Highlights Estimation of all parameters required for MFD-based simulation using large scale mobile phone data. Estimation of time dependent OD-specific and origin-specific penetration rates. Proposal of well-defined correlation between the detour ratio and the mean speeds. Empirical estimation of path-flow coeffcients and UE gaps.

    Abstract The present work proposes a global framework to estimate all MFD model parameters using mobile phone data. The three major components that are estimated in the present context are MFD shapes, regional trip lengths and path flow distribution. A trip enrichment scheme based on the map matching process is proposed for the trips that have sparser records. Time dependent penetration rates are estimated by fusing the OD matrix and the Loop Detector Data (LDD). Two different types of penetration rates of vehicles are proposed based on the OD flow and the trips starting within an origin, respectively. The estimated MFDs based on two types of penetration rates are stable with very low scatter. In the following step, macro-paths and their corresponding trip lengths are estimated. This work is the first to present empirical evidences of the dynamic evolution of mean trip lengths over the day, which is very difficult to capture with other types of data sources. The last component is the time dependent path flow distributions between the different macro-paths for a given OD pair. The manuscript is concluded by presenting the time evolution of the User Equilibrium (UE) gap for different macroscopic OD pairs. It is noticed that UE principle holds true most of the time, except for OD pairs that have macro-paths transversing through congested reservoirs, especially during peak hours.


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    Titel :

    Estimating MFDs, trip lengths and path flow distributions in a multi-region setting using mobile phone data


    Beteiligte:


    Erscheinungsdatum :

    2020-06-23




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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