从实时车辆探测数据生成合成O-D需求:潜力和局限性

M. Van Aerde, G. MacKinnon, B. Hellinga
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引用次数: 12

摘要

在中央交通控制中心和所有配备路线引导系统(RGS)的车辆之间提供双向通信,使得非常有效地组装对当前动态或时变O-D(出发地-目的地)矩阵的连续估计成为可能。本文描述了利用车辆探测数据建立时变外径矩阵的四步数学过程,并讨论了最终外径估计的重要统计限制。结果表明,除非在网络中有非常高的市场渗透率,否则所得的OD估计将包含如此高的统计不确定性,使其实际价值有限。因此,预计所得到的OD估计即使在长期内也不是不适合单独使用,相反,这个估计总是需要作为种子解矩阵进一步处理,以供随后的动态合成OD生成分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The generation of synthetic O-D demands from real-time vehicle probe data: Potential and limitations
The provision of two-way communications between the central traffic control center and all vehicles, which are equipped with route guidance systems (RGS), makes it possible to assemble very efficiently a continuous estimate of the prevailing dynamic or time-varying O-D (Origin-Destination) matrix. This paper describes the mathematics of a four step procedure for developing such a time varying OD matrix from vehicle probe data and discusses the important statistical limitations of the final OD estimates. It is shown that, unless there is a very high level of market penetration in the network, the resulting OD estimate will contain such a high level of statistical uncertainty as to render it of limited practical value. consequently, it is anticipated that the resulting OD estimate will even in the long term not be unsuitable to be utilized on its own, and that instead this estimate will always need to be further processed as a seed solution matrix for a subsequent dynamic synthetic OD generation analysis.
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