This paper presents a new perspective for in-station transfer flow estimation, utilising data collected by WiFi sensor system, which is critical for path choice modelling and pedestrian management. The full in-station transfer flow can be estimated by scaling up a ‘seed matrix’, which is constructed based on the identification of inter-platform transfer activities. Due to sensor failures, the main problem comes from handling the missing elements in the constructed ‘seed matrix’. We address this problem with a novel kernel-based framework, named self-measuring multi-task Gaussian process (SM-MTGP). The heterogeneous correlations in temporal features are captured by the designed task-based and input-based kernels separately. Moreover, a self-measuring kernel is designed for learning the correlations carried by the observations. The performance of the proposed method is validated with data from a busy railway station. The results show that the proposed algorithm achieves the best imputation accuracy in both accuracy and robustness, especially at high missing rates.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Missing data imputation for transfer passenger flow identified from in-station WiFi systems


    Beteiligte:
    Jiang, Wenhua (Autor:in) / Zheng, Nan (Autor:in) / Kim, Inhi (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2023-12-31


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt





    Augmented Stochastic Multiple Imputation Model for Airport Pavement Missing Data Imputation

    Farhan, J. / Fwa, T. F. | Transportation Research Record | 2014


    Missing traffic data: comparison of imputation methods

    Li, Yuebiao / Li, Zhiheng / Li, Li | Wiley | 2014

    Freier Zugriff


    Missing traffic data: comparison of imputation methods

    Li, Yuebiao / Li, Zhiheng / Li, Li | IET | 2014

    Freier Zugriff