Abstract Traditional approaches to trip generation modelling rely on household travel surveys which are expensive and prone to reporting errors. On the other hand, mobile phone data, where spatio-temporal trajectories of millions of users are passively recorded has recently emerged as a promising input for transport analyses. However, such data has primarily been used for the development of human mobility models, extraction of statistics on human mobility behaviour, and origin-destination matrix estimation as opposed to the development of econometric models of travel demand. This is primarily due to the exclusion of user demographics from mobile phone data made available for research (owing to privacy reasons). In this study, we address this limitation by proposing a hybrid trip generation model framework where demographic groups are treated as latent or unobserved. The proposed model first predicts the demographic group membership probabilities of individuals based on their phone usage characteristics and then uses these probabilities as weights inside a latent class model for trip generation, with different classes representing different socio-demographic groups. The model is calibrated using the call log data of a sub-sample of users with known demographics and trip rates extracted from their GSM mobility data. The performance of the hybrid model is compared with that of a traditional trip generation model which uses observed demographic variables to validate the proposed methodology. This comparative analysis shows that the model fit and the prediction results of the hybrid model are close to those of the traditional model. The research thus serves as a proof-of-concept that the mobile phone data can be successfully used to develop econometric models of transport planning by having additional information for a subset of the users.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Modelling trip generation using mobile phone data: A latent demographics approach


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2017-08-31


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Using Mobile Phone Location Data to Develop External Trip Models

    Huntsinger, Leta F. / Ward, Kyle | Transportation Research Record | 2015


    Analysis of land trip generation rates driven by mobile phone signaling data

    Liu, Jianmeng / Liu, Tao / Zhang, Dongqi et al. | British Library Conference Proceedings | 2022


    Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips

    Demissie, Merkebe Getachew / Phithakkitnukoon, Santi / Kattan, Lina | IEEE | 2019


    A Novel Trip Coverage Index for Transit Accessibility Assessment Using Mobile Phone Data

    Zhengyi Cai / Dianhai Wang / Xiqun (Michael) Chen | DOAJ | 2017

    Freier Zugriff