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

Shoufeng Lu, Victor L. Knoop, Mehdi Keyvan-Ekbatani

Research output: Contribution to journalConference articleScientificpeer-review

6 Citations (Scopus)
15 Downloads (Pure)

Abstract

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 GPS data has 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, we 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.
Original languageEnglish
Pages (from-to)243-250
Number of pages8
JournalTransportation Research Procedia
Volume34
DOIs
Publication statusPublished - 1 Jan 2018
Event6th International Symposium of Transport Simulation, ISTS 2018 and the 5th International Workshop on Traffic Data Collection and its Standardization, IWTDCS 2018 - Matsuyama, Japan
Duration: 6 Aug 20188 Aug 2018

Keywords

  • macroscopic fundamental diagrams
  • parameter calibration
  • taxi GPS data
  • two-fluid model

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