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

在过去的十年里，美国的电子商务经历了爆炸性的增长，导致卡车交通量急剧增加。卡车交通的激增对城市环境造成了许多负面影响，例如交通拥堵和排放量增加，道路基础设施磨损加快，卡车停车位短缺更加严重。这些后果越来越不符合发展宜居城市社区的需要，这需要大幅减少卡车交通。最近出现了众筹，作为卡车送货的替代方案。利用一群步行、骑自行车或开车的普通人在城市地区进行交付，众筹在协调宜居社区发展的强烈需求与城市货运需求的快速增长方面具有相当大的潜力。该奖项为建模和提高城市交付的众包效率奠定了理论基础。研究结果将有助于更好地了解众包的交通、经济和环境影响，并支持城市货运政策制定。从该项目中获得的知识还将为日益众包和按需社会的其他领域提供通用见解，例如乘车外包和移动的传感。通过设计，交付和评估工程教育活动的管道，该奖项将进一步提高不同学生群体对货运和城市交付创新的认识和理解。研究活动围绕两个重点组织。第一个推力建立静态和动态机制，以解决个人招标和货运分配问题的微观尺度。本研究将探讨在众包配送中激励个人参与的机制的性质，以及在运送分配中近似技术的渐近性。第二个推力创建了一个基于网络的框架，以表征和提高系统性能的众筹在宏观尺度上。将确定众包系统均衡存在的条件和众包个体的均衡流。将开发分析能力，以确定众包个人的最佳池大小，以满足给定的航运需求，并提高交付服务的公平性。将使用由真实的世界数据提供信息的案例研究来评估所开发的机制、技术和模型。如果成功，这项研究将推进知识和分析能力的众包城市交付，并丰富交通系统分析和城市物流的文献。此外，PI将吸引不同的学生群体（高中和社区大学生），以提高不同学生群体对货运和城市交付创新的认识。

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.