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A new perspective for precision evaluation of large-scale traffic sensor data measurement
Transportation Planning and Technology ( IF 1.6 ) Pub Date : 2020-06-17 , DOI: 10.1080/03081060.2020.1780708 Junseo Bae 1 , Kunhee Choi 2
Transportation Planning and Technology ( IF 1.6 ) Pub Date : 2020-06-17 , DOI: 10.1080/03081060.2020.1780708 Junseo Bae 1 , Kunhee Choi 2
Affiliation
ABSTRACT Use of sensor data has been increasingly common in recent years, yet there is still a knowledge gap in evaluating the precision of traffic sensor data being used in traffic analyses for developing a transportation management plan. This paper fills this gap by exploring a new approach to evaluating the level of precision of large-scale traffic sensor data. The proposed analytical framework incorporates a spatiotemporal domain for the purpose of projecting spatiotemporal characteristics of the data into a repeatability and reproducibility (R&R) study. The main finding of this study is that the proposed framework is effective in examining the precision level of large-scale data spatiotemporally. The proposed framework would be useful for researchers and practitioners to benchmark precision measurements of traffic sensor data in a way to gather quality data and avoid any potential biased result of deeper traffic analyses.
中文翻译:
大规模交通传感器数据测量精度评估的新视角
摘要 近年来,传感器数据的使用越来越普遍,但在评估用于制定交通管理计划的交通分析中使用的交通传感器数据的精度方面仍然存在知识差距。本文通过探索一种评估大规模交通传感器数据精度水平的新方法来填补这一空白。拟议的分析框架结合了一个时空域,目的是将数据的时空特征投影到可重复性和再现性 (R&R) 研究中。本研究的主要发现是,所提出的框架在时空检查大规模数据的精度水平方面是有效的。
更新日期:2020-06-17
中文翻译:
大规模交通传感器数据测量精度评估的新视角
摘要 近年来,传感器数据的使用越来越普遍,但在评估用于制定交通管理计划的交通分析中使用的交通传感器数据的精度方面仍然存在知识差距。本文通过探索一种评估大规模交通传感器数据精度水平的新方法来填补这一空白。拟议的分析框架结合了一个时空域,目的是将数据的时空特征投影到可重复性和再现性 (R&R) 研究中。本研究的主要发现是,所提出的框架在时空检查大规模数据的精度水平方面是有效的。