PFI-TT: Cloud-based Route Management Platform for Optimizing Last-Mile Logistics of Electric Truck and Drone Operations

PFI-TT：基于云的路线管理平台，用于优化电动卡车和无人机运营的最后一英里物流

• 批准号: 2313887
• 负责人: Sharan Srinivas
• 金额: $ 25万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313887&HistoricalAwards=false
• 关键词: PFI; TT; Cloud; based; Route

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to enable the safe and efficient use of unmanned aerial vehicles (UAVs or drones) and electric trucks for last-mile logistics, a multi-billion global market that accounts for 41% of the total supply cost and 8% of global greenhouse gas emissions. Specifically, the envisioned technology allows logistics service providers to establish reliable and optimized routing plans for a scalable fleet involving electric trucks and UAVs. The technology being developed in this project has the potential to: (i) increase the fleet utilization and productivity of last-mile service providers, (ii) reduce carbon footprint in supply chains, (iii) enhance operational safety and network communication reliability of drone-based deliveries, and (iv) decrease operational costs of last-mile logistics. The potential markets for the technology being developed in the project include many areas, such as medical delivery, e-commerce logistics, humanitarian operations, emergency response, and last-mile delivery. The methodological advancements and scientific understanding derived from this project can benefit policymakers, researchers and practitioners and strengthen the economic competitiveness of the United States.This project is developing and validating a cloud-based route optimization platform for electric trucks and UAVs to enable safe and efficient last-mile operations. A key technical challenge addressed in this project is the joint consideration of operational (i.e., optimizing vehicle’s route plan) and networking (packet forwarding strategy for communication among vehicles and ground servers) decisions for UAV and electric truck route management. The research objectives include the development and validation of (i) new optimization models and heuristic methods to efficiently solve the electric truck and UAV routing problem, (ii) new dynamic routing models that integrate machine learning and optimization for handling stochastic elements, while accounting for airspace and road network management, environmental factors and network communications, and (iii) network protocol design that features artificial intelligence (AI)-enabled algorithms for UAV trajectory planning based on awareness of environmental conditions. The project involves a modular strategy, thereby allowing the route planning algorithm to be scalable for any delivery methods (electric truck-only distribution, direct drone delivery, and hybrid truck-drone operations). The innovation in this project is evaluated based on field experimentation and pilot testing of a minimum viable product (MVP) in collaboration with multiple industrial partners.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个创新-技术转化伙伴关系（PFI-TT）项目的更广泛影响/商业潜力是使无人机（UAV或无人机）和电动卡车能够安全有效地用于最后一英里物流，这是一个数十亿美元的全球市场，占总供应成本的41%和全球温室气体排放的8%。具体而言，设想的技术允许物流服务提供商为涉及电动卡车和无人机的可扩展车队建立可靠和优化的路线规划。该项目正在开发的技术有可能：（i）提高最后一英里服务提供商的车队利用率和生产力，（ii）减少供应链中的碳足迹，（iii）提高无人机交付的运营安全性和网络通信可靠性，以及（iv）降低最后一英里物流的运营成本。该项目正在开发的技术的潜在市场包括许多领域，如医疗交付、电子商务物流、人道主义行动、应急响应和最后一英里交付。该项目所取得的方法进步和科学理解可以使政策制定者、研究人员和从业人员受益，并增强美国的经济竞争力。该项目正在开发和验证一个基于云的电动卡车和无人机路线优化平台，以实现安全高效的最后一英里运营。该项目所处理的一个关键技术挑战是联合考虑业务（即，优化车辆的路线计划）和网络（车辆和地面服务器之间通信的数据包转发策略）决策，用于无人机和电动卡车路线管理。研究目标包括开发和验证（i）新的优化模型和启发式方法，以有效解决电动卡车和无人机路由问题，（ii）新的动态路由模型，集成机器学习和优化，以处理随机元素，同时考虑空域和道路网络管理，环境因素和网络通信，以及（iii）网络协议设计，其特征在于基于对环境条件的感知的UAV轨迹规划的人工智能（AI）使能算法。该项目涉及模块化策略，从而允许路线规划算法可扩展到任何交付方法（纯电动卡车配送，直接无人机交付和混合卡车无人机操作）。该项目的创新是根据与多个工业合作伙伴合作的最小可行产品（MVP）的现场实验和试点测试进行评估的。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。