Bicycle Flow Dynamics of Cyclist Loading and Unloading Processes at Bottlenecks

Author:

Guo Ning1,Wong Wai2,Jiang Rui3ORCID,Wong S. C.45ORCID,Hao Qing-Yi6,Wu Chao-Yun6

Affiliation:

1. School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, People’s Republic of China;

2. Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch 8041, New Zealand;

3. School of Systems Science, Beijing Jiaotong University, Beijing 100044, People’s Republic of China;

4. Department of Civil Engineering, The University of Hong Kong, Hong Kong 999077, People’s Republic of China;

5. Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities, Shenzhen 518060, People’s Republic of China;

6. School of Mathematics and Computational Science, Anqing Normal University, Anqing 246133, People’s Republic of China

Abstract

Cycling has emerged as one of the most important green transport modes in recent years, with cities increasingly prioritizing cycling in their sustainable policy agenda. However, the associated traffic dynamics, especially the evolution of bicycle flow at bottlenecks, have not been extensively studied. In this study, real-world experiments were conducted to investigate the dynamics of bicycle flow at bottlenecks under various cycling demands generated by the cyclist unloading and loading processes. Upon the activation of the bottleneck, its capacity remained largely constant. For the same physical system, the bottleneck capacity of the cyclist loading process exceeded that of the unloading process, indicating the occurrence of capacity drop and hysteresis. Statistical analyses demonstrated that the capacity drop was attributable to the difference in speeds of the two processes for the same cycling demands after the bottleneck activation. These findings could potentially be explained by behavioral inertia. Further analysis revealed that, compared with the unloading process, the cyclist loading process was associated with higher cycling speeds owing to the higher overtaking rates. The outcomes of this study can advance our understanding of the physics of bicycle flow dynamics and provide valuable insights for transport planning professionals involved in facility planning and control of existing networks. Funding: This work was supported by National Natural Science Foundation of China [Grants 71931002 and 72288101], the University of Hong Kong [Francis S Y Bong Professorship to S. C. Wong], the Guangdong-Hong Kong-Macau Joint Laboratory Program of the 2020 Guangdong New Innovative Strategic Research Fund, Guangdong Science and Technology Department [Grant 2020B1212030009], and Fundamental Research Funds for the Central Universities [Grant JZ2023YQTD0073]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2023.0193 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Transportation,Civil and Structural Engineering

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