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Substantiation of Loading Hub Location for Electric Cargo Bikes Servicing City Areas with Restricted Traffic

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  • Vitalii Naumov

    (Faculty of Civil Engineering, Cracow University of Technology, Warszawska 24, 31155 Krakow, Poland)

Abstract

Electric cargo bicycles have become a popular mode of transport for last-mile goods deliveries under conditions of restricted traffic in urban areas. The indispensable elements of the cargo bike delivery systems are loading hubs: they serve as intermediate points between vans and bikes ensuring loading, storage, and e-vehicle charging operations. The choice of the loading hub location is one of the basic problems to be solved when designing city logistics systems that presume the use of electric bicycles. The paper proposes an approach to justifying the location of a loading hub based on computer simulations of the delivery process in the closed urban area under the condition of stochastic demand for transport services. The developed mathematical model considers consignees and loading hubs as vertices in the graph representing the transport network. A single request for transport services is described based on the set of numeric parameters, among which the most significant are the size of the consignment, its dimensions, and the time interval between the current and the previous requests for deliveries. The software implementation of the developed model in Python programming language was used to simulate the process of goods delivery by e-bikes for two cases—the synthetically generated rectangular network and the real-world case of the Old Town district in Krakow, Poland. The loading hub location was substantiated based on the simulation results from a set of alternative locations by using the minimum of the total transport work as the efficiency criterion. The obtained results differ from the loading hub locations chosen with the use of classical rectilinear and center-of-gravity methods to solve a simple facility location problem.

Suggested Citation

  • Vitalii Naumov, 2021. "Substantiation of Loading Hub Location for Electric Cargo Bikes Servicing City Areas with Restricted Traffic," Energies, MDPI, vol. 14(4), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:839-:d:494449
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    References listed on IDEAS

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    1. Hong Gao & Kai Liu & Xinchao Peng & Cheng Li, 2020. "Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands," Energies, MDPI, vol. 13(8), pages 1-16, April.
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    Cited by:

    1. Narayanan, Santhanakrishnan & Antoniou, Constantinos, 2022. "Electric cargo cycles - A comprehensive review," Transport Policy, Elsevier, vol. 116(C), pages 278-303.
    2. Parisa Zare & Christopher Pettit & Simone Leao & Ori Gudes, 2022. "Digital Bicycling Planning: A Systematic Literature Review of Data-Driven Approaches," Sustainability, MDPI, vol. 14(23), pages 1-20, December.
    3. Albert Y. S. Lam & Bogusław Łazarz & Grzegorz Peruń, 2022. "Smart Energy and Intelligent Transportation Systems," Energies, MDPI, vol. 15(8), pages 1-3, April.

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