交通运输:从开放数据方法的概述

Yussef Parcianello, N. P. Kozievitch, K. Fonseca, M. Rosa, T. Gadda, Francisco C. Malucelli
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引用次数: 5

摘要

不断增长的城市人口对交通解决方案提出了新的需求。交通拥堵或交通连接效率低下的影响直接影响公共健康(例如排放、压力)和城市经济(道路交通事故死亡、生产力、通勤等)。与此同时,技术的进步使人们更容易获得构成城市信息系统的系统的数据。这种情况的结果是大量的数据,每天都在增长,需要有效的处理才能转化为集成和有用的信息。本文旨在从开放数据和数据科学的角度对城市公共交通进行分析。我们专注于智慧城市应用的数据集成挑战,并提出了一个数据使用的用例,以限制执行速度。我们还对纽约和库里提巴的数据收集和处理方法进行了初步比较分析。研究结果揭示了需要克服的挑战,包括文件格式、参考系统、精度、准确性和数据质量等,这些挑战仍然需要有效的方法来方便地为新服务开发开放数据。我们讨论了可能用于优化公共交通系统的数据特征,旨在实现全球交通数据标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transportation: An Overview from Open Data Approach
The increasing urban population sets new demands for mobility solutions. The impacts of traffic congestions or inefficient transit connectivity directly affect public health (emissions, stress, for example) and the city economy (deaths in road accidents, productivity, commuting, etc). In parallel, the advance of technology has made it easier to obtain data about the systems which make up the city information systems. The result of this scenario is a large amount of data, growing every day and requiring effective handling in order to be transformed into integrated and useful information. This article aims to analyze the urban public transportation from the perspective of open data and data science. We focus on data integration challenges for smart city applications and present an use case of data usage to speed limit enforcement. We also present an initial comparative analysis of New York and Curitiba data collection and processing approaches. The results unveil challenges to overcome regarding file formats, reference systems, precision, accuracy and data quality, among others, that still need effective approaches to easy open data exploitation for new services. We discuss data characteristics that can possibly be used to optimize public transportation systems aiming at standards for transportation data worldwide.
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