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User satisfaction based model for resource allocation in bike-sharing systems

机译:基于用户满意度的自行车共享系统资源分配模型

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摘要

Over the past decade, the number of ongoing bike-sharing programs has remarkably risen. In this framework, operators need appropriate methodologies to support them in optimizing the allocation of their resources to globally enhance the bike-sharing program, even without massive and costly interventions on the existing configuration of the system.In this paper, we propose an optimization model able to determine how to employ a given budget to enhancing a bike-sharing system, maximizing the global user satisfaction. During the day, each bicycle station has a certain number of bikes that fluctuates according to the travel demand; it happens, however, that for certain time slots, the station is full or empty. Then, we propose to consider as key performance indicators the zero-vehicle time and the full-port time, that reflected respectively the duration of vehicle shortage and parking stall unavailability in the stations. Both these indicators, together with the lost users of the system, need to be kept to a minimum if the final aim is maximizing the customer satisfaction, i.e. not forcing the user to use other stations or turn/shift to other travel modes. We have analyzed the historical usage patterns of the bike-sharing stations, smoothing their trends (by wavelets), and operated a preliminary spatio-temporal clustering. Our model verifies the necessity of adding or removing racks to each station, setting at the same time the optimal number of bikes to allocate in them, and decide the eventual realization of further stations. Then, an application, both on a small test and a real-size network, is presented, together with a sensitivity analysis.
机译:在过去的十年中,正在进行的自行车共享计划的数量已显着增加。在此框架中,即使没有对系统的现有配置进行大规模且昂贵的干预,运营商也需要适当的方法来支持他们优化资源分配,以全局增强自行车共享计划。本文提出了一种优化模型能够确定如何使用给定的预算来增强自行车共享系统,从而最大程度地提高全球用户满意度。白天,每个自行车站都有一定数量的自行车,这些自行车会根据旅行需求而波动;但是,在某些时隙中,电台已满或空了。然后,我们建议将零车辆时间和全港时间作为关键性能指标,分别反映车站的车辆短缺和停车失速的持续时间。如果最终目的是最大程度地提高客户满意度,即不强迫用户使用其他车站或转向/转换为其他出行方式,则这两个指标以及系统的丢失用户都必须保持在最低水平。我们分析了自行车共享站点的历史使用模式,通过小波平滑了它们的趋势,并进行了初步的时空聚类。我们的模型验证了在每个站点上添加或移除机架的必要性,同时设置了在其中分配自行车的最佳数量,并决定了最终站点的最终实现。然后,提出了在小型测试和真实网络上的应用程序,以及敏感性分析。

著录项

  • 来源
    《Transport policy》 |2019年第8期|117-126|共10页
  • 作者单位

    Polytech Univ Bari, Dept Civil Environm Land Bldg Engn & Chem DICATEC, Viale Orabona 4, I-70125 Bari, Italy;

    Polytech Univ Bari, Dept Civil Environm Land Bldg Engn & Chem DICATEC, Viale Orabona 4, I-70125 Bari, Italy;

    Polytech Univ Bari, Dept Civil Environm Land Bldg Engn & Chem DICATEC, Viale Orabona 4, I-70125 Bari, Italy;

    Polytech Univ Bari, Dept Civil Environm Land Bldg Engn & Chem DICATEC, Viale Orabona 4, I-70125 Bari, Italy;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Resource allocation; Bike-sharing system; Spatio-temporal clustering;

    机译:资源分配;自行车共享系统;时空聚类;

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