A Bayesian approach for modeling origin-destination matrices

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel census studies, in contrast, covers the entire population of a specific study area of interest. In such cases where reliable historical data exist, statistical methodology may serve as a flexible alternative to traditional travel demand models by incorporating estimation of trip-generation, trip-attraction and trip-distribution in one model. In this research, a statistical Bayesian approach on OD matrix estimation is presented, where modeling of OD flows derived from census data, is related only to a set of general explanatory variables. A Poisson and a negative binomial model are formulated in detail, while emphasis is placed on the hierarchical Poisson-gamma structure of the latter. Problems related to the absence of closed-form expressions are bypassed with the use of a Markov Chain Monte Carlo method known as the Metropolis-Hastings algorithm. The methodology is tested on a realistic application area concerning the Belgian region of Flanders on the level of municipalities. Model comparison indicates that negative binomial likelihood is a more suitable distributional assumption than Poisson likelihood, due to the great degree of overdispersion present in OD flows. Finally, several predictive goodness-of-fit tests on the negative binomial model suggest a good overall fit to the data. In general, Bayesian methodology reduces the overall uncertainty of the estimates by delivering posterior distributions for the parameters of scientific interest as well as predictive distributions for future OD flows.

• Record URL:
  http://www.sciencedirect.com/science/article/pii/S096585641100098X
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Perrakis, Konstantinos
  • Karlis, Dimitris
  • Cools, Mario
  • Janssens, Davy
  • Vanhoof, Koen
  • Wets, Geert
• Publication Date: 2012-1

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 200-212
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 46
  • Issue Number: 1
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Alternatives analysis; Bayes' theorem; Census; Field tests; Markov chains; Mathematical prediction; Matrices (Mathematics); Monte Carlo method; Origin and destination; Poisson distributions; Traffic data; Traffic estimation; Traffic models; Travel demand; Travel surveys; Trip distribution; Trip generation
• Uncontrolled Terms: Trip attraction
• Geographic Terms: Flanders (Belgium)
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01359067
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Dec 16 2011 2:48PM