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) 拨款将通过在网络、传感和计算三个关键领域以及之间的协同创新来推进最先进的联网和自动驾驶车辆 (CAV) 系统他们。这项工作利用了一些有望改变地面交通系统的新兴技术趋势：更高速的无线连接、改进的车载和基础设施传感能力以及机器学习算法的进步。到目前为止，大多数相关研发都集中在个别技术上，导致效益有限。该项目将开发一个综合平台，共同处理网络、传感和计算，解决与 CAV 操作条件相关的关键挑战：例如安全关键、高移动性、稀缺的机载计算资源、波动的网络条件、传感器能力有限。研究团队将研究如何利用集成平台实现CAV的实际应用，例如提高公共服务人员的安全、缓解瓶颈地区的拥堵以及保护弱势道路使用者（VRU）。鉴于其跨学科性质，该项目将对多个研究社区产生广泛影响，包括交通工程、移动/边缘计算和机器学习。这项研究的成果将使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、交通政府机构、移动网络运营商等，最终提高国家交通系统的安全性和机动性。该项目还将提供一个平台来开展各种教育和外展活动。这项研究的知识核心包括对地面交通 CPS 领域的多项基础性贡献。首先，它通过战略性聚合 4G/5G/WiFi/DSRC 技术来创新车对万物 (V2X) 通信，以增强网络性能。其次，它开发了一个协作传感和感知框架，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，从而提供扩展的感知范围和遮挡物体的检测。关键的技术贡献是确保良好的可扩展性——尽管网络资源有限且波动，但允许许多移动车辆有效地共享数据。第三，它支持跨车辆和基础设施的分区计算，以满足 CAV 应用的实时要求。第四，整合上述网络、传感和计算的构建模块，研究团队将开发一个优化框架，该框架可以对需要在何处以何种质量执行哪些计算做出自适应、资源感知的决策，以最大限度地提高 CAV 的服务质量该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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