Corresponding author for this work

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

8 Scopus citations

Abstract

Travel time information is a fundamental component in Advanced Traveler Information System. In this paper, we propose a short-term travel time estimation and prediction framework for long freeway corridor, considering measurements from vehicle detectors (VD) and floating car data (FCD). The modeling approach is based on a modified Nearest-Neighborhood (NN) model with threshold and a regression model capturing the within day variations. The advantages are that our approach allows for missing data without the need of data imputation in real-time, and is suitable for travel time prediction of long corridors. The validation analysis using an 88 km long section of freeway shows satisfactory results.

Original languageEnglish
Title of host publication2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
Pages582-587
Number of pages6
DOIs
StatePublished - 21 Dec 2012
Event2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012 - Anchorage, AK, United States
Duration: 16 Sep 201219 Sep 2012

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Conference

Conference2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
CountryUnited States
CityAnchorage, AK
Period16/09/1219/09/12

Keywords

  • Advanced Traveler Information System
  • Nearest Neighborhood
  • floating car data
  • travel time
  • vehicle detector

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