CPS: Medium: Edge-Cloud Support for Predictable, Global Situational-Awareness for Autonomous Vehicles

该项目的目标是提高自动驾驶车辆在许多不同网络上的情况感知。这种方法是对潜在移动的物理系统以高速率加入和离开网络的系统的新理论和抽象。要使这类网络物理系统(CP)高效和安全，需要利用来自网络上其他邻近车辆的传感器信息：这将使车辆具有更高的态势感知能力--有效地看到角落。然而，计算必须执行得足够快才能准确地控制物理系统，而通过网络进行协调使这一点更加具有挑战性。该研究计划与一项教育倡议相结合，整合到研究人员广泛的指导计划中，重点是让不同背景的学生参与进来。该项目调查部署在网络“边缘”的软件平台CPSEdge，该平台收集附近车辆的传感器信息，并智能地分享产生的行动计划。CPSEdge利用其靠近车辆的网络，经过精心设计，能够以足够快的速度响应车辆，以跟上快速变化的物理环境。为CPSEdge开发的工具和技术将为自动驾驶车辆提供更好的态势感知，并提高管理它们的软件平台的响应性、可靠性和安全性。CPSEdge构建在一个新的流程抽象之上，它是轻量级的，可以扩展到非常大的系统，即使在重大波动的情况下也是如此，同时提供更高的可靠性和安全性。此抽象由CPSEdge系统管理，以确保与物理系统实时进行必要的计算。传感器数据将被融合以生成环境的概率模型，为附近的车辆提供全球规划。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 goal of this project is improved situation awareness for autonomous vehicles across many different networks. The approach is new theory and abstractions for systems where potentially moving physical systems join and leave the network at a high rate. Making these kinds of cyber-physical systems (CPS) efficient and safe requires leveraging the sensor information from other proximate vehicles over the network: this will enable vehicles to have much higher situational awareness--effectively seeing around corners. However, computation must be performed fast enough to accurately control the physical system, and coordination over networks makes this even more challenging. The research program is paired with an educational initiative integrated into the extensive mentoring program of the researchers, with an emphasis on involving students of diverse backgrounds.This project investigates CPSEdge, a software platform deployed at the network "edge", which aggregates sensor information from nearby vehicles, and intelligently shares resulting plans of action. CPSEdge leverages its network proximity to vehicles, and is carefully designed to reply to vehicles fast enough to keep up with a quickly changing physical environment. The tools and techniques developed for CPSEdge will offer greater situational awareness to autonomous vehicles, and improve the responsiveness, reliability, and security of the software platforms that manage them. CPSEdge is built on a new process abstraction that is lightweight and can scale up to very large systems, even under significant churn, while providing increased reliability and security. This abstraction is managed by the CPSEdge system to ensure that the requisite computation is conducted in real-time with the physical system. Sensor data will be fused to generate a probabilistic model of the environment, providing global planning for nearby vehicles.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.