Freight distribution in urban areas: a method to select the most important loading and unloading areas and a survey tool to investigate related demand patterns

Marco Diana, Miriam Pirra, Andree Woodcock

    Research output: Contribution to journalArticlepeer-review

    21 Citations (Scopus)
    81 Downloads (Pure)

    Abstract

    Cities all around the world are observing increasing levels of urban freight activities owing to the growth of internet shopping combined to the traditional distribution to shops, creating additional problems in terms of congestions and environmental impacts. This study, developed within the European Project SUITS framework, aims at showing how Local Authorities can effectively observe freight flows from the demand side. This led to the design, implementation and testing of a spatial cluster analysis approach to understand which are the most important loading/unloading parking spots in an urban setting by processing the GPS traces of a fleet of logistic vehicles. Later field activities should focus on these important areas to maximize the efficiency of the survey. A survey of retailers and shops in such areas to observe delivering activities is then proposed. The whole process, namely the spatial analysis and the field survey, was then tested to the real case of an Italian city (Turin) to assess the potentiality of the methods. The methodology proposed can give useful insights to Local Authorities on a way of monitoring the freight distribution patterns at the more disaggregated individual loading/unloading area.

    Original languageEnglish
    Article number40
    Number of pages14
    JournalEuropean Transport Research Review
    Volume12
    Issue number1
    Early online date3 Jun 2020
    DOIs
    Publication statusPublished - 1 Dec 2020

    Bibliographical note

    This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

    Funder

    European Union’s Horizon 2020 Framework programme for research and innovation under grant agreement no 690650

    Keywords

    • Cluster analysis
    • DBSCAN
    • Freight distribution
    • GPS traces
    • Spatial clustering
    • Urban mobility

    ASJC Scopus subject areas

    • Automotive Engineering
    • Transportation
    • Mechanical Engineering

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