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Simulating Bicycle Traffic by the Intelligent-Driver Model: Reproducing the Traffic-Wave Characteristics Observed in a Bicycle-Following Experiment

In: Traffic and Granular Flow '17

Author

Listed:
  • Valentina Kurtc

    (Peter the Great St. Petersburg Polytechnic University)

  • Martin Treiber

    (Institute for Transport and Economics, Technische Universität Dresden)

Abstract

Bicycle traffic operations become increasingly important and yet are largely ignored in the traffic flow community, until recently. We hypothesize that there is no qualitative difference between vehicular and bicycle traffic flow dynamics, so the latter can be described by reparameterized car-following models. To test this proposition, we reproduce bicycle experiments on a ring with the intelligent-driver model and compare its fit quality (calibration) and predictive power (validation) with that of the necessary-deceleration-model which is specifically designed for bike traffic. We find similar quality metrics for both models, so the above hypothesis of a qualitative equivalence cannot be rejected.

Suggested Citation

  • Valentina Kurtc & Martin Treiber, 2019. "Simulating Bicycle Traffic by the Intelligent-Driver Model: Reproducing the Traffic-Wave Characteristics Observed in a Bicycle-Following Experiment," Springer Books, in: Samer H. Hamdar (ed.), Traffic and Granular Flow '17, pages 507-515, Springer.
  • Handle: RePEc:spr:sprchp:978-3-030-11440-4_55
    DOI: 10.1007/978-3-030-11440-4_55
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