CAREER: Reconfigurable Infrastructure and Scalable Execution for Advanced Air Mobility (RISE-AAM)

职业：先进空中机动性的可重构基础设施和可扩展执行（RISE-AAM）

• 批准号: 2237215
• 负责人: Zhenbo Wang
• 金额: $ 53.78万
• 依托单位: University of Tennessee Knoxville
• 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: 2023-05-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2237215&HistoricalAwards=false
• 关键词: CAREER; Reconfigurable; Infrastructure; Scalable; Execution

This Faculty Early Career Development (CAREER) project will advance the knowledge needed to develop transformative infrastructure and execution schemes for the emerging advanced air mobility missions. With the goals of addressing future mobility needs and fostering safe, efficient, and sustainable transportation systems, advanced air mobility focuses on the transition from the traditional air transportation to future passenger or cargo-carrying services in and around urban areas. However, integration of air mobility into complex three-dimensional built environments presents many unique challenges in infrastructure design and operation. To address these challenges, this project will develop and test a novel airway system as well as the coupled operational rules and control schemes. These approaches are adaptive and scalable depending on the real-time travel demand, vertiport distribution and throughput, airspace capacity, and environmental footprint. The resulting advances are expected to impact multiple fields including transportation, aerospace, smart cities, and civil engineering. The research activities are closely integrated with educational activities to 1) support pre-college education and research through K-12 teacher training and summer pre-college programs, 2) promote undergraduate and graduate education and research by creating new courses, enhancing existing courses, and mentoring student researchers, and 3) educate broader community and general public through scholarly forums, university events, and network platforms.The long-term goal of this project is to transform the transportation system by advancing the knowledge and capabilities of novel concepts, infrastructures, and operations for intelligent, automated, cooperative air transportation services in and around urban areas. The overall objective of this project is to develop and test advanced air mobility infrastructures (both physical and digital) and execution procedures to enable safe and efficient coordination of an increasing number of heterogeneous air vehicles for on-demand fast transit services in chaotic, dynamic environments. Specific research objectives include: 1) optimize location of physical air mobility infrastructure and investigate a transformative digital air mobility infrastructure, 2) develop a hierarchical execution approach that integrates a novel data-driven scheduling method and a new distributed model-based vehicle control technique for safe and efficient air mobility operations, and 3) validate the infrastructure designs and execution approaches through integrated simulations and emulated experiments. These contributions are significant because they are a fundamental step toward reimagining transportation systems by uncovering how high-tempo, high-density air mobility operations can be safely and efficiently coordinated in limited airspace.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.

这个教师早期职业发展（CAREER）项目将推进为新兴的先进空中机动任务开发变革性基础设施和执行计划所需的知识。为了满足未来的流动性需求，促进安全，高效和可持续的运输系统，先进的空中交通侧重于从传统的航空运输过渡到未来的乘客或货物运输服务。然而，将空中交通整合到复杂的三维建筑环境中，在基础设施设计和运营方面提出了许多独特的挑战。为了应对这些挑战，本项目将开发和测试一种新的气道系统以及耦合的操作规则和控制方案。这些方法具有自适应性和可扩展性，具体取决于实时旅行需求、垂直起降机场分布和吞吐量、空域容量和环境足迹。由此产生的进步预计将影响多个领域，包括交通、航空航天、智慧城市和土木工程。研究活动与教育活动紧密结合，1）通过K-12教师培训和夏季大学预科课程支持大学预科教育和研究，2）通过创建新课程，加强现有课程和指导学生研究人员，促进本科和研究生教育和研究，3）通过学术论坛，大学活动，该项目的长期目标是通过推进城市地区及其周边地区智能化、自动化、合作航空运输服务的新概念、基础设施和运营的知识和能力来改造交通系统。该项目的总体目标是开发和测试先进的空中移动基础设施（物理和数字）和执行程序，以实现在混乱，动态环境中安全，高效地协调越来越多的异构飞行器，以提供按需快速运输服务。具体研究目标包括：1）优化物理空中交通基础设施的位置，并研究变革性的数字空中交通基础设施，2）开发一种分层执行方法，该方法集成了新的数据驱动调度方法和新的基于分布式模型的车辆控制技术，以实现安全高效的空中交通运营，3）通过集成仿真和仿真实验验证基础设施设计和执行方法。这些贡献意义重大，因为它们揭示了如何在有限的空域内安全有效地协调高节奏、高密度的空中机动行动，从而为重塑交通系统迈出了重要一步。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。

项目成果

A Reinforcement Learning Approach to Vehicle Coordination for Structured Advanced Air Mobility

• DOI: 10.1016/j.geits.2024.100157
• 发表时间: 2024-01
• 期刊: Green Energy and Intelligent Transportation
• 作者: Sabrullah Deniz;Yufei Wu;Yang Shi;Zhenbo Wang

A Convex Approach to High-fidelity Landing Trajectory Optimization for Advanced Air Mobility

先进空中机动性高保真着陆轨迹优化的凸方法

• DOI: 10.2514/6.2024-2484
• 发表时间: 2024
• 期刊: American Institute of Aeronautics and Astronautics
• 作者: Wu, Yufei;Deniz, Sabrullah;Wang, Zhenbo;Huang, Daning
• 通讯作者: Huang, Daning

Autonomous Landing of eVTOL Vehicles for Advanced Air Mobility via Deep Reinforcement Learning

• DOI: 10.2514/6.2024-2485
• 发表时间: 2024-01
• 期刊: AIAA SCITECH 2024 Forum
• 作者: Sabrullah Deniz;Yufei Wu;Zhenbo Wang