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Understanding the patterns of car travel

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Abstract

Are the patterns of car travel different from those of general human mobility? Based on a unique dataset consisting of the GPS trajectories of 10 million travels accomplished by 150,000 cars in Italy, we investigate how known mobility models apply to car travels, and illustrate novel analytical findings. We also assess to what extent the sample in our dataset is representative of the overall car mobility, and discover how to build an extremely accurate model that, given our GPS data, estimates the real traffic values as measured by road sensors.

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Authors and Affiliations

  1. KDDLab – ISTI – CNR, Pisa, Italy

    Luca Pappalardo, Salvatore Rinzivillo, Zehui Qu & Fosca Giannotti

  2. KDDLab, Department of Computer Science, University of Pisa, Pisa, Italy

    Luca Pappalardo & Dino Pedreschi

  3. College of Computer and Information Science, Southwest University, Chongqing, China

    Zehui Qu

Authors
  1. Luca Pappalardo
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  2. Salvatore Rinzivillo
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  3. Zehui Qu
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  4. Dino Pedreschi
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  5. Fosca Giannotti
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Corresponding authors

Correspondence to Luca Pappalardo, Salvatore Rinzivillo, Zehui Qu, Dino Pedreschi or Fosca Giannotti.

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Pappalardo, L., Rinzivillo, S., Qu, Z. et al. Understanding the patterns of car travel. Eur. Phys. J. Spec. Top. 215, 61–73 (2013). https://doi.org/10.1140/epjst/e2013-01715-5

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  • DOI: https://doi.org/10.1140/epjst/e2013-01715-5

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