Estimation of origin-destination matrices by fusing detector data and Floating Car Data

被引:8
|
作者
Vogt, Sebastian [1 ]
Fourati, Walid [1 ]
Schendzielorz, Tobias [2 ]
Friedrich, Bernhard [1 ]
机构
[1] Tech Univ Carolo Wilhelmina Braunschweig, Inst Transportat & Urban Engn, Hermann Blenk Str 42, D-38108 Braunschweig, Germany
[2] SCHLOTHAUER & WAUER GmbH, Richard Reitzner Allee 1, D-85540 Haar, Germany
关键词
Floating Car Data; traffic distribution; data fusion;
D O I
10.1016/j.trpro.2018.12.216
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Neither traffic detector counts nor Floating Car Data are able to determine the absolute traffic demand with sufficient accuracy. Therefore, traffic management depends on simple and often inaccurate estimations. In recent years, various research projects have shown that plausible results can be achieved from mere road detector data by applying the Information Minimization model and eliminating redundant information. However, a problem that has not yet been solved in this approach is the lack of information about the structure of traffic demand. This can be extracted from Floating Car Data. To merge both pieces of information into one consistent model the present paper introduces a methodology based on the work of Pohlmann utilizing the Information Minimization Model by Van Zuylen. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:473 / 480
页数:8
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