Dynamic and stochastic shortest path in transportation networks with two components of travel time uncertainty

Parichart Pattanamekar, Dongjoo Park, Laurence R. Rilett, Jeomho Lee, Choulki Lee

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

The existing dynamic and stochastic shortest path problem (DSSPP) algorithms assume that the mean and variance of link travel time (or other specific random variable such as cost) are available. When they are used with observed data from previous time periods, this assumption is reasonable. However, when they are applied using forecast data for future time periods, which happens in the context of ATIS, the travel time uncertainty needs to be taken into account. There are two components of travel time uncertainty and these are the individual travel time variance and the mean travel time forecasting error. The objectives of this study are to examine the characteristics of two components of travel time uncertainty, to develop mathematical models for determining the mean and variance of the forecast individual travel time in future time periods in the context of ATIS, and to validate the proposed models. First, this study examines the characteristics of the two components of uncertainty of the individual travel time forecasts for future time periods and then develops mathematical models for estimating the mean and variance of individual route travel time forecasts for future time periods. The proposed models are then implemented and the results are evaluated using the travel time data from a test bed located in Houston, Texas. The results show that the proposed DSSPP algorithms can be applied for both travel time estimation and travel time forecasting.

Original languageEnglish (US)
Pages (from-to)331-354
Number of pages24
JournalTransportation Research Part C: Emerging Technologies
Volume11
Issue number5
DOIs
StatePublished - Oct 2003

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Travel time
travel
uncertainty
time
Uncertainty
Shortest path
Transportation networks
Mathematical models
Random variables

Keywords

  • Advanced traveler information system
  • Dynamic and stochastic network
  • Route guidance system
  • Shortest path problem
  • Travel time estimation and forecasting
  • Travel time uncertainty

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications

Cite this

Dynamic and stochastic shortest path in transportation networks with two components of travel time uncertainty. / Pattanamekar, Parichart; Park, Dongjoo; Rilett, Laurence R.; Lee, Jeomho; Lee, Choulki.

In: Transportation Research Part C: Emerging Technologies, Vol. 11, No. 5, 10.2003, p. 331-354.

Research output: Contribution to journalArticle

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