Understanding Dynamics of Truck Co-Driving Networks

  • Gerrit Jan de BruinEmail author
  • Cor J. Veenman
  • H. Jaap van den Herik
  • Frank W. Takes
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 882)


The goal of this paper is to learn the dynamics of truck co-driving behaviour. Understanding this behaviour is important because co-driving has a potential positive impact on the environment. In the so-called co-driving network, trucks are nodes while links indicate that two trucks frequently drive together. To understand the network’s dynamics, we use a link prediction approach employing a machine learning classifier. The features of the classifier can be categorized into spatio-temporal features, neighbourhood features, path features, and node features. The very different types of features allow us to understand the social processes underlying the co-driving behaviour. Our work is based on a spatio-temporal data not studied before. Data is collected from 18 million truck movements in the Netherlands. We find that co-driving behaviour is best described by using neighbourhood features, and to lesser extent by path and spatio-temporal features. Node features are deemed unimportant. Findings suggest that the dynamics of a truck co-driving network has clear social network effects.


Transport networks Mobility Co-driving behaviour Spatio-temporal networks Link prediction 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Gerrit Jan de Bruin
    • 1
    • 2
    • 3
    Email author
  • Cor J. Veenman
    • 1
    • 4
  • H. Jaap van den Herik
    • 2
  • Frank W. Takes
    • 1
  1. 1.Leiden Institute of Advanced Computer ScienceLeiden UniversityLeidenThe Netherlands
  2. 2.Leiden Centre of Data ScienceLeiden UniversityLeidenThe Netherlands
  3. 3.Human Environment and Transport InspectorateNetherlands Ministry of Infrastructure and Water ManagementThe HagueThe Netherlands
  4. 4.Data Science DepartmentTNOThe HagueThe Netherlands

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