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

这一创新-技术转化伙伴关系(PFI-TT)项目的更广泛影响/商业潜力是使无人驾驶飞行器(无人机或无人机)和电动卡车能够安全高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%，占全球温室气体排放的8%。具体地说，这项设想的技术允许物流服务提供商为使用电动卡车和无人机的可扩展车队建立可靠和优化的路线计划。该项目正在开发的技术具有以下潜力：(I)提高最后一英里服务提供商的车队利用率和生产率，(Ii)减少供应链中的碳足迹，(Iii)增强基于无人机交付的操作安全和网络通信可靠性，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，如医疗递送、电子商务物流、人道主义行动、应急响应和最后一英里递送。该项目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操作。该项目解决的一个关键技术挑战是联合考虑无人机和电动卡车路线管理的运营(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分组转发策略)决策。研究目标包括开发和验证(I)有效解决电动卡车和无人机路线问题的新优化模型和启发式方法，(Ii)集成机器学习和处理随机元素优化的新动态路线模型，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，其特点是基于环境条件感知的无人机轨迹规划的人工智能(AI)启用的算法。该项目涉及一种模块化战略，从而使路线规划算法可以针对任何交付方式(电动卡车配送、直接无人机配送和卡车-无人机混合作业)进行扩展。该项目的创新是基于与多个工业合作伙伴合作的最低可行产品(MVP)的现场实验和中试测试进行评估的。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.