IUCRC Planning Grant University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)

IUCRC 规划拨款北德克萨斯大学：电动、互联和自主移动技术中心 (eCAT)

• 批准号: 2113805
• 负责人: Song Fu
• 金额: $ 2万
• 依托单位: University of North Texas
• 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: 2021-07-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2113805&HistoricalAwards=false
• 关键词: IUCRC; Planning; Grant; University; North

While autonomous vehicle companies focus on manufacturing driverless cars, electrification and connectivity technologies can upgrade the industry by allowing vehicles to communicate with the driving circumstance to achieve better safety with less emission. A key obstacle to the development of the electric, connected and autonomous vehicle system is the shortage of synergy research from needed domains. The proposed Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT) will concentrate on interdisciplinary research, aiming to initiate and accelerate the transformation of mobility methods from conventional vehicles to electric, connected and autonomous vehicles by creating innovative electric, connected and autonomous technologies. A partnership between Wayne State University (WSU), University of North Texas (UNT), and Clarkson University (Clarkson), the center not only serves as an apparatus of academic researchers collaborating with industry on important problems, but also provides industry partners opportunities to access advanced synergic research produced from a diverse group of researchers. The UNT Site will particularly focus on developing novel perception algorithms and system architecture to support connected autonomous vehicles. The UNT’s eCAT will leverage the Connected Autonomous Vehicular System Lab, the Center for Integrated Intelligent Mobility Systems, and long-running relationships with industry to bring significant contributions to the center. The Center will not only advance the science and technologies of electric, connected and autonomous vehicles, but also accelerate both knowledge and intellectual property transfer between academia and industry through collaborative partnerships. This will allow for the rapid transformation of the state-of-the-art mobility technologies from research labs to industry. Educational efforts will be devoted to (1) curriculum design for the BS/MS programs, (2) summer camp development for K-12 students, (3) broadening participation in computing and engineering, at WSU, UNT, and Clarkson. Research results will be disseminated through our annual conference - MetroCAD, publications, and the development of publicly-available open-source projects.Data obtained from this project will include experimental, computational, text-based, and/or curricular data. All data products will be retained for a minimum of three years after conclusion of the award or three years after public release (publication), whichever is later. WSU, UNT, and Clarkson will have password-protected shared network drives to facilitate data sharing within the teams, with collaborators, and indeed anyone in the community with an interest in the NSF-funded data. A landing page for navigation to archived data will be created at http://ecat.center.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.

虽然自动驾驶汽车公司专注于制造无人驾驶汽车，但电气化和连接技术可以通过允许车辆与驾驶环境进行通信来升级行业，以实现更少排放的更好安全性。电动、互联和自动驾驶汽车系统发展的一个关键障碍是缺乏所需领域的协同研究。拟议中的电动、互联和自动驾驶技术中心（eCAT）将专注于跨学科研究，旨在通过创造创新的电动、互联和自动驾驶技术，启动和加速从传统车辆到电动、互联和自动驾驶车辆的移动方式转型。该中心是韦恩州立大学（WSU）、北德克萨斯大学（UNT）和克拉克森大学（克拉克森）之间的合作伙伴关系，不仅是学术研究人员与工业界就重要问题进行合作的机构，而且还为工业合作伙伴提供机会，以获得来自不同研究人员群体的先进协同研究。UNT网站将特别专注于开发新的感知算法和系统架构，以支持联网的自动驾驶汽车。UNT的eCAT将利用互联自动驾驶车辆系统实验室、集成智能移动系统中心以及与行业的长期合作关系，为该中心做出重大贡献。该中心不仅将推进电动、互联和自动驾驶汽车的科学和技术，还将通过合作伙伴关系加速学术界和工业界之间的知识和知识产权转移。这将使最先进的移动技术从研究实验室快速转变为工业。教育工作将致力于（1）BS/MS课程的课程设计，（2）K-12学生的夏令营开发，（3）在WSU，UNT和克拉克森扩大对计算和工程的参与。研究成果将通过我们的年度会议- MetroCAD，出版物和公开的开源项目的开发进行传播。从这个项目中获得的数据将包括实验，计算，基于文本和/或课程数据。所有数据产品将在奖项结束后至少保留三年，或在公开发布（出版）后至少保留三年，以较晚者为准。WSU、UNT和克拉克森将拥有受密码保护的共享网络驱动器，以促进团队内部、合作者以及社区中对NSF资助的数据感兴趣的任何人的数据共享。将在www.example.com上创建一个用于导航到存档数据的着陆页http://ecat.center.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

Privacy-Preserving Object Detection with Secure Convolutional Neural Networks for Vehicular Edge Computing

使用用于车辆边缘计算的安全卷积神经网络进行隐私保护对象检测

• DOI: 10.3390/fi14110316
• 发表时间: 2022
• 期刊: Future Internet
• 影响因子: 3.4
• 作者: Bai, Tianyu;Fu, Song;Yang, Qing
• 通讯作者: Yang, Qing

VECFrame: A Vehicular Edge Computing Framework for Connected Autonomous Vehicles

VECFrame：用于联网自动驾驶车辆的车辆边缘计算框架

• DOI: 10.1109/edge53862.2021.00019
• 发表时间: 2021
• 期刊: 2021 IEEE International Conference on Edge Computing (EDGE
• 作者: Tang, Sihai;Chen, Bruce;Iwen, Harold;Hirsch, Jason;Fu, Song;Yang, Qing;Palacharla, Paparao;Wang, Nannan;Wang, Xi;Shi, Weisong
• 通讯作者: Shi, Weisong

Signal Processing for TDM MIMO FMCW Millimeter-Wave Radar Sensors

• DOI: 10.1109/access.2021.3137387
• 发表时间: 2021-01-01
• 期刊: IEEE ACCESS
• 影响因子: 3.9
• 作者: Li, Xinrong;Wang, Xiaodong;Fu, Song
• 通讯作者: Fu, Song

Online Self-Evolving Anomaly Detection for Reliable Cloud Computing

• DOI: 10.1109/ucc56403.2022.00014
• 发表时间: 2022-12
• 期刊: 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC)
• 作者: Tianyu Bai;Haili Wang;Jingda Guo;Xu Ma;Mahendra Talasila;Sihai Tang;Song Fu;Qing Yang

MLCNN: Cross-Layer Cooperative Optimization and Accelerator Architecture for Speeding Up Deep Learning Applications

MLCNN：用于加速深度学习应用的跨层协作优化和加速器架构

• 发表时间: 2022
• 期刊: 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS
• 作者: Beilei Jiang, Xianwei Cheng