S&AS: INT: COLLAB: Aerodynamic Intelligent Morphing System (A-IMS) for Autonomous Smart Utility Truck Safety and Productivity in Severe Environments

在极端天气情况下，公共事业车是救援受灾人员、砍伐树木恢复交通、修理电线杆和恢复电力等任务的第一反应者。本研究建立了一个科学的框架，以保持应急车辆的生产力和安全性，同时消除事故。这是通过一个新颖的集成框架来实现的，该框架可以监测和预测天气状况，并将信息输入智能机制，自动塑造多功能卡车的空气动力学表面。该项目包括招募工作和活动，以整合高中学生，以及来自不同文化和学科的学生进行自主研究。该项目预计将为下一代交通基础设施弹性提供新的科学知识和工程技术，并促进阿拉巴马州的经济增长。与传统方法不同，A-IMS将无模型变形学习机制与基于模型的交互设计相结合，根据路况、气象、速度限制、风速和方向来管理空气-流体流动。这一潜在的A-IMS变革框架将：(1)带来新的学习视角，以增强利用物理和信息过程的自然工程系统的适应性和智能；(2)建立一个针对危险环境的综合设计框架，通过形态特性的综合适应来实现弹性和生产力，同时减轻可能存在于云中的潜在对抗性学习代理的影响；(3)研究A-IMS的交互物理组件，该组件将同时在两种不同的多相流体和固体介质（即空气/流体和道路）中运行。A-IMS框架将通过硬件/软件实施以及在佛罗里达国际大学风之墙的独特测试条件下的真实条件进行评估。该项目的教育和外联部分包括综合研究和教育计划，将导致技术转让和夏令营，特别侧重于向代表性不足的少数民族和妇女伸出援助之手。该奖项反映了美国国家科学基金会的法定使命，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。

Utility trucks are the first responders in areas of extreme weather situations for tasks such as rescuing people from disaster areas, cutting trees to restore traffic, and repairing electric posts and restoring power. This study establishes a scientific framework for maintaining the productivity and safety of emergency response vehicles while eliminating accidents. This is implemented via a novel integrated framework to monitor and predict weather conditions and feed that information into intelligent mechanisms that autonomously shape the aerodynamic surfaces of utility trucks. The project includes recruitment efforts and activities to integrate high-school students, as well as students from multiple cultures, and disciplines into autonomy research. This project is expected to contribute new scientific knowledge and engineering techniques for next generation transportation infrastructure resiliency, and to facilitate economic growth in the state of Alabama.Unlike conventional approaches, the A-IMS will integrate model-free shape-morphing learning mechanisms with model-based interactive design to manage air-fluid flows, based on the road conditions, meteorology, speed limit, wind speed, and direction. This potentially transformative framework for A-IMS will: (1) bring new perspectives of learning to enhance the adaptability and intelligence in natural-engineering systems that leverage physical and information processes; (2) establish an integrated design framework for hazardous environments to achieve resilience, and productivity through integrated adaptation of morphological properties while also mitigating the effects of potentially adversarial learning agents that can exist in the cloud; (3) investigate the interactive physical components of the A-IMS, that will simultaneously operate in two different mediums of multi-phase fluids, and solids (i.e., the air/fluid and road). The A-IMS framework will be evaluated through hardware/software implementation, as well as in real-world conditions in the unique test conditions available at Wall of Wind at Florida International University. The project's education and outreach component include integrated research and education plans that will lead to technology transfer and summer camps with a special focus on reaching out to underrepresented minorities and women.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.