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Communication Dans Un Congrès Année : 2020

Calibrating MFD Models from Mobile Phone Data

Résumé

This work focuses on the estimation ofMacroscopic Fundamental Diagram (MFD) and trip lengths for the city scale network using mobile phone data for the city of Dallas. The data used in the present work has different sampling intervals and in order to have an accurate estimation of travelled distance, a trip enhancement method is proposed based on map-matching scheme. Data from peak hour OD matrix and loop-detectors are fused together to obtain a typical full day OD matrix of Dallas city. Using the enhanced trip set and OD matrix data, penetration rates that depend on OD pair and time are estimated. The macroscopic variables computed from the data are expanded using the penetration rates. Finally, MFDs and trip lengths are estimated for the partitioned net work. An analysis on the trip lengths is presented to demonstrate the differences in trip length distributions that depend on the OD pair and macro-path.
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Dates et versions

hal-02493342 , version 1 (19-04-2021)

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  • HAL Id : hal-02493342 , version 1

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Mahendra Paipuri, Yanyan Xu, Marta C Gonzalez, Ludovic Leclercq. Calibrating MFD Models from Mobile Phone Data. TRB 2020, 99th Annual Meeting Transportation Research Board, Jan 2020, Washington, United States. 2p. ⟨hal-02493342⟩
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