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

CPS：中：边缘云支持自动驾驶汽车的可预测、全球态势感知

基本信息

批准号：
1837382
负责人：
Gabriel Parmer
金额：
$ 100万
依托单位：
George Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-01-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1837382&HistoricalAwards=false
关键词：
CPS Medium Edge Cloud Support

项目摘要

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.

该项目的目的是提高许多不同网络的自动驾驶汽车的状况意识。该方法是系统的新理论和抽象，其中潜在移动的物理系统以很高的速度加入并离开网络。使这类网络物理系统（CPS）有效且安全需要通过网络利用其他近距离车辆的传感器信息：这将使车辆能够具有更高的情境意识 - 有效地在角落周围看到。但是，必须对计算进行足够快的速度来准确控制物理系统，并且网络的协调使这更具挑战性。该研究计划与研究人员广泛指导计划的一项教育计划相结合，重点是涉及不同背景的学生。该项目调查了在网络“ Edge”中部署的软件平台CPSEDGE，该项目部署了来自附近车辆的传感器信息，并智能地促进了行动计划。 CPSEDGE利用其网络靠近车辆，经过精心设计，可以快速回复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汽车提供更大的情境意识，并提高管理它们的软件平台的响应能力，可靠性和安全性。 CPSEDGE建立在新的过程抽象上，该过程轻巧，甚至可以扩展到非常大的系统，即使在大量搅拌下，同时也可以提供更高的可靠性和安全性。该抽象由CPSEDGE系统管理，以确保必要的计算通过物理系统实时进行。传感器数据将被融合以产生环境的概率模型，为附近的车辆提供全球计划。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估来获得支持的。