I-Corps: Optimization-driven high-density air traffic management software for large-scale drone operations

这个i-Corps项目的更广泛的影响/商业潜力是开发技术，使商业无人机交付作业更容易进入低空空域，同时确保高水平的作业安全和效率。大规模、有组织地部署送货无人机可以在减少道路拥堵、减少二氧化碳排放方面显著提高交通系统的效率；此外，它还将为老年人、病人和行动不便的社会成员提供健康和便利的好处。然而，由于空中交通管理(ATM)模式效率低下，现有的无人机交付做法在范围、规模和操作条件方面受到限制。该项目旨在发现一种可行的商业模式，将无人自动取款机的技术创新转化为可操作的、城市规模的全自动无人机交付系统。拟议中的系统将允许以前所未有的密度和效率安全使用低空空域，为最后一英里的送货节省大量成本。这个i-Corps项目探索在运动规划、动态车辆路线选择、通信和风险最小化领域开发一套新颖的优化驱动算法，为在共享空域导航的合作无人机机队提供实时ATM和轨迹控制。现有的ATM方法由于人类水平的响应时间和控制灵活性而留下了过高的分离余量。相比之下，拟议的新系统针对高密度空中交通条件进行了优化，提供了对4D飞行轨迹进行实时调整的能力，允许较小的分离裕度，并监督整个机队控制命令的安全执行。以即插即用的方式，拟议的系统将把一个由不同种类的多人无人机组成的集合变成一个有组织的智能机队。竞争优势在于通过商品化的云计算、物联网和通信基础设施将最先进的运筹学(OR)模型和算法融合到无人机平台上。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 I-Corps project is to develop technology to make the low-altitude airspace more accessible for commercial drone delivery operations while ensuring a high level of operational safety and efficiency. Large-scale, organized deployment of delivery drones can unlock substantial efficiency gain in transportation systems in terms of reduced road congestion, reduced CO2 emission; in addition, it would offer health and convenience benefits to senior citizens, the ill, and mobility-challenged members of society. However, existing drone delivery practices are limited in scope, scale, and operating conditions due to inefficient air traffic management (ATM) paradigms. This project aims to discover a viable business model for translating technological innovations in unmanned ATM into an operable, city-scale, fully automated drone delivery system. The proposed system would allow safe use of the low-altitude airspace at an unprecedented density and efficiency, generating enormous savings for last-mile deliveries. This I-Corps project explores the development of a suite of novel optimization-driven algorithms in the areas of motion-planning, dynamic vehicle routing, communication and risk minimization to provide real-time ATM and trajectory control for a cooperative fleet of drones navigating a shared airspace. Existing ATM methods leave excessive separation margins due to human-level response time and control dexterity. In contrast, the proposed new system is optimized for high-density air traffic conditions, offering the capability to generate real-time adjustments to 4D flight trajectories, tolerating a smaller separation margin, and overseeing safe execution of control commands across the fleet. In a plug-and-play fashion, the proposed system will turn a collection of heterogeneous multicopter drones into an organized and intelligent fleet. The competitive advantage lies in the fusion of the state-of-the-art operations research (OR) models and algorithms onto drone platforms via commoditized cloud computing, IoT and communication infrastructures.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.