Deriving the Probability Density Function of Travel Time Under Capacity Uncertainty

In this paper the authors present a novel methodology to assess travel time reliability in a transportation network, when the source of uncertainty is given by uncertain road capacities. Specifically, the authors present a method based on the theory of Fourier transforms to numerically approximate the probability density function of the system-wide travel time. Except for noted pathological cases, any common continuous or discrete probability distribution can be used to model capacity uncertainty. Theoretical bounds on the approximation errors are formally derived. These bounds provide valuable insights into the structure of the approximation errors and suggest ways to reduce them. From a practical point of view, the authors propose a procedure based on successively refining the computational grid in order to guarantee accurate approximations. The proposed methodology takes advantage of the established computational efficiency of the fast Fourier transform. In a numerical case study, the authors demonstrate that the results of the methodology are consistent with intuition.


  • English

Media Info

  • Media Type: DVD
  • Features: Figures; References; Tables;
  • Pagination: 16p
  • Monograph Title: TRB 89th Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01155411
  • Record Type: Publication
  • Report/Paper Numbers: 10-1127
  • Files: TRIS, TRB
  • Created Date: Jan 25 2010 10:30AM