SCC-IRG Track 1: Crowd+AI Tools to Map, Analyze, and Visualize Sidewalk Accessibility for Inclusive Cities

尽管针对美国残疾人的民权立法已经实施了几十年，但许多城市的人行道仍然无法通行。一个关键问题是缺乏关于人行道的位置和质量的可靠数据。这种数据的缺乏从根本上限制了对城市中人行道可达性的研究，限制了社区、倡导团体和地方政府理解、透明讨论和做出明智规划决策的能力，也限制了如何将人行道和可达性纳入交互式地图、导航和地理信息系统分析工具。该提案旨在(1)促进对利益相关者需求的理解，并利用社会技术工具来评估和规划无障碍人行道；(2)开发和评估人群+人工智能人行道数据收集和评估技术，以提高可扩展性和可靠性，更好地支持不同利益相关者的需求；(3)开发并评价一套开放源代码的城市可达性分析和可视化工具。为了实现这些目标，该项目的跨学科团队将通过参与式设计方法、众包、利益相关者焦点小组和访谈，与城市和交通规划者、政府领导人、残疾人倡导者（如EasterSeals——也作为共同牵头人参与）和残疾人合作。这项工作为人机交互、城市规划和残疾研究做出了基础性贡献。首先，本项目将增进对利益相关者需求的了解，并利用社会技术工具支持无障碍人行道规划、公民参与、宣传和出行规划。其次，该项目将开发新的数据收集和评估技术，这些技术将贡献新的基于ml的算法、人群+人工智能工作流和质量控制机制，从而提高可扩展性、可靠性，并更好地支持不同利益相关者的需求。拟议的人群+人工智能方法将加强对挑战、问题和未来机会的理解，使残疾人参与智慧城市的公民参与。第三，该项目将开发和评估一套开源的人行道可达性分析和可视化工具，这些工具由我们的数据收集技术独特地实现，以帮助城市规划者和交通机构制定《美国残疾人法》的过渡计划，以改善人行道可达性，使行人和残疾人倡导者能够检查无障碍的地理空间模式并审查政府进展，并帮助残疾人安全，无障碍移动决策。所提出的数据收集和可视化工具有可能改变人行道可达性数据的收集和分析方式，城市如何规划和改善人行道可达性，以及城市基础设施资金如何分散。这些工具和数据将是开源的，使其他人能够利用我们的工作，包括超过80%尚未计划拆除人行道障碍的美国城市。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Despite decades of civil rights legislation for Americans with disabilities, many city sidewalks remain inaccessible. A key problem is the lack of reliable data on where sidewalks exist and their quality. This lack of data fundamentally limits how sidewalk accessibility can be studied in cities, the ability for communities, advocacy groups, and local governments to understand, transparently discuss, and make informed planning decisions, and how sidewalks and accessibility are incorporated into interactive map, navigation, and Geographic Information Systems analysis tools. This proposal aims to (1) advance understanding of stakeholder needs and opportunities for socio-technical tools to assess and plan for accessible sidewalks; (2) develop and evaluate crowd+AI sidewalk data collection and assessment techniques to improve scalability, reliability, and better support diverse stakeholder needs; and (3) develop and evaluate a suite of open-source urban accessibility analysis and visualization tools. To address these aims, this project's cross-disciplinary team will work with urban and transportation planners, government leaders, disability advocates (e.g. EasterSeals - which also is participating as a Co-PI) and people with disabilities via participatory-design methods, crowdsourcing and stakeholder focus groups and interviews.The proposed work makes foundational contributions to Human Computer Interaction, urban planning, and disability studies. First, this project will advance understanding of stakeholder needs and opportunities for socio-technical tools to support planning of accessible sidewalks, civic engagement, advocacy, and trip planning. Second, this project will develop new data collection and assessment techniques that will contribute new ML-based algorithms, crowd+AI workflows, and quality control mechanisms that improve scalability, reliability, and better support diverse stakeholder needs. The proposed crowd+AI approaches will enhance understanding of the challenges, concerns, and future opportunities for engaging people with disabilities in smart cities civic participation. Third, this project will develop and evaluate a suite of open-source sidewalk accessibility analysis and visualization tools, which are uniquely enabled by our data collection techniques, to help urban planners and transit agencies develop ADA transition plans for improving sidewalk accessibility, enable pedestrian and disability advocates to examine geo-spatial patterns of inaccessibility and review government progress, and help people with disabilities make safe, accessible mobility decisions. The proposed data collection and visualization tools have the potential to transform how sidewalk accessibility data is collected and analyzed, how cities plan for and improve sidewalk accessibility, and how infrastructure funding is dispersed in cities. The tools and data will be open sourced, enabling others to build off our work—including the over 80% of US cities that do not yet have plans to remove sidewalk barriers.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.