标题： 通过人工智能分割卫星图像将行人过街分析扩展到100个美国城市 显示英文标题

标题： Scaling Pedestrian Crossing Analysis to 100 U.S. Cities via AI-based Segmentation of Satellite Imagery

摘要： 准确测量街道尺寸对于评估其设计如何影响出行行为和安全性至关重要。 然而，鉴于城市交叉口的数量和复杂性，以高精度在城市规模上收集街道层面的信息是困难的。 为了应对这一挑战，在行人横穿道路这一影响步行性的关键组成部分的背景下，我们引入了一种可扩展且准确的方法，用于自动测量标记和未标记人行横道的横穿距离，并应用于美国最大的100个城市。 首先，使用OpenStreetMap坐标检索每个城市中交叉口的卫星图像，总计约三百万张图像。 接下来，对这些图像中手动标注的子集进行训练，以区分可行驶表面和不可行驶表面（即道路与人行道）。 第三，提取OpenStreetMap中所有可用的横穿边缘。 最后，将横穿边缘叠加在分割后的交叉口图像上，并应用生长切割算法将每条边缘连接到相邻的不可行驶表面（例如，人行道、私人财产等），从而实现横穿距离的计算。 与整个城市的手动验证数据相比，该方法在测量横穿距离方面达到了93%的准确率，中位数绝对误差为2英尺3英寸（0.69米）。 在美国最大的100个城市中，中位数横穿距离从32英尺到78英尺（9.8至23.8米）不等，并显示出可检测的区域模式。 中位数横穿距离还与城市成立年份呈正相关，以一种新颖的方式说明了美国城市越来越强调更宽（以及更以汽车为中心）的街道。 显示英文摘要

摘要： Accurately measuring street dimensions is essential to evaluating how their design influences both travel behavior and safety. However, gathering street-level information at city scale with precision is difficult given the quantity and complexity of urban intersections. To address this challenge in the context of pedestrian crossings - a crucial component of walkability - we introduce a scalable and accurate method for automatically measuring crossing distance at both marked and unmarked crosswalks, applied to America's 100 largest cities. First, OpenStreetMap coordinates were used to retrieve satellite imagery of intersections throughout each city, totaling roughly three million images. Next, Meta's Segment Anything Model was trained on a manually-labelled subset of these images to differentiate drivable from non-drivable surfaces (i.e., roads vs. sidewalks). Third, all available crossing edges from OpenStreetMap were extracted. Finally, crossing edges were overlaid on the segmented intersection images, and a grow-cut algorithm was applied to connect each edge to its adjacent non-drivable surface (e.g., sidewalk, private property, etc.), thus enabling the calculation of crossing distance. This achieved 93 percent accuracy in measuring crossing distance, with a median absolute error of 2 feet 3 inches (0.69 meters), when compared to manually-verified data for an entire city. Across the 100 largest US cities, median crossing distance ranges from 32 feet to 78 feet (9.8 to 23.8m), with detectable regional patterns. Median crossing distance also displays a positive relationship with cities' year of incorporation, illustrating in a novel way how American cities increasingly emphasize wider (and more car-centric) streets.