Using taxi GPS data for macroscopic traffic monitoring in large scale urban networks: calibration and MFD derivation

A two-Fluid Model (TFM) of urban traffic provides the macroscopic description of traffic state. The TFMs parameters are hard to calibrate, particularly for the dynamic traffic conditions. This leads to the TFM often being used to compare the quality of service through the plot of stopping time versus trip time of the vehicles in the network. Recently, the taxi Global Positioning System (GPS) data have been applied to predict the traffic condition at the network level. Despite the network-wide coverage of the taxi GPS probe data, the penetration rate of taxis in the network traffic is still a vital and challenging issue for traffic estimation purpose. It is necessary to estimate penetration rate of taxis by combining with other data sources. Here, the authors propose a novel approach to fill two gaps: TFM parameter calibration and the taxis penetration rate. This method stretches the description of TFM to a zone size. The method is applied to real Changsha city GPS data, calibrating the parameters. The macroscopic fundamental diagram of the large-scale city is derived. For the Changsha case, running speed is the super-linear power law of the fraction of running cars; the fraction of stopping time is nearly linear power law of density, which can be an alternative of the density. The proposed method enables the calibration of TFM parameters and macroscopic traffic monitoring at urban scale using only GPS data.

• Record URL:
  • https://doi.org/10.1016/j.trpro.2018.11.038
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2352146518303272
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2018 Shoufeng Lu et al. Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Lu, Shoufeng
  • Knoop, Victor L
  • Keyvan-Ekbatani, Mehdi
• Conference:
  • International Symposium of Transport Simulation (ISTS’18) and the International Workshop on Traffic Data Collection and its Standardization (IWTDCS’18)
  • Location: Matsuyama , Japan
  • Date: 2018-8-6 to 2018-8-8
• Publication Date: 2018

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 243-250
• Serial:
  • Transportation Research Procedia
  • Volume: 34
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Global Positioning System; Large cities; Macroscopic traffic flow; Taxicabs; Traffic surveillance
• Uncontrolled Terms: Macroscopic fundamental diagrams; Two-fluid model
• Geographic Terms: Changsha (China)
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01689697
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 24 2018 2:56PM