Journal of Advanced Transportation (Jan 2021)

An Improved Social Force Model for Bicycle Flow in Groups

  • Ying-Xu Rui,
  • Tie-Qiao Tang,
  • Jian Zhang

DOI
https://doi.org/10.1155/2021/2412655
Journal volume & issue
Vol. 2021

Abstract

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Bicycle flow widely has group behavior (i.e., cyclists have a tendency to ride in groups), which may have some significant effects on the bicycle’s motion. However, the existing studies on bicycle flow rarely consider this factor. Generally, bicycle flow has two kinds of group behaviors, i.e., shoulder group behavior and following group behavior. In this paper, we propose an improved social force (SF) model to describe the two kinds of group behaviors. Then, we use the improved SF model to, respectively, explore the effects of the two kinds of group behaviors on the bicycle’s motion from the simulation perspective. The numerical results show that (i) shoulder group behavior has some negative impacts on the bicycle’s motion, i.e., the critical density (where the through capacity can reach the maximum value), the jam density, and the through capacity will be reduced; (ii) following group behavior has some positive impacts on the bicycle’s motion, i.e., the critical density, the jam density, and the through capacity will be enhanced; (iii) the impacts of coexistence of shoulder and following group behavior are related to the density. Besides, increasing group size and group probability will enlarge the negative impacts of shoulder group behavior and alleviate the positive impacts of following group behavior. These results can guide administrators to better manage bicycle flow (especially reasonably control the negative impacts of group behaviors).