Effect of the Choice of Stagnation Density in Data-Fitted First- and Second-Order Traffic Models

For a class of data-fitted macroscopic traffic models, the influence of the choice of the stagnation density on the model accuracy is investigated. This work builds on an established framework of data-fitted first-order Lighthill-Whitham-Richards (LWR) models and their second-order Aw-Rascle-Zhang (ARZ) generalizations. These models are systematically fitted to historic fundamental diagram data, and then their predictive accuracy is quantified via a version of the three-detector problem test, considering vehicle trajectory data and single-loop sensor data. The key outcome of this study is that with commonly suggested stagnation densities of 120 vehicles/km/lane and above, information travels backwards too slowly. It is then demonstrated that the reduction of the stagnation density to 90-100 vehicles/km/lane addresses this problem and results in a significant improvement of the predictive accuracy of the considered models.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AHB45 Traffic Flow Theory and Characteristics.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Fan, Shimao
  • Seibold, Benjamin
• Conference:
  • Transportation Research Board 93rd Annual Meeting
  • Location: Washington DC
  • Date: 2014-1-12 to 2014-1-16
• Date: 2014

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 18p
• Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Accuracy; Traffic data; Traffic density; Traffic flow theory; Traffic models
• Uncontrolled Terms: Fundamental diagram
• Subject Areas: Highways; Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 01520189
• Record Type: Publication
• Report/Paper Numbers: 14-5083
• Files: TRIS, TRB, ATRI
• Created Date: Mar 26 2014 11:27AM