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Integrating the Directional Effect of Traffic into Geostatistical Approaches for Travel Time Estimation

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Abstract

With the direct linkage to a travel map system, geostatistical techniques have been recently adopted for urban travel time estimation. Some important traffic characteristics of urban transportation networks, however, have not been adequately addressed in these studies. As an improvement over the existing studies, this study incorporates the directional effect of traffic into several commonly used geostatistical models for travel time estimation. We show that model performance can be significantly enhanced when flow specific properties are explicitly considered in constructing the associated interpolation models. The developed methodology is applied to a set of traffic data collected in the city of Tucson, Arizona during the rush hours. Results demonstrate an average of 20 % reduction in RMSE compared with those by the traditional approaches.

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Authors and Affiliations

  1. School of Geography and Development, University of Arizona, Tucson, AZ, 85721, USA

    Daoqin Tong

  2. Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, 85721, USA

    Wei-Hua Lin

  3. Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands

    Alfred Stein

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  1. Daoqin Tong
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  2. Wei-Hua Lin
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  3. Alfred Stein
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Correspondence to Daoqin Tong.

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Tong, D., Lin, WH. & Stein, A. Integrating the Directional Effect of Traffic into Geostatistical Approaches for Travel Time Estimation. Int. J. ITS Res. 11, 101–112 (2013). https://doi.org/10.1007/s13177-013-0061-0

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  • DOI: https://doi.org/10.1007/s13177-013-0061-0

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