An Improved Social Force Model for Bicycle Flow in Groups

Ying-Xu Rui,Jian Zhang,Tie-Qiao Tang,Yuan Gao

doi:10.1155/2021/2412655

Ying-Xu Rui, Jian Zhang + Show 2 more

Open Access

https://doi.org/10.1155/2021/2412655

Copy DOI

Abstract

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).

Highlights

Due to the bicycle’s own merits, bicycle has been an important commuting tool in many countries [1], and cyclists have a tendency to ride in groups [2]
(2) When ρ ≥ 250 bic/km, the speed and flow are both the highest under K 2 and the lowest under K 1; the critical density, the jam density, and the maximum flow increase when the group size switches from 1 to 2 and decrease when the group size switches from 2 to 3. ese results indicate that following group behavior has some positive impacts on bicycle flow, but the positive impacts will be alleviated with the increase of group size
Numerical tests on one three-lane circuit road are conducted to explore the impacts of group behaviors on bicycle flow

Summary

Introduction

Due to the bicycle’s own merits (i.e., low price and no emissions), bicycle has been an important commuting tool in many countries [1], and cyclists have a tendency to ride in groups (especially after shared bicycles occur) [2]. Limited by the discrete motion, this model cannot accurately describe the interactions among bicycles (especially compared with the continuous model) To overcome this drawback, researchers extended the SF model for pedestrian flow [11, 12] to describe the bicycle’s. Li et al [21] embedded the decision process in the SF model and designed a behavior force to explore the lateral dispersion phenomenon of high density through bicycle flow at an intersection. To study the bicycle group behavior, Tang et al [22, 23] proposed an extended CA model to evaluate the impacts of shoulder group behavior and following group behavior on bicycle flow in two typical traffic scenarios, but they did not analyze the impacts from the perspective of continuous model, such as SF model.

Extended SF Model Accounting for Group Behavior

Numerical Tests

Conclusions