Revealing reliable information from taxi traces: from raw data to information discovery

A. Keskinarkaus, Ekaterina Gilman, Lauri Lovén, S. Tamminen, M. Hippi, G. Xiong, F. Zhu, T. Seppanen, J. Riekki, S. Pirttikangas
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Abstract

In this paper we present procedures for processing raw data collected with moving vehicles and for fusing this data with digital map data. The goal is to have a better understanding of the city traffic via quantitative research on collected taxi data in relation to digital map properties. Map attributes are provided by Digiroad, which is a database of Finnish road and street network. We define methods to clean up data that has been collected with taxis equipped with on-board vehicle tracking devices from real customer service situations. Consequently, the driving behavior may be inconsistent and sensor data can be limited and contain errors. We explain procedures of preparing data; filtering the most obvious errors from the data set, map-matching moving object data, and fetching map attributes along the routes of the moving vehicles. The fetched properties, as well as other measurement data, are used for deriving statistics and illustrations to study driving behavior in downtown Oulu, Finland.
从出租车痕迹中揭示可靠信息:从原始数据到信息发现
在本文中,我们提出了处理移动车辆收集的原始数据并将这些数据与数字地图数据融合的程序。目标是通过对收集到的出租车数据与数字地图属性的关系进行定量研究,更好地了解城市交通。地图属性由Digiroad提供,这是芬兰道路和街道网络的数据库。我们定义了从实际客户服务情况中清理配备车载车辆跟踪装置的出租车收集的数据的方法。因此,驾驶行为可能不一致,传感器数据可能有限并包含错误。我们解释准备数据的程序;从数据集中过滤最明显的错误,地图匹配移动对象数据,并沿着移动车辆的路线获取地图属性。获取的属性以及其他测量数据用于导出统计数据和插图,以研究芬兰奥卢市中心的驾驶行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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