Navigation and orientation while walking in urban spaces pose serious challenges for blind pedestrians, sometimes even on a daily basis. Research shows the practicability of computerized weighted network route planning algorithms based on OpenStreetMap mapping data for calculating customized routes for blind pedestrians. While data about pedestrians and vehicle traffic flow at different times throughout the day influence the route choices of blind pedestrians, such data do not exist in OpenStreetMap. Quantifying the correlation between spatial structure and traffic flow could be used to fill this gap. As such, we investigated machine‐learning methods to develop a computerized model for predicting pedestrian traffic flow levels, with the objective of enriching the OpenStreetMap database. This article presents prediction results by implementing six machine‐learning algorithms based on parameters relating to the geometrical and topological configuration of streets in OpenStreetMap, as well as points‐of‐interest such as public transportation and shops. The Random Forest algorithm produced the best results, whereby 95% of the testing data were successfully predicted. These results indicate that machine‐learning algorithms can accurately generate necessary temporal data, which when combined with the available crowdsourced open mapping data could augment the reliability of route planning algorithms for blind pedestrians.

中文翻译：

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针对行人交通流量水平的机器学习预测模型：为盲人行人优化步行路线

在城市空间中行走时的导航和定向给盲人行人带来了严峻的挑战，有时甚至是每天。研究表明，基于OpenStreetMap映射数据的计算机加权网络路线规划算法可用于计算盲人行人定制路线。尽管全天不同时间的行人和车辆流量数据会影响盲人行人的路线选择，但OpenStreetMap中不存在此类数据。量化空间结构与交通流量之间的相关性可用于填补这一空白。因此，我们研究了机器学习方法，以开发一种计算机模型来预测行人交通量，目的是丰富OpenStreetMap数据库。本文通过基于与OpenStreetMap中街道的几何和拓扑配置有关的参数以及诸如公共交通和商店之类的关注点的参数，实施六种机器学习算法来提供预测结果。随机森林算法产生了最佳结果，从而成功预测了95％的测试数据。这些结果表明，机器学习算法可以准确地生成必要的时间数据，当与可用的众包开放地图数据结合使用时，可以提高盲人行人路线规划算法的可靠性。随机森林算法产生了最佳结果，从而成功预测了95％的测试数据。这些结果表明，机器学习算法可以准确地生成必要的时间数据，当与可用的众包开放地图数据结合使用时，可以提高盲人行人路线规划算法的可靠性。随机森林算法产生了最佳结果，从而成功预测了95％的测试数据。这些结果表明，机器学习算法可以准确地生成必要的时间数据，当与可用的众包开放地图数据结合使用时，可以提高盲人行人路线规划算法的可靠性。