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Techniques for Smart Urban Logistics Solutions’ Simulation: A Systematic Review

  • Ioannis KarakikesEmail author
  • Eftihia Nathanail
  • Mihails Savrasovs
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 68)

Abstract

Today, cities devise their own Sustainable Urban Logistics Plan (SULP) to improve the sustainability of their distribution system. Modern SULPs, following the development of technology, consider smart solutions e.g. pick-ups and deliveries by electric vehicles, bicycles or drones, city lockers, ITS systems for planning/routing, crowdsourcing services and other, which aim at mitigating the negative effects of the freight transport in the urban area. The effectiveness of these solutions, however, is not for sure, since their performance relies on particularities of cities’ urban freight transport system as well as the level of infrastructure, cooperation and policy adoption. To better understand and assess the impacts of a proposed solution in a city context, ex-ante evaluation through modeling is advised.

This study synthesizes the types of simulation techniques that are used to model the impacts of innovative smart urban freight solutions. A systematic literature review was performed in Web of Science Core Collection, SCOPUS and JSTOR databases to identify records that tackle with modeling smart urban freight solutions and present real case study results. Having gathered all relevant records through a query-based identification process, a screening process was adopted to keep only those that have an essential contribution to the topic. Eighty-two full papers met the criteria and were included in the qualitative analysis. Analysis’ key findings were that (1) the majority of studies use custom-made techniques for the evaluation of urban freight solutions, (2) there is growing tendency from 2015 onwards for such studies and, (3) “ITS for freight monitoring and planning/routing” is the most prominent solution in such studies.

Keywords

City logistics Last mile distribution Evaluation Modeling PRISMA 

Notes

Acknowledgements

This work has been supported by the ALLIANCE project (http://alliance-project.eu/) and has been funded within the European Commission’s H2020 Programme under contract number 692426. This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ioannis Karakikes
    • 1
    Email author
  • Eftihia Nathanail
    • 1
  • Mihails Savrasovs
    • 2
  1. 1.Department of Civil EngineeringUniversity of ThessalyVolosGreece
  2. 2.Transport and Telecommunication InstituteRigaLatvia

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