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Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda

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  • Valeska Engesser

    (Research Group Mobilise, Department BUTO—Business Technology and Operations, Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
    Research Group Mobi, Mobility, Logistics and Automotive Technology Research Centre, Department BUTO—Business Technology and Operations, Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium)

  • Evy Rombaut

    (Research Group Mobi, Mobility, Logistics and Automotive Technology Research Centre, Department BUTO—Business Technology and Operations, Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium)

  • Lieselot Vanhaverbeke

    (Research Group Mobi, Mobility, Logistics and Automotive Technology Research Centre, Department BUTO—Business Technology and Operations, Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium)

  • Philippe Lebeau

    (Research Group Mobilise, Department BUTO—Business Technology and Operations, Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium)

Abstract

The implementation of autonomous delivery solutions in last-mile logistics operations is considered promising. Autonomous delivery solutions can help in tackling urban challenges related to last-mile logistics operations. Urbanization creates higher mobility and transportation demand, which contributes to increased congestion levels, traffic, air pollution, and accident rates. Moreover, mega-trends, such as e-commerce, demand that logistics companies react to increased customer expectations in terms of delivery time and service. Concerning service, electrified autonomous delivery solutions have the potential to operate 24/7 and can help to overcome driver shortages. This paper conducts a systematic literature review. Based on the literature set, a snowballing procedure was applied. Complementary gray literature was included. This work discusses different autonomous delivery solutions such as Autonomous Delivery Robots (ADRs), Unmanned Aerial Vehicles (UAVs), two- or multi-tiered systems, and the concept of passenger and freight integration. The work presents advantages and disadvantages, enabling the comparison of solutions. Furthermore, a research agenda is provided, from which practical-managerial and theoretical implications can be derived. The research agenda can help researchers, manufacturers, businesses, and governmental institutions to prepare for the arrival and subsequent implementation of autonomous delivery services. Various implications related to energy demand, legislation, implementation strategy, training, and risk and safety are presented. The outcome of this work calls for collaboration among various stakeholders, encourages mutual learning, and hints at the importance of national and international development projects.

Suggested Citation

  • Valeska Engesser & Evy Rombaut & Lieselot Vanhaverbeke & Philippe Lebeau, 2023. "Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda," Sustainability, MDPI, vol. 15(3), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2774-:d:1056750
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    References listed on IDEAS

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    1. Konstantina Anastasiadou, 2021. "Sustainable Mobility Driven Prioritization of New Vehicle Technologies, Based on a New Decision-Aiding Methodology," Sustainability, MDPI, vol. 13(9), pages 1-27, April.
    2. Luigi Ranieri & Salvatore Digiesi & Bartolomeo Silvestri & Michele Roccotelli, 2018. "A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    3. Wang, Yuan & Zhang, Dongxiang & Liu, Qing & Shen, Fumin & Lee, Loo Hay, 2016. "Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 279-293.
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    Cited by:

    1. Guglielmo Papagni & Setareh Zafari & Johann Schrammel & Manfred Tscheligi, 2024. "Automating Logistics Operations: Qualitative Insights from Four European Sites," Logistics, MDPI, vol. 8(4), pages 1-21, November.
    2. Wang, Aijia & Wang, Junqi & Zhang, Ruijun & Cao, Shi-Jie, 2024. "Mitigating urban heat and air pollution considering green and transportation infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).
    3. Miloš Veljović & Snežana Tadić & Mladen Krstić, 2024. "Last Word in Last-Mile Logistics: A Novel Hybrid Multi-Criteria Decision-Making Model for Ranking Industry 4.0 Technologies," Mathematics, MDPI, vol. 12(13), pages 1-30, June.

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