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

IUCRC 第一阶段北德克萨斯大学：电动、互联和自主移动技术中心 (eCAT)

• 批准号: 2231519
• 负责人: Song Fu
• 金额: $ 60万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2028-02-29
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2231519&HistoricalAwards=false
• 关键词: IUCRC; Phase; University; North; Texas

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 accelerate the transformation of mobility methods from conventional vehicles to electric, connected and autonomous vehicles by creating innovative electric, connected and autonomous technologies. 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 University of North Texas (UNT) Site will particularly focus on developing novel perception algorithms and system architecture to support connected autonomous vehicles. The UNT Site will leverage the Connected Autonomous Vehicular System Lab, the Vehicle and Edge Computing Lab, and the Center for Integrated Intelligent Mobility Systems, as well as the long-running relationships with industry to bring significant contributions to the Center. The Center will advance the science and technologies of electric, connected and autonomous vehicles, and 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. Education and workforce development 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. Research results will be disseminated through our annual conference, publications, and the development of 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. The Sites of the Center 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，但电气化和互联技术可以通过允许车辆与驾驶环境进行通信来升级行业，以实现更好的安全性和更少的排放。电动、互联和自动驾驶汽车系统发展的一个主要障碍是缺乏所需领域的协同研究。拟建的电动、网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、网联和自动驾驶技术，加速移动方式从传统车辆向电动、网联和自动驾驶汽车的转变。该中心不仅充当学术研究人员与工业界就重要问题进行合作的机构，而且还为工业界合作伙伴提供获得来自不同研究人员群体的先进协同研究的机会。北德克萨斯大学 (UNT) 站点将特别专注于开发新颖的感知算法和系统架构，以支持联网自动驾驶汽车。 UNT 站点将利用互联自动驾驶车辆系统实验室、车辆和边缘计算实验室、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。该中心将推进电动、互联和自动驾驶汽车的科学技术，并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界。教育和劳动力发展工作将致力于 (1) BS/MS 课程的课程设计，(2) K-12 学生的夏令营开发，(3) 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、出版物和开源项目的开发来传播。从该项目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公开发布（出版）后三年，以较晚者为准。该中心的站点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 http://ecat.center 创建导航至存档数据的登陆页面。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点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

Perception Workload Characterization and Prediction on the Edges with Memory Contention for Connected Autonomous Vehicles

互联自动驾驶车辆边缘的感知工作负载表征和内存争用预测

• DOI: 10.1109/edge60047.2023.00026
• 发表时间: 2023-07
• 期刊: 2023 IEEE International Conference on Edge Computing and Communications (EDGE
• 作者: Tang, Sihai;Wang, Shengze;Fu, Song;Yang, Qing
• 通讯作者: Yang, Qing

Sniffer Faster R-CNN ++: An Efficient Camera-LiDAR Object Detector with Proposal Refinement on Fused Candidates

Sniffer Faster R-CNN：一种高效的相机激光雷达目标检测器，可对融合候选者进行建议细化

• DOI: 10.1145/3631138
• 发表时间: 2023-10
• 期刊: ACM Journal on Autonomous Transportation Systems
• 作者: Dhakal, Sudip;Carrillo, Dominic;Qu, Deyuan;Yang, Qing;Fu, Song
• 通讯作者: Fu, Song

Output-Directed Dynamic Quantization for DNN Acceleration

用于 DNN 加速的输出导向动态量化

• DOI: 10.1145/3605573.3605580
• 发表时间: 2023-08
• 期刊: ACM
• 作者: Jiang, Beilei;Cheng, Xianwei;Li, Yuan;Zhang, Jocelyn;Fu, Song;Yang, Qing;Liu, Mingxiong;Olvera, Alejandro
• 通讯作者: Olvera, Alejandro

User-Defined Privacy Preserving Data Sharing for Connected Autonomous Vehicles Utilizing Edge Computing

利用边缘计算为联网自动驾驶车辆提供用户定义的隐私保护数据共享

• 发表时间: 2023-12
• 期刊: 2023 IEEE/ACM Symposium on Edge Computing (SEC
• 作者: Tianyu Bai; Qing Yang
• 通讯作者: Qing Yang

P3: A Privacy-Preserving Perception Framework for Building Vehicle-Edge Perception Networks Protecting Data Privacy

P3：用于构建保护数据隐私的车辆边缘感知网络的隐私保护感知框架

• DOI: 10.1109/icccn58024.2023.10230191
• 发表时间: 2023-07
• 期刊: IEEE
• 作者: Bai, Tianyu;Shao, Danyang;He, Ying;Fu, Song;Yang, Qing
• 通讯作者: Yang, Qing