Multi-scale Modeling of Crowdshipping as a New Form of Urban Delivery

众包作为城市配送新形式的多尺度建模

基本信息

  • 批准号:
    1663411
  • 负责人:
  • 金额:
    $ 34.93万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-08-15 至 2021-07-31
  • 项目状态:
    已结题

项目摘要

E-commerce in the US has experienced explosive growth in the past decade, resulting in a precipitous increase in truck traffic. The surge of truck traffic has caused many negative consequences to the urban environment such as greater traffic congestion and emissions, faster wear-and-tear on road infrastructure, and more acute shortage of truck parking space. These consequences are increasingly at odds with the need to develop livable urban communities which requires significant reduction of truck traffic. Crowdshipping has emerged recently as an alternative to truck-based delivery. Using a crowd of ordinary individuals who walk, bike, or drive to perform delivery in urban areas, crowdshipping presents considerable promise to reconcile the strong need for livable community development with the rapid growth of urban freight demand. This award develops theoretic foundations for modeling and improving the efficiency of crowdshipping for urban delivery. Results from the research will lead to a better understanding of the traffic, economic, and environmental impact of crowdshipping and support urban freight policy making. Knowledge gained from this project will also provide generic insights for other areas in the increasingly crowdsourced and on-demand society, such as ride sourcing and mobile sensing. By designing, delivering, and evaluating a pipeline of engineering education activities, this award will further enhance the awareness and understanding of freight transportation and urban delivery innovations among diverse student groups. The research activities are organized around two thrusts. The first thrust establishes static and dynamic mechanisms to address individual solicitation and shipment assignment problems at the microscale. The properties of the mechanisms in incentivizing individual participation in crowdsourced delivery and the asymptotics of an approximation technique in shipment assignment will be investigated. The second thrust creates a queueing network-based framework to characterize and improve system performance of crowdshipping at the macroscale. Conditions for crowdshipping system equilibrium existence and equilibrium flows of crowdsourced individuals will be identified. Analytical capabilities will be developed to determine the optimal pool size of crowdsourced individuals to meet given shipping demand and improve delivery service fairness. The developed mechanisms, techniques, and models will be evaluated using case studies informed by real world data. If successful, this research will advance the knowledge and analysis capabilities of crowdshipping for urban delivery, and enrich the literature of transportation systems analysis and city logistics. Additionally, the PI will engage diverse student groups (high school and community college students) to raise awareness in understanding of freight transportation and urban delivery innovations among diverse student groups.
在过去的十年中,美国的电子商务经历了爆炸性的增长,导致卡车交通急剧增加。卡车交通的激增对城市环境造成了许多负面影响,例如更大的交通拥堵和排放,道路基础设施上的磨损速度更快,以及卡车停车位的严重短缺。这些后果越来越多,与建立可宜居的城市社区的需求相抵触,这需要大幅减少卡车交通。最近出现了众筹作为基于卡车的交付的替代方案。人群使用一群在城市地区行走,骑自行车或开车进行交付的普通人,表现出了巨大的希望,可以调和宜居社区发展的强烈需求,而城市货运需求的迅速增长。该奖项为建模和提高城市交付的众筹效率建模和提高了理论基础。研究结果将使人们更好地了解众筹和支持城市货运政策的交通,经济和环境影响。从该项目中获得的知识还将为越来越多的众包和按需社会的其他领域(例如乘车采购和移动传感)提供通用见解。通过设计,交付和评估工程教育活动的渠道,该奖项将进一步增强对各种学生群体之间货运运输和城市交付创新的认识和理解。研究活动围绕两个推力组织。第一个推力建立了静态和动态机制,以解决微观的个人招标和发货分配问题。该机制在激励个人参与众包交付和临时技术的渐近技术方面的特性将得到研究。第二个推力创建了一个基于网络的排队框架,以表征和提高宏观上的人群的系统性能。将确定众群体平衡存在的条件和众包个人的平衡流。将开发分析能力,以确定众包个人的最佳池大小,以满足运输需求并提高交付服务的公平性。将使用现实世界数据告知的案例研究对开发的机制,技术和模型进行评估。如果成功,这项研究将提高众筹的知识和分析能力,以进行城市交付,并丰富运输系统分析和城市物流的文献。此外,PI将吸引各种学生团体(高中和社区大学生),以提高人们对不同学生团体之间货运运输和城市交付创新的认识。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Deep reinforcement learning in transportation research: A review
Deep Reinforcement Learning for Crowdsourced Urban Delivery
Vehicle ownership models for a sharing economy with autonomous vehicle considerations
考虑自动驾驶汽车的共享经济车辆所有权模型
  • DOI:
    10.1080/19427867.2021.2007681
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Stinson, M.
  • 通讯作者:
    Stinson, M.
共 3 条
  • 1
前往

Bo Zou其他文献

Facile fabrication of faceted copper nanocrystals with high catalytic activity for p-nitrophenol reduction
轻松制备对硝基苯酚还原具有高催化活性的多面铜纳米晶体
Stress-Dependent Multicolor Mechanochromism in Epoxy Thermosets Based on Rhodamine and Diaminodiphenylmethane Mechanophores
基于罗丹明和二氨基二苯甲烷力团的环氧热固性材料中应力依赖性多色力致变色
  • DOI:
    10.1021/acs.macromol.1c02242
    10.1021/acs.macromol.1c02242
  • 发表时间:
    2022
    2022
  • 期刊:
  • 影响因子:
    5.5
  • 作者:
    Zhongtao Chen;Fangjun Ye;Tianyin Shao;Yeping Wu;Mao Chen;Yinyu Zhang;Xiuli Zhao;Bo Zou;Yuguo Ma
    Zhongtao Chen;Fangjun Ye;Tianyin Shao;Yeping Wu;Mao Chen;Yinyu Zhang;Xiuli Zhao;Bo Zou;Yuguo Ma
  • 通讯作者:
    Yuguo Ma
    Yuguo Ma
Research on Scan-GMTI technology of airborne MIMO radar based on STAP
基于STAP的机载MIMO雷达Scan-GMTI技术研究
Using deep learning algorithm to surmount drawbacks of statistical method in the procession of identify related genes with cancer
利用深度学习算法克服统计方法在癌症相关基因识别过程中的弊端
  • DOI:
    10.1101/571851
    10.1101/571851
  • 发表时间:
    2019
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bo Zou
    Bo Zou
  • 通讯作者:
    Bo Zou
    Bo Zou
Revealing the mechanism of ohmic heating against <em>Bacillus cereus</em> spores through intracellular homeostasis and lipid analysis
  • DOI:
    10.1016/j.foodcont.2024.110972
    10.1016/j.foodcont.2024.110972
  • 发表时间:
    2025-03-01
    2025-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yingying Sun;Yana Liu;Han Wang;Bo Zou;Yijie Zhao;Xingmin Li;Ruitong Dai
    Yingying Sun;Yana Liu;Han Wang;Bo Zou;Yijie Zhao;Xingmin Li;Ruitong Dai
  • 通讯作者:
    Ruitong Dai
    Ruitong Dai
共 51 条
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 11
前往

Bo Zou的其他基金

Maximizing Truck Platooning Participation with Preferences, Inclusion, and Privacy Preservation
通过偏好、包容性和隐私保护最大限度地提高卡车编队参与度
  • 批准号:
    2221418
    2221418
  • 财政年份:
    2023
  • 资助金额:
    $ 34.93万
    $ 34.93万
  • 项目类别:
    Standard Grant
    Standard Grant

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