An Analytical Approximation of the Joint Distribution of Aggregate Queue-Lengths in an Urban Network

Traditional queuing network models assume infinite queue capacities due to the complexity of capturing interactions between finite capacity queues. Accounting for this correlation can help explain how congestion propagates through a network. Joint queue-length distribution can be accurately estimated through simulation. Nonetheless, simulation is a computationally intensive technique, and its use for optimization purposes is challenging. By modeling the system analytically, it loses accuracy but gains efficiency and adaptability and can contribute novel information to a variety of congestion related problems, such as traffic signal optimization. An analytical technique is formulated that combines queuing theory with aggregation-disaggregation techniques in order to approximate the joint network distribution, considering an aggregate description of the network. A stationary formulation is proposed and a tandem network with three queues is considered. The model is validated by comparing the aggregate joint distribution of the three queue system with the exact results determined by a simulation over several scenarios. It derives a good approximation of aggregate joint distributions.

• Record URL:
  https://doi.org/10.1016/j.sbspro.2012.09.807
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1877042812042693
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/18770428
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Osorio, Carolina
  • Wang, Carter
• Conference:
  • 15th Meeting of the EURO Working Group on Transportation
  • Location: Paris , France
  • Date: 2012-9-10 to 2012-9-13
• Publication Date: 2012-10-4

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 917-925
• Serial:
  • Procedia - Social and Behavioral Sciences
  • Volume: 54
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1877-0428
  • Serial URL: http://www.sciencedirect.com/science/journal/18770428/53
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Cluster analysis; Disaggregate analysis; Optimization; Queuing theory; Traffic congestion; Traffic queuing; Traffic simulation
• Subject Areas: Highways; Planning and Forecasting; I71: Traffic Theory;

Filing Info

• Accession Number: 01488317
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 3 2013 1:36PM