REU Site: Vehicular Edge Computing and Security: Research Experience for Undergraduates

REU 网站：车辆边缘计算和安全：本科生的研究经验

• 批准号: 1852134
• 负责人: Song Fu
• 金额: $ 36万
• 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: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1852134&HistoricalAwards=false
• 关键词: REU; Site; Vehicular; Edge; Computing

This Research Experiences for Undergraduates (REU) Site award funds a new REU Site at the University of North Texas. The site will recruit undergraduates from across the nation to participate in research involving vehicular edge computing and security. The topic is important and timely due to the high demand for dependable, reliable, and secure autonomous cars. The students will work in teams to develop technologies and apply them to electric cars equipped with a variety of sensors. The students will participate in a variety of related professional development activities. The REU experience provides students with the foundations and inspiration to pursue computing careers and research in areas that are rapidly evolving and essential for the technical workforce of the future.The project is led by an outstanding team offering state-of-the art facilities and professional mentors to guide undergraduates in explorations of cutting-edge problems related to vehicular edge computing and security. Project topics include hierarchical edge computing architecture, vehicular sensing data processing, trustworthy information dissemination, and privacy protection of sensing data on vehicles. The site is run with a problem-based, team-oriented approach. The goals are to expose undergraduates to real-world and innovative research focused on vehicular edge systems and security by system design, to motivate more undergraduates to continue their academic careers and seek graduate degrees in computer science and engineering, and to develop research skills and improve communication and collaboration skills. The team will strive to attract students from groups under-represented in computing, particularly students from small colleges with limited research opportunities. Thus, the project has the potential to produce a new generation of computer science graduate students and computing professionals and to advance discovery and understanding while promoting learning.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.

本科生研究经验 (REU) 站点奖励资助北德克萨斯大学新的 REU 站点。 该网站将招募全国各地的本科生参与涉及车辆边缘计算和安全的研究。由于对可靠、可靠和安全的自动驾驶汽车的高需求，这个主题非常重要和及时。学生们将分组合作开发技术并将其应用于配备各种传感器的电动汽车。学生将参加各种相关的专业发展活动。 REU 的经验为学生在快速发展且对未来技术劳动力至关重要的领域追求计算机职业和研究提供了基础和灵感。该项目由一支优秀的团队领导，提供最先进的设施和专业知识导师指导本科生探索与车辆边缘计算和安全相关的前沿问题。项目主题包括分层边缘计算架构、车辆传感数据处理、可信信息传播以及车辆传感数据的隐私保护。 该网站采用以问题为基础、以团队为导向的方法运行。 目标是通过系统设计让本科生接触到以车辆边缘系统和安全为重点的现实世界和创新研究，激励更多本科生继续他们的学术生涯并攻读计算机科学与工程研究生学位，并发展研究技能并提高沟通和协作能力。该团队将努力吸引计算机领域代表性不足的群体的学生，特别是来自研究机会有限的小型学院的学生。 因此，该项目有潜力培养新一代计算机科学研究生和计算机专业人员，并在促进学习的同时促进发现和理解。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进行评估，被认为值得支持以及更广泛的影响审查标准。

项目成果

CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles

CoFF：用于自动驾驶车辆 3D 物体检测的协作空间特征融合

• DOI: 10.1109/jiot.2021.3053184
• 发表时间: 2021-01
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Guo, Jingda;Carrillo, Dominic;Tang, Sihai;Chen, Qi;Yang, Qing;Fu, Song;Wang, Xi;Wang, Nannan;Palacharla, Paparao
• 通讯作者: Palacharla, Paparao

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: 2022-11
• 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: 2021-09
• 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

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: 2023-10-28
• 期刊: Journal on Autonomous Transportation Systems
• 作者: Sudip Dhakal;Dominic Carrillo;Deyuan Qu;Qing Yang;Song Fu
• 通讯作者: Song Fu

F-cooper: feature based cooperative perception for autonomous vehicle edge computing system using 3D point clouds

F-cooper：使用 3D 点云的自动驾驶车辆边缘计算系统基于特征的协作感知

• DOI: 10.1145/3318216.3363300
• 发表时间: 2019-09-13
• 期刊: Proceedings of the 4th ACM/IEEE Symposium on Edge Computing
• 作者: Qi Chen