International Conference on Ambient Systems , Networks and Technologies ( ANT 2015 ) TRIP / STOP Detection in GPS Traces to Feed Prompted Recall Survey
International Conference on Ambient Systems , Networks and Technologies ( ANT 2015 ) TRIP / STOP Detection in GPS Traces to Feed Prompted Recall Survey
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环境系统、网络和技术国际会议 (ANT 2015) GPS 轨迹中的 TRIP/STOP 检测以反馈提示召回调查
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发表时间：
2015
期刊：
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通讯作者：
Geert Wetsa
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作者：
Glenn Cicha;Luk Knapena;Tom Bellemansa;Davy Janssensa;Geert Wetsa
本文提出了两种从 GPS 轨迹中提取行程和停留的方法：第一种方法侧重于非运动（停留）时间段，第二种方法尝试识别最长的运动时间段（行程）。为了断言这两种方法的质量，将结果与旅行者确定的停靠点和行程进行比较；这是通过视觉工具完成的，该工具旨在将日记中手动报告的时间段与自动记录的 GPS 坐标对齐。提出了多项质量指标；它们已使用灵敏度分析进行评估，以确定探测器配置设置的最佳值。使用了人的痕迹（而不是汽车的痕迹）。个体特定行为似乎对跳闸和停止检测器算法中使用的阈值设置的最佳值有很大影响。准确检测 GPS 轨迹中的停靠点和行程对于提示召回调查至关重要，因为这些调查可能会持续数周。不准确的停止检测需要用户频繁纠正，并可能导致他们退出。 c © 2015 作者。由 Elsevier B.V. 出版，同行评审由会议计划主席负责。
This paper presents two methods to extract trips and stops from GPS traces: the first one focuses on periods of non-movement (stops) and the second one tries to identify the longest periods of movement (trips). In order to assert the quality of both methods, the results are compared to stops and trips identified by the traveler; this was done by means of a visual tool aimed at alignment of manually reported periods in the diary to automatically recorded GPS coordinates. Several quality indicators are presented; they have been evaluated using sensitivity analysis in order to determine the optimal values for the detector’s configuration settings. Person traces (as opposed to car traces) were used. Individual specific behavior seems to have a large effect on the optimal values for threshold settings used in both the trip and stop detector algorithms. Accurate detection of stops and trips in GPS traces is vital to prompted recall surveys because those surveys can extend over several weeks. Inaccurate stop detection requires frequent corrections by the users and can cause them to quit. c © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Conference Program Chairs.