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: 2234517
• 负责人: Anindya Maiti
• 金额: $ 20.59万
• 依托单位: University of Oklahoma Norman Campus
• 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
• 起止时间: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2234517&HistoricalAwards=false
• 关键词: Collaborative; Research; CCRI; New; ScooterLab

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.

微移动车辆，如电池供电的电动滑板车，正在城市社区迅速普及。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。研究界--包括计算机和数据科学家、工程师和城市规划者--已经开始应对这些挑战，但进展是临时性的，而且缓慢。这主要是由于缺乏微移动基础设施，无法在现实环境和环境中收集不同的骑手、移动性和上下文数据。迫切需要一个大规模和易于使用的研究工具，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，包括一个高度可定制的微型车辆车队。这些电池驱动的车辆将被改造为具有异构传感和远程通信和控制能力，以感知与乘客的移动性，上下文和环境相关的人群感知数据，从而实现（1）多个计算学科的融合研究，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）（微观）流动性、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Web界面，用于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，以促进试验台的使用，并分享试验台数据促成的研究活动成果。ScooterLab车辆除了为参与者提供方便的电动选择外，还将作为人群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（CISE）和其他跨学科领域的研究取得新的突破。通过授权NSF CISE和其他研究社区公开访问这些科学数据集，ScooterLab测试平台将带来变革性的进步。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）、俄克拉荷马州大学（俄克拉荷马州）以及其他合作组织和高等教育机构的微流动性相关和微流动性支持研究。ScooterLab将在全国范围内改善吸引和维持CISE，工程，城市规划和政策教师和学生从事新兴智能交通和移动解决方案的机会。ScooterLab测试平台还将作为UTSA最近在圣安东尼奥市中心推出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举措做出贡献。作为一个少数民族服务机构（59%的西班牙裔和53%的女性），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，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。