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GPS Data Analysis for Understanding Urban Goods Movement

Author

Listed:
  • Pascal Pluvinet

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Jesus Gonzalez-Feliu

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Christian Ambrosini

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper aims to investigate the contribution of GPS survey techniques for urban goods movement characterization and diagnosis, more precisely the implementation and application issues related to the introduction of real-time data transmission procedures and phone tools with integrated GPS devices. We propose a GPS-based data collection method for urban freight route characterization using a Smartphone application. After testing and calibrating the data processing tool, we analyze the main results on a baseline of about 900 rounds, with the R software. This analysis allows us to define the characteristics of the overall routes as well as the environmental impacts linked with the categories of roads: urban highways, main roads and residential streets. Moreover, the study shows that the environmental behavior of the driver is connected with the main activity of the carriers. The complementarity between GPS and traditional urban freight surveys is finally discussed.

Suggested Citation

  • Pascal Pluvinet & Jesus Gonzalez-Feliu & Christian Ambrosini, 2012. "GPS Data Analysis for Understanding Urban Goods Movement," Post-Print halshs-03863412, HAL.
    • Handle: RePEc:hal:journl:halshs-03863412
    DOI: 10.1016/j.sbspro.2012.03.121
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    Cited by:

    1. Regal, Andrés & Gonzalez-Feliu, Jesús & Rodriguez, Michelle, 2023. "A spatio-functional logistics profile clustering analysis method for metropolitan areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).

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