ERI: From Data to Design: Enhancing Pedestrian Infrastructure for Well-Being through Mobile Sensing and Experience Sampling in the Wild

ERI：从数据到设计：通过移动传感和野外体验采样增强行人基础设施以促进福祉

• 批准号: 2347012
• 负责人: Arash Tavakoli
• 金额: $ 19.99万
• 依托单位: Villanova University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2347012&HistoricalAwards=false
• 关键词: ERI; Data; Design; Enhancing; Pedestrian

This Engineering Research Initiation (ERI) award will advance research in understanding the impact of pedestrian infrastructure on various aspects of well-being, including emotions, stress, and cognitive abilities. Pedestrian infrastructure plays a crucial role in influencing well-being metrics and can either encourage or discourage walking as a mode of transportation, even in areas with safe walkways. By employing innovative human sensing techniques, this project will establish a comprehensive pedestrian data collection framework. Through collaboration with practitioners and road users in focus groups, alternative infrastructure designs will be developed and evaluated using immersive virtual environments. This research bridges the gap between real-world data, infrastructure design, and behavioral aspects of walking adoption. This project has the potential to drive positive changes in urban planning, design, and public policy through data-driven insights. The resulting naturalistic dataset can benefit research in various disciplines such as behavioral science, psychology, and computer science. This project will bring opportunities for graduate and undergraduate researchers as well as Ph.D. students from all walks of life to learn, grow, become trained in an academic environment, and contribute to the science of human-centered infrastructure design.Current pedestrian research predominantly concentrates on safety, leaving a substantial gap in well-being-related data, especially in real-world settings. Well-being metrics while including physical aspects, encompass different parameters such as perceived stress, valence, and arousal and emotion metrics, creativity, social interactions, and cognitive abilities among other factors. The first component of this study introduces a novel naturalistic framework to comprehensively monitor and collect data on various aspects of pedestrian well-being. This framework intelligently integrates data from mobile sensing devices, such as smartwatches, with in-the-wild experience sampling techniques through a specifically designed app. In the second component, this framework is applied in a suburban area to create a first-of-its-kind, longitudinal, and naturalistic dataset, addressing the scarcity of pedestrian well-being data. This component will yield quantitative and qualitative models connecting infrastructural elements with real-world pedestrian well-being metrics, employing observational studies and computer vision techniques. The project will develop heatmaps highlighting regions associated with different well-being metrics that will be shared with broader research communities. The third component will result in preliminary guidelines for identifying design flaws in pedestrian infrastructure considering human well-being. Lastly, Immersive Virtual Environments will be utilized to assess alternative designs objectively and subjectively, closing the loop in enhancing pedestrian infrastructure prior to construction.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.

该工程研究启动 (ERI) 奖项将推动研究，了解行人基础设施对福祉各个方面的影响，包括情绪、压力和认知能力。行人基础设施在影响福祉指标方面发挥着至关重要的作用，可以鼓励或阻止步行作为一种交通方式，即使在有安全人行道的地区也是如此。通过采用创新的人体传感技术，该项目将建立一个全面的行人数据收集框架。通过与焦点小组中的从业者和道路使用者合作，将使用沉浸式虚拟环境开发和评估替代基础设施设计。这项研究弥合了现实世界数据、基础设施设计和步行采用行为方面之间的差距。该项目有潜力通过数据驱动的见解推动城市规划、设计和公共政策的积极变化。由此产生的自然数据集可以有利于行为科学、心理学和计算机科学等各个学科的研究。该项目将为研究生和本科生研究人员以及博士生带来机会。来自各行各业的学生在学术环境中学习、成长、接受培训，并为以人为本的基础设施设计科学做出贡献。当前的行人研究主要集中在安全方面，在与福祉相关的数据方面存在很大差距，尤其是在现实世界中。幸福感指标虽然包括身体方面，但还包含不同的参数，例如感知压力、效价、唤醒和情绪指标、创造力、社交互动和认知能力等因素。本研究的第一部分介绍了一种新颖的自然主义框架，以全面监测和收集行人福祉各个方面的数据。该框架通过专门设计的应用程序，智能地将来自移动传感设备（例如智能手表）的数据与野外经验采样技术集成在一起。在第二个部分中，该框架应用于郊区，创建首个同类纵向自然数据集，解决行人福祉数据的稀缺问题。该组件将采用观察研究和计算机视觉技术，产生将基础设施元素与现实世界的行人福祉指标连接起来的定量和定性模型。该项目将开发热图，突出显示与不同福祉指标相关的区域，并将与更广泛的研究社区共享。第三部分将产生初步指南，用于识别考虑到人类福祉的行人基础设施的设计缺陷。最后，沉浸式虚拟环境将用于客观和主观地评估替代设计，从而在施工前关闭增强步行基础设施的循环。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和更广泛的影响进行评估，被认为值得支持审查标准。