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TRIP/STOP Detection in GPS Traces to Feed Prompted Recall Survey

机译:GPS迹线中的跳闸/停止检测,以提供及时的召回调查

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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 toprompted recall surveysbecause those surveys can extend over several weeks. Inaccurate stop detection requires frequent corrections by the users and can cause them to quit.
机译:本文介绍了两种从GPS轨迹中提取行程和停靠点的方法:第一种方法侧重于不运动的周期(停靠点),第二种尝试确定最长的运动周期(行程)。为了确定两种方法的质量,将结果与旅行者确定的停留和行程进行比较;这是通过可视化工具完成的,该可视化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。提出了几个质量指标;为了确定探测器配置设置的最佳值,已使用灵敏度分析对其进行了评估。使用了人迹线(与汽车迹线相反)。个别特定行为似乎对行程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。准确地检测GPS轨迹中的停止和行程对于及时召回调查至关重要,因为这些调查可能会持续数周。不正确的停止检测需要用户进行频繁的更正,并可能导致他们退出。

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