A probability model and sampling algorithm for the inter-day stochastic traffic assignment problem

The authors of this study consider that inter-day traffic flow fluctuations in a network are caused by stochastic travel behavior. Route traffic flows at each time interval are treated as random variables and therefore, the solution of the stochastic assignment problem should be the conditional joint probability distribution of the route flows given that the network is in stochastic user equilibrium. The authors formulate the conditional joint distribution and develop a Gibbs sampler to draw samples from the conditional joint distribution. Characteristics of the route flows at each time interval during the time horizon can be estimated on the basis of the simulated samples.

• Record URL:
  • https://doi.org/10.1002/atr.214
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/5121625
• Authors:
  • Wei, Chong
  • Asakura, Yasuo
  • Iryo, Takamasa
• Publication Date: 2012-7

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 222-235
• Serial:
  • Journal of Advanced Transportation
  • Volume: 46
  • Issue Number: 3
  • Publisher: John Wiley & Sons, Incorporated
  • ISSN: 0197-6729
  • EISSN: 2042-3195
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Advanced traffic management systems; Bayes' theorem; Dynamic traffic assignment; Equilibrium (Systems); Stochastic processes; Time intervals; Traffic flow
• Uncontrolled Terms: Directed acyclic graphs; Gibbs sampling
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I71: Traffic Theory; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01383465
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 22 2012 3:36PM