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Reconciliation of Regional Travel Model and Passive Device Tracking Data

机译:区域旅行模型与被动设备跟踪数据的协调

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The ability to passively track large numbers of mobile devices has generated a lot of excitement in recent years. Traditional travel surveys without GPS tracking, either wholly or in part, seems passé today. However, Global Positioning Satellite (GPS) tracking can only overcome some of the problems associated with travel diary surveys. It can capture missed trips and route choice information, but at increased cost per survey. However, it does nothing to ease the rising cost and difficulty associated with contacting, recruiting, retaining households in the first place, or collecting and processing the data. Passive tracking overcomes these limitations, at the expense of giving up interaction with the device owner. Thus, information about the traveler, trip purpose, and other details must be inferred or lost. The ideal solution is to use both travel diaries and passive tracking together. While techniques for fusing these data are yet to be proven the concept has strong intuitive appeal. Until such techniques emerge the question becomes whether such data can be used on their own, and whether they resemble the output of travel models built using traditional survey data. The opportunity to answer such questions arose recently in the Research Triangle Region of North Carolina, which served as a pilot project for using origin destination data from AirSage as an adjunct to modeling. A detailed analysis of the differences between the AirSage data and the Triangle Regional Model (TRM) has been completed. The differences were subtle in some cases and surprising in others. This paper reports on the findings of this comparison. A brief description of the AirSage data and TRM provides the context for the discussion. Presented in this paper is the methodology for comparing the two data sources along with the results. The results show that the highway assignment using AirSage data is comparable to the highway assignment using model estimated trip tables, supporting the use of passively collected cellular data as a low cost option for travel model validation.
机译:被动跟踪大量移动设备的能力最近引起了极大的兴趣 年。如今,完全或部分不使用GPS跟踪的传统旅行调查似乎已经过时了。 但是,全球定位卫星(GPS)跟踪只能解决某些问题 与旅行日记调查相关。它可以捕获错过的旅程和路线选择信息,但是在 每次调查的成本增加。但是,它并不能减轻与之相关的不断上升的成本和难度。 首先联系,招募,保留住户,或收集和处理数据。 被动跟踪克服了这些限制,但以放弃与设备的交互为代价 所有者。因此,必须推断或丢失有关旅行者,出行目的和其他详细信息。 理想的解决方案是同时使用旅行日记和被动跟踪。而融合技术 这些数据尚未得到证实,该概念具有很强的直观吸引力。在这种技术出现之前 问题在于这些数据是否可以单独使用,以及它们是否类似于 使用传统调查数据构建的旅行模型。最近出现了回答此类问题的机会 位于北卡罗来纳州三角研究区的一个实验项目,该实验使用了来自AirSage的原始目的地数据作为建模的辅助工具。详细分析两者之间的区别 AirSage数据和三角区域模型(TRM)已完成。区别是 在某些情况下微妙,而在另一些情况下则令人惊讶。 本文报告了这种比较的结果。 AirSage数据和TRM的简要说明 提供了讨论的背景。本文介绍的是比较这两种方法的方法 数据源以及结果。结果表明,使用AirSage数据的高速公路分配为 可与使用模型估计行程表的高速公路分配相媲美,支持被动使用 收集蜂窝数据是旅行模型验证的一种低成本选择。

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