CPS: Medium: Collaborative Research: Transforming Connected and Automated Transportation with Smart Networking, Cooperative Sensing, and Edge Computing

CPS：中：协作研究：通过智能网络、协作传感和边缘计算改变互联和自动化交通

• 批准号: 2038559
• 负责人: Feng Qian
• 金额: $ 25.98万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038559&HistoricalAwards=false
• 关键词: CPS; Medium; Collaborative; Research; Transforming

This NSF Cyber-Physical Systems (CPS) grant will advance the state-of-the-art of Connected and Automated Vehicle (CAV) systems by innovating in the three key areas of networking, sensing, and computation, as well as the synergy among them. This work leverages several emerging technology trends that are expected to transform the ground transportation system: much higher-speed wireless connectivity, improved on-vehicle and infrastructure based sensing capabilities, and advances in machine learning algorithms. So far, most related research and development focused on individual technologies, leading to limited benefits. This project will develop an integrated platform that jointly handles networking, sensing, and computation, by addressing key challenges associated with the operating conditions of the CAVs: e.g., safety-critical, high mobility, scarce on-board computing resources, fluctuating network conditions, limited sensor capabilities. The research team will study how to use the integrated platform to enable real-world CAV applications, such as enhancement of public service personnel's safety, alleviation of congestion at bottleneck areas, and protection of vulnerable road users (VRUs). Given its interdisciplinary nature, this project will yield a broad impact in multiple research communities including transportation engineering, mobile/edge computing, and machine learning. The outcome of this research will benefit multiple stakeholders in the CAV ecosystem: drivers, pedestrians, CAV manufacturers, transportation government agencies, mobile network carriers, etc., ultimately improving the safety and mobility of the nation's transportation system. This project will also provide a platform to conduct various education and outreach activities. The intellectual core of this research consists of several foundational contributions to the ground transportation CPS domain. First, it innovates vehicle-to-everything (V2X) communications through strategically aggregating 4G/5G/WiFi/DSRC technologies to enhance network performance. Second, it develops a cooperative sensing and perception framework where nearby vehicles can share raw sensor data with an edge node to create a global view, which can provide extended perceptual range and detection of occluded objects. The key technical contribution is to ensure good scalability - allowing many moving vehicles to efficiently share their data despite limited, fluctuating network resources. Third, it enables partitioning computation across vehicles and the infrastructure to meet the real-time requirements of CAV applications. Fourth, integrating the above building blocks of networking, sensing, and computation, the research team will develop an optimization framework that makes adaptive, resource-aware decisions on what computation needs to be performed where at which quality, to maximize the service quality of CAV applications.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.

NSF网络物理系统（CPS）赠款将通过在网络，传感和计算的三个关键领域以及其中的协同作用中进行创新，从而推动连接和自动化车辆（CAV）系统的最新技术。这项工作利用了一些新兴技术趋势，这些趋势有望改变地面运输系统：更高速度的无线连接，改善了基于车辆和基础架构的感应功能以及机器学习算法的进步。到目前为止，大多数相关的研究和发展都集中在单个技术上，从而带来有限的收益。该项目将通过解决与骑士的运营条件相关的关键挑战来开发一个集成的平台，该平台可以共同处理网络，传感和计算：例如，关键安全性，高移动性，稀缺的车载计算资源，波动网络条件，有限的传感器功能。研究团队将研究如何使用集成平台来实现现实世界中的CAV应用程序，例如增强公共服务人员的安全性，减轻瓶颈领域的拥塞以及保护脆弱的道路使用者（VRUS）。鉴于其跨学科性质，该项目将对多个研究社区产生广泛的影响，包括运输工程，移动/边缘计算和机器学习。这项研究的结果将使CAV生态系统中的多个利益相关者受益：驾驶员，行人，CAV制造商，运输政府机构，移动网络运营商等，最终改善了国家运输系统的安全性和流动性。该项目还将提供一个进行各种教育和外展活动的平台。这项研究的智力核心包括对地面运输CPS领域的几项基础贡献。首先，它通过策略性地汇总4G/5G/WIFI/DSRC技术来创新车辆到所有设施（V2X）通信，以增强网络性能。其次，它开发了一个合作的感应和感知框架，附近的车辆可以与边缘节点共享原始传感器数据以创建全局视图，该视图可以提供扩展的感知范围和闭塞对象的检测。关键的技术贡献是确保良好的可扩展性 - 尽管有限的网络资源有限，但许多移动的车辆能够有效地共享其数据。第三，它使跨车辆和基础架构的计算能够满足CAV应用程序的实时要求。第四，研究团队将整合上述网络，感应和计算的构建块，将开发一个优化框架，该框架对需要执行哪些计算的自适应，具有资源感知的决策，以最大程度地提高CAV应用程序的服务质量，以最大程度地提高NSF的法定任务，并通过评估范围的范围来反映出该奖励的范围，并通过评估了范围的知识群体，并具有基础的支持。

项目成果

EMP: edge-assisted multi-vehicle perception

• DOI: 10.1145/3447993.3483242
• 发表时间: 2021-10
• 期刊: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
• 作者: Xumiao Zhang;Anlan Zhang;Jiachen Sun;Xiao Zhu;Y. Guo;Feng Qian;Z. Mao

Vivisecting Mobility Management in 5G Cellular Networks

• DOI: 10.1145/3544216.3544217
• 发表时间: 2022-01-01
• 期刊: SIGCOMM '22: PROCEEDINGS OF THE 2022 ACM SIGCOMM 2022 CONFERENCE
• 作者: Hassan, Ahmad;Narayanan, Arvind;Zhang, Zhi-Li
• 通讯作者: Zhang, Zhi-Li

A Variegated Look at 5G in the Wild: Performance, Power, and QoE Implications

• DOI: 10.1145/3452296.3472923
• 发表时间: 2021-01-01
• 期刊: SIGCOMM '21: PROCEEDINGS OF THE 2021 ACM SIGCOMM 2021 CONFERENCE
• 作者: Narayanan, Arvind;Zhang, Xumiao;Zhang, Zhi-Li
• 通讯作者: Zhang, Zhi-Li

An In-Depth Measurement Analysis of 5G mmWave PHY Latency and Its Impact on End-to-End Delay

• DOI: 10.1007/978-3-031-28486-1_13
• 发表时间: 2023
• 作者: Rostand A. K. Fezeu;Eman Ramadan;Wei Ye;Benjamin Minneci;Jack Xie;Arvind Narayanan;Ahmad Hassan;Feng Qian;Zhi-Li Zhang;J. Chandrashekar;Myungjin Lee