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

多用途卡车是极端天气情况下的第一反应者，用于执行救援灾区人员、砍伐树木以恢复交通、修理电线杆和恢复电力等任务。这项研究建立了一个科学的框架，以保持生产力和安全的应急响应车辆，同时消除事故。这是通过一个新的集成框架来实现的，该框架可以监测和预测天气状况，并将这些信息输入智能机制，从而自动塑造多用途卡车的空气动力学表面。该项目包括招聘工作和活动，以将高中生以及来自多种文化和学科的学生纳入自主研究。 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，并促进亚拉巴马州的经济增长。与传统方法不同，A-IMS将基于道路条件，气象，速度限制，风速和方向，将无模型形状变形学习机制与基于模型的交互式设计相结合，以管理空气-流体流动。这种潜在的A-IMS变革框架将：（1）带来新的学习视角，以提高自然工程系统的适应性和智能，从而利用物理和信息过程;（2）为危险环境建立一个综合设计框架，以实现复原力，和生产力，同时还减轻了潜在的敌对学习代理的影响，可以存在于云中;（3）研究A-IMS的交互式物理组件，该组件将同时在多相流体和固体的两种不同介质中运行（即，空气/流体和道路）。A-IMS框架将通过硬件/软件实施进行评估，以及在佛罗里达国际大学风墙的独特测试条件下进行评估。该项目的教育和推广部分包括综合研究和教育计划，这将导致技术转让和夏令营，特别侧重于接触代表性不足的少数民族和妇女，这一奖项反映了NSF的法定使命，并已被认为值得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的支持。

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.