Project Sidewalk is a web-based platform that enables crowdsourcing accessibility of sidewalks at city-scale by virtually walking through city streets using Google Street View. The tool has been used in 40 cities across the world, including the US, Mexico, Chile, and Europe. In this paper, we describe adaptation efforts to enable deployment in Chandigarh, India, including modifying annotation types, provided examples, and integrating VLM-based mission guidance, which adapts instructions based on a street scene and metadata analysis. Our evaluation with 3 annotators indicates the utility of AI-mission guidance with an average score of 4.66. Using this adapted Project Sidewalk tool, we conduct a Points of Interest (POI)-centric accessibility analysis for three sectors in Chandigarh with very different land uses, residential, commercial and institutional covering about 40 km of sidewalks. Across 40 km of roads audited in three sectors and around 230 POIs, we identified 1,644 of 2,913 locations where infrastructure improvements could enhance accessibility.

翻译：Sidewalk项目是一个基于网络的平台，通过使用谷歌街景虚拟行走于城市街道，实现城市尺度人行道无障碍性的众包评估。该工具已在全球40个城市得到应用，包括美国、墨西哥、智利和欧洲国家。本文描述了为在印度昌迪加尔部署该工具所做的适应性改进工作，包括修改标注类型、提供示例以及集成基于视觉语言模型的任务引导系统——该系统能根据街景图像和元数据分析动态调整任务指令。我们通过3名标注员进行的评估表明，AI任务引导具有显著效用，平均评分为4.66分。利用改进后的Sidewalk工具，我们对昌迪加尔三个具有截然不同土地用途（居住区、商业区和机构区）的片区开展了以兴趣点为中心的无障碍性分析，覆盖约40公里人行道。在对三个片区总计40公里道路及约230个兴趣点的审计中，我们在2913个定位点中识别出1644处可通过基础设施改造提升无障碍性的位置。