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Collaborative Research: CCRI: New: ScooterLab - A Programmable and Participatory Sensing Testbed using Micromobility Vehicles

Collaborative Research: CCRI: New: ScooterLab - A Programmable and Participatory Sensing Testbed using Micromobility Vehicles
合作研究:CCRI:新:ScooterLab - 使用微型移动车辆的可编程和参与式传感测试台
批准号:
2234516
负责人:
Murtuza Jadliwala
金额:
$171.32万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-03-01 至 2026-02-28

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中文摘要
翻译
微型移动车辆,如电池供电的电动滑板车,正在城市社区迅速流行起来。然而,它们也带来了必须解决的重大安全、用户隐私、基础设施和规划挑战。包括计算机和数据科学家、工程师和城市规划师在内的研究界已经开始应对这些挑战,但进展是临时的和缓慢的。这主要可以归因于缺乏微移动基础设施,无法在现实环境中收集不同的骑手、机动性和背景数据。迫切需要一种大规模的、易于获取的研究仪器,以便能够进行这种数据收集。为此,该项目将设计、开发、部署和管理SCooterLab,这是一个社区研究基础设施,包括一支高度可定制的微型移动车辆车队。这些电池驱动的车辆将改装各种传感和远程通信和控制能力,以群体感知与骑手的移动性、背景和环境相关的数据,从而能够进行以下多个计算学科的研究:(1)多个计算学科,包括机器学习、计算机视觉、图像处理、高性能计算、大数据分析和隐私增强技术;(2)(微)移动性、城市规划和交通研究。该项目将为社区研究人员提供精心设计和可用的网络界面,以请求部署定制的传感实验,并访问过去实验和试验中精心策划的数据集。该项目还将定期开展社区外联和参与活动,包括举办讲习班,以促进试验床的使用,并分享试验床数据促成的研究活动的成果。除了为参与者提供方便的电动选择外,SCoterLab车辆还将成为群体感知细粒度、多传感器科学数据的优秀工具,使计算机和信息科学与工程(CEISE)和其他跨学科领域的研究取得新的突破。通过授权NSF Cise和其他研究团体公开访问这些科学数据集,SCooterLab试验台将产生变革性的进步。SCooterLab的成功开发和部署将改变德克萨斯大学圣安东尼奥分校(UTSA)、俄克拉何马大学(OU)以及其他合作组织和高等教育机构与微移动性相关和由微移动性支持的研究。SCooterLab将在全国范围内增加机会,吸引和维持致力于新兴智能交通和移动解决方案的CESE、工程、城市规划和政策学院的教职员工和学生。指示器实验室试验床还将作为UTSA最近成立的位于圣安东尼奥市中心的数据科学学院的基础研究工具,并为该大学减少碳排放的倡议做出贡献。作为一家为少数群体服务的机构(59%为西班牙裔,53%为女性),UTSA将为有色人种和女性提供广泛的研究和参与机会。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Micromobility vehicles, such as battery-powered e-scooters, are rapidly gaining popularity in urban communities. Yet they also present significant safety, user privacy, infrastructure, and planning challenges that must be addressed. The research community –including computer and data scientists, engineers, and urban planners– has started responding to these challenges, but the progress has been ad hoc and slow. This can be primarily attributed to a lack of micromobility infrastructure for collecting diverse rider, mobility, and contextual data in realistic settings and environments. There is a critical need for a large-scale and easily accessible research instrument to enable such data collection. To this end, this project will design, develop, deploy, and manage ScooterLab, a community research infrastructure comprising a highly customizable fleet of micromobility vehicles. These battery-operated vehicles will be retrofitted with heterogeneous sensing and remote communication and control capabilities to crowd-sense data related to riders’ mobility, context, and environment, enabling research at the confluence of (1) multiple computing disciplines, including machine learning, computer vision, image processing, high-performance computing, big data analytics, and privacy-enhancing technologies; and (2) (micro)mobility, urban planning, and transportation research. The project will provide community researchers with well-designed and usable web interfaces for requesting the deployment of customized sensing experiments and for accessing carefully curated datasets from past experiments and trials. The project will also conduct periodic community outreach and engagement activities, including workshops to promote the testbed’s use and share the outcomes of research activities enabled by the testbed data. ScooterLab vehicles, besides providing a convenient, electric option to its participants, will serve as excellent instruments to crowd-sense fine-grained, multi-sensor scientific data, enabling new research breakthroughs in Computer and Information Science and Engineering (CISE) and other interdisciplinary domains. By empowering NSF CISE and other research communities to openly access these scientific datasets, the ScooterLab testbed will engender transformative advancements. Successful development and deployment of ScooterLab will transform micromobility-related and micromobility-supported research at the University of Texas at San Antonio (UTSA), the University of Oklahoma (OU), and other collaborating organizations and institutes of higher education. ScooterLab will improve opportunities nationally for attracting and sustaining CISE, engineering, urban planning, and policy faculty and students working on emerging intelligent transportation and mobility solutions. The ScooterLab testbed will also serve as a foundational research instrument for UTSA’s recently launched School of Data Science located in downtown San Antonio, and contribute to the university’s initiatives to reduce its carbon emissions. As a Minority-Serving Institution (59% Hispanic and 53% Female), UTSA will provide extensive research and participation opportunities for people of color and women.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.
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会议论文
Collaborative Research: CISE-MSI: DP: CNS: Multi-Modal User-Centric Mobility Scooter Driving Safety Assessment System
  • 批准号:
    2318672
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.58万
  • 财政年份:
    2023
  • 负责人:
    Murtuza Jadliwala
  • 依托单位:
Collaborative Research: CISE-MSI: Active and Passive Internet Measurements for Inferring IoT Maliciousness at Scale
  • 批准号:
    2219772
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.0万
  • 财政年份:
    2022
  • 负责人:
    Murtuza Jadliwala
  • 依托单位:
CCRI: Planning: ScooterLab: Development of a Programmable and Participatory e-Scooter Testbed to Enable CISE-focused Micromobility Research
  • 批准号:
    2016717
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.0万
  • 财政年份:
    2020
  • 负责人:
    Murtuza Jadliwala
  • 依托单位:
CAREER: A Holistic Context-based Approach for Security and Privacy in the Era of Ubiquitous Sensing and Computing
  • 批准号:
    1943351
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.95万
  • 财政年份:
    2020
  • 负责人:
    Murtuza Jadliwala
  • 依托单位:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
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