课题基金 / 基金详情

Collaborative Research: PPoSS: Planning: Scaling Autonomous Vehicle Systems at the Edge: from On-Board Processing to Cloud Infrastructure

Collaborative Research: PPoSS: Planning: Scaling Autonomous Vehicle Systems at the Edge: from On-Board Processing to Cloud Infrastructure
合作研究:PPoSS:规划:扩展边缘自主车辆系统:从车载处理到云基础设施
批准号:
2118202
负责人:
Daniel Grosu
金额:
$16.38万
依托单位:
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
项目状态:
已结题
起止时间:
2021-07-15 至 2023-06-30

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The focus of this project is on Connected and Autonomous Vehicles (CAVs) and the smart city infrastructure supporting their operation. Current CAV and smart city infrastructure systems do not scale well with the increasing number of applications and are overwhelmed with massive amounts of data collected from embedded, roadside, and edge devices. As more infrastructure and vehicle sensors begin to collect data, novel techniques and methodologies are required to improve the scalability of these systems. The project’s novelties are developments of principles, abstractions, and methodologies for the design and implementation of scalable systems for CAVs and the smart city infrastructure supporting the operation of CAVs. The project's impacts are in the development and deployment of CAVs which will lead to a safer, cleaner, and more efficient transportation. This project develops: (1) theoretical models, frameworks, and software libraries to support the design and implementation of scalable parallel algorithms on heterogeneous CAV platforms; (2) a highly-scalable system for opportunistic offloading of CAV applications to the cloud/edge that will perform on-CAV mixed-criticality scheduling and task-offloading selection, edge-performance-aware vehicle path planning, and multi-hop secure and private offloading; (3) a scalable and secure real-time collaborative detection system in which CAVs leverage sensing data from their on-board sensors and neighboring vehicles; (4) scalable, adaptive traffic-signal and CAV-trajectory coordination protocols via fine-grained sensing of traffic data while addressing the increased computation demands of increased volumes of data; and (5) a programming framework, including libraries and interfaces, that facilitates the development of scalable applications for CAVs and their supporting smart city infrastructure.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.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/tits.2023.3275367
发表时间: 2022-09
期刊: IEEE Transactions on Intelligent Transportation Systems
影响因子: 8.5
作者: [Syeda Tanjila Atik;Marco Brocanelli;Daniel Grosu]
通讯作者: Syeda Tanjila Atik;Marco Brocanelli;Daniel Grosu
DOI: 10.1109/hpcc-dss-smartcity-dependsys57074.2022.00289
发表时间: 2022
期刊: Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys
影响因子: --
作者: [Duncan, Mitchell, Raadia, Fatima, Atik, Syeda Tanjila, Brocanelli, Marco, Fisher, Nathan]
通讯作者: Fisher, Nathan
Data Sharing-Aware Task Allocation in Edge Computing Systems
边缘计算系统中的数据共享感知任务分配
DOI: 10.1109/edge53862.2021.00018
发表时间: 2021
期刊: 2021 IEEE International Conference on Edge Computing (EDGE
影响因子: --
作者: [Rabinia, Sanaz, Mehryar, Haydar, Brocanelli, Marco, Grosu, Daniel]
通讯作者: Grosu, Daniel
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)