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Extracting accurate location information from a highly inaccurate traffic accident dataset: A methodology based on a string matching technique

机译:从高度不准确的交通事故数据集中提取准确的位置信息:一种基于字符串匹配技术的方法

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The objective of this research was to develop a model for validating traffic accident locations that would be applicable worldwide, regardless of linguistic or cultural differences. In order to achieve this, a Volunteered Geographic Information (VGI) dataset was used, the OpenStreetMap (OSM) project. To test the developed model, a total of 8550 accidents with fatal or non-fatal injuries that occurred in the City of Zagreb from 2010 to 2014 were evaluated. Traffic accident data was collected using the pen-and-paper method while the traffic accident locations were determined using Global Positioning System (GPS) receivers embedded within police vehicles. This form of data entry invariably introduces errors in both geometric and contextual attributes. To fully counteract these errors, the developed model consists of two key concepts: the jaro-Winkler string matching technique and the Inverse Distance Weighting method. Over 66% of traffic accident locations were validated, which is an increase of 15% when compared to the classical approach. The model outlined in this paper shows a significant improvement in estimating the correct location of traffic accidents. This in turn results in a drastic decrease in resources needed to estimate the quality of accident locations. (C) 2016 The Authors. Published by Elsevier Ltd.
机译:这项研究的目的是开发一种模型来验证交通事故发生地点,该模型将在全球范围内适用,无论语言或文化差异如何。为了实现此目的,使用了“自愿地理信息”(VGI)数据集,即OpenStreetMap(OSM)项目。为了测试开发的模型,评估了2010年至2014年在萨格勒布市发生的8550起致命或非致命伤害事故。使用纸笔法收集交通事故数据,而使用嵌入在警车中的全球定位系统(GPS)接收器确定交通事故位置。这种数据输入形式总是会在几何和上下文属性中引入错误。为了完全抵消这些错误,开发的模型包含两个关键概念:jaro-Winkler字符串匹配技术和反距离权重方法。超过66%的交通事故地点得到了验证,与传统方法相比,增加了15%。本文概述的模型显示出在估计交通事故的正确位置方面的重大改进。反过来,这导致估计事故地点质量所需的资源急剧减少。 (C)2016作者。由Elsevier Ltd.发布

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