Mortenson Center in Global Engineering, University of Colorado Boulder, Boulder, Colorado, United States of America.
Amazi Yego Ltd., Kigali, Rwanda.
PLoS One. 2020 Oct 26;15(10):e0241379. doi: 10.1371/journal.pone.0241379. eCollection 2020.
Trail bridges can improve access to critical services such as health care, schools, and markets. In order to evaluate the impact of trail bridges in rural Rwanda, it is helpful to objectively know how and when they are being used. In this study, we deployed motion-activated digital cameras across several trail bridges installed by the non-profit Bridges to Prosperity. We conducted and validated manual counting of bridge use to establish a ground truth. We adapted an open source computer vision algorithm to identify and count bridge use reflected in the digital images. We found a reliable correlation with less than 3% error bias of bridge crossings per hour between manual counting and those sites at which the cameras logged short video clips. We applied this algorithm across 186 total days of observation at four sites in fall 2019, and observed a total of 33,800 daily bridge crossings ranging from about 20 to over 1,100 individual uses per day, with no apparent correlation between daily or total weekly rainfall and bridge use, potentially indicating that transportation behaviors, after a bridge is installed, are no longer impacted by rainfall conditions. Higher bridge use was observed in the late afternoons, on market and church days, and roughly equal use of the bridge crossings in each direction. These trends are consistent with the design-intent of these bridges.
步道桥可以改善获得医疗保健、学校和市场等关键服务的机会。为了评估卢旺达农村地区步道桥的影响，客观了解它们的使用方式和时间非常有帮助。在这项研究中，我们在由非营利组织 Bridges to Prosperity 安装的几座步道桥上部署了运动激活的数字摄像机。我们进行并验证了人工计数以建立基准。我们改编了一个开源计算机视觉算法来识别和计算数字图像中反映的桥梁使用情况。我们发现，人工计数和摄像机记录短视频片段的站点之间每小时过桥次数的可靠相关性，误差偏差小于 3%。我们在 2019 年秋季的四个地点总共观察了 186 天，总共观察到 33800 次每天的过桥次数，每天或每周总降雨量和桥梁使用之间没有明显的相关性，这可能表明，在安装桥梁后，交通行为不再受降雨条件的影响。在下午晚些时候、市场日和教堂日，以及每个方向的桥梁过境点大致相等的使用量，观察到更高的桥梁使用量。这些趋势与这些桥梁的设计意图一致。
