Estimating link travel time correlation: An application of Bayesian smoothing splines

Byron J. Gajewski, Laurence R. Rilett

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

The estimation and forecasting of travel times has become an increasingly important topic as Advanced Traveler Information Systems (ATIS) have moved from conceptualization to deployment. This paper focuses on an important, but often neglected, component of ATIS - the estimation of link travel time correlation. Natural cubic splines are used to model the mean link travel time. Subsequently, a Bayesian-based methodology is developed for estimating the posterior distribution of the correlation of travel times between links along a corridor. The approach is illustrated on a corridor in Houston, Texas, that is instrumented with an Automatic Vehicle Identification system.

Original languageEnglish (US)
Pages (from-to)53-70
Number of pages18
JournalJournal of Transportation and Statistics
Volume7
Issue number2-3
StatePublished - Jan 1 2005

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Keywords

  • Automatic vehicle identification
  • Gibbs Sampler
  • Intelligent transportation systems
  • Markov Chain Monte Carlo

ASJC Scopus subject areas

  • Statistics and Probability
  • Transportation

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