阿根廷的计算机无障碍环境
Computing Accessibility Metrics for Argentina
摘要：
我们提出了一个工具来计算距离和旅行时间之间的一组起点和一组目的地，使用不同的交通方式在阿根廷。该工具的输入数据是一组目的地（城市设施或“机会”点的地理参考列表，如公司、学校、医院、公园、银行或零售店等）。以及一组以其地理坐标为特征的起源，这些地理坐标可以被解释为家庭或其他。该工具根据距离或旅行时间以及交通方式（步行、自行车、汽车和公共交通）确定距离每个起点最近的目的地。起点和终点的集合是大型集合，最多可包含数千个点。我们应用和开发的算法，以提高程序的不同部分的可扩展性。对于公共交通网络，我们对每个点的可达线路进行了预处理，并使用四叉树来确定所述点与公交线路路径之间的距离。该项目的第二个目标是仅依赖于开放数据，例如开放街道地图（OSM）数据，并使该工具开源。因此，这一工具的成功开发和实施可能有益于公共部门机构以及非政府组织和其他民间社会组织，这些组织的工作重点是设计和实施公共政策，旨在改善城市的无障碍环境，以此减少空间不平等和社会排斥。
英文摘要：
We present a tool to calculate distances and travel times between a set of origins and a set of destinations, using different modes of transport in Argentina. The input data for the tool is a set of destinations (a geo-referenced list of points of city amenities or "opportunities", such as firms, schools, hospitals, parks, banks or retail, etc.) and a set of origins characterized by their geographic coordinates that could be interpreted as households or other. The tool determines, from each origin, which is the closest destination, depending on the distance or travel time and the mode of transport (on foot, by bicycle, by car, and by public transport). The sets of origins and destinations are large sets, which can contain up to several thousand points. We applied and developed algorithms to improve the scalability of the different parts of the procedure. For the public transportation network, we pre-processed the reachable lines from each point and used quad-trees to determine the distance between said points and the bus line's path. A second objective of this project was to rely only on open data, such as Open Street Map (OSM) data, together with making this tool open source. Therefore, the successful development and implementation of this tool is potentially beneficial to both public sector agencies as well as NGOs and other civil society organizations that focus their work on the design and implementation of public policies, aimed at improving accessibility in cities as a way to reduce spatial inequalities and social exclusion.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
