Collaborative Research: CPS: Small: Risk-Aware Planning and Control for Safety-Critical Human-CPS

合作研究：CPS：小型：安全关键型人类 CPS 的风险意识规划和控制

• 批准号: 2423130
• 负责人: Negar Mehr
• 金额: $ 25万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2423130&HistoricalAwards=false
• 关键词: Collaborative; Research; CPS; Small; Risk

The future of cyber-physical systems are smart technologies that can work collaboratively, cooperatively, and safely with humans. Smart technologies and humans will share autonomy, i.e., the right, obligation and ability to share control in order to meet their mutual objectives in the environment of operations. For example, surgical robots must interact with surgeons to increase their capabilities in performing high-precision surgeries, drones need to deliver packages to humans and places, and autonomous cars need to share roads with human-driven cars. In all such interactions, these systems must act safely despite the risks and uncertainties that are intrinsic with humans, technologies, and the environments in which they interact. The key insight of this project is that control strategies can be developed that increase safety in situations where a human needs to closely interact with a cyber-physical system (CPS) that is capable of autonomy or semi-autonomous action.The goal of this project is to develop risk-aware interactive control and planning for achieving safe cyber-physical-human (CPS-h) systems. This project will advance the state-of-the-art of CPS-h planning and control in three main ways: (i) developing computationally tractable risk-aware trajectory planning algorithms that are suited to general autonomous CPS-h, (ii) developing a computationally efficient and empirically supported framework to account for risk-awareness in human’s decision-making, and (iii) deriving interaction-aware planning algorithms for achieving safe and efficient interactions between multiple risk-aware agents. The proposed algorithms will be extensively evaluated with human subjects in interaction with autonomous CPS-h such as autonomous cars and quadcopters. This work will have direct impact on many CPS-h domains including but not limited to multi-agent interactions, autonomous driving, collaboration and coordination between humans and autonomous agents in safety-critical scenarios.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.

信息物理系统的未来是能够与人类协同、协作和安全地工作的智能技术。智能技术和人类将共享自主权，即共享控制的权利、义务和能力，以实现其共同目标。例如，手术机器人必须与外科医生互动，以提高他们进行高精度手术的能力，无人机需要将包裹运送到人类和地方，自动驾驶汽车需要与人类驾驶的汽车共享道路。尽管相互作用，这些系统必须安全地运行该项目的主要见解是，可以开发控制策略来提高人类需要与网络物理密切交互的情况下的安全性。能够自主或半自主行动的系统（CPS）。该项目的目标是开发风险感知的交互式控制和规划，以实现安全的网络物理人类（CPS-h）系统。最先进的CPS-h 规划和控制主要采用三种方式：(i) 开发适合通用自主 CPS-h 的计算上易于处理的风险感知轨迹规划算法，(ii) 开发计算高效且有经验支持的框架来考虑风险意识(iii) 推导交互感知规划算法，以实现多个风险感知主体之间安全有效的交互。所提出的算法将在主要与自动 CPS-h（例如自动驾驶汽车）交互的人类受试者中进行评估。和这项工作将对许多 CPS-h 领域产生直接影响，包括但不限于安全关键场景中的多智能体交互、自动驾驶、人类与自主智能体之间的协作和协调。该奖项反映了 NSF 的法定使命，并已获得通过使用基金会的智力优点和更广泛的影响审查标准进行评估，认为值得支持。