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Modeling the interactions of pedestrians and cyclists in mixed flow conditions in uni- and bidirectional flows on a shared pedestrian-cycle road

Author

Listed:
  • Guo, Ning
  • Jiang, Rui
  • Wong, S.C.
  • Hao, Qing-Yi
  • Xue, Shu-Qi
  • Xiao, Yao
  • Wu, Chao-Yun

Abstract

The mixed flow of pedestrians and cyclists is frequently observed on the roads they share, but investigations of the dynamics of this kind of mixed flow have been very limited. This study proposes a heuristic-based model to reproduce the mixed-flow dynamics of pedestrians and cyclists, and the model is calibrated with an experiment on the mixed traffic flow of pedestrians and cyclists. Pedestrians/cyclists were asked to walk/ride on a ring-shaped track. In the uni/bidirectional flow scenario, pedestrians and cyclists moved in the same/opposite direction. A genetic algorithm was used for parameter calibration. The model could reproduce the experimental results well. Under both scenarios, pedestrians and cyclists formed their own lanes. The pedestrians walked in the inner lane, and cyclists rode in the outer lane in a self-organized process. The widths of the pedestrian lane and the cyclist lane were found to be more uniform during bidirectional flow. The pedestrian flow rate was higher in the unidirectional flow scenario than in the bidirectional flow scenario. In contrast, at low cyclist densities, the cyclist flow rate was essentially the same in both scenarios. When the density was high, the cyclist flow rate is higher in the unidirectional flow scenario. Sensitivity analyses showed that cyclist speed had little effect on the pedestrian flow rate. A higher cyclist speed led to a higher cyclist flow rate at low densities, but the cyclist flow rates approached the same value at high cyclist densities. As the proportion of pedestrians/cyclists increased, the flow rate of cyclists/pedestrians decreased. The simulation results on a straight track were largely consistent with those on a ring-shaped track.

Suggested Citation

  • Guo, Ning & Jiang, Rui & Wong, S.C. & Hao, Qing-Yi & Xue, Shu-Qi & Xiao, Yao & Wu, Chao-Yun, 2020. "Modeling the interactions of pedestrians and cyclists in mixed flow conditions in uni- and bidirectional flows on a shared pedestrian-cycle road," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 259-284.
    • Handle: RePEc:eee:transb:v:139:y:2020:i:c:p:259-284
    DOI: 10.1016/j.trb.2020.06.010
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    References listed on IDEAS

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    1. Ujjal Chattaraj & Armin Seyfried & Partha Chakroborty, 2009. "Comparison Of Pedestrian Fundamental Diagram Across Cultures," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 393-405.
    2. Mehdi Moussaïd & Elsa G Guillot & Mathieu Moreau & Jérôme Fehrenbach & Olivier Chabiron & Samuel Lemercier & Julien Pettré & Cécile Appert-Rolland & Pierre Degond & Guy Theraulaz, 2012. "Traffic Instabilities in Self-Organized Pedestrian Crowds," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-10, March.
    3. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    4. Rui Jiang & Mao-Bin Hu & Qing-Song Wu & Wei-Guo Song, 2017. "Traffic Dynamics of Bicycle Flow: Experiment and Modeling," Transportation Science, INFORMS, vol. 51(3), pages 998-1008, August.
    5. Muramatsu, Masakuni & Irie, Tunemasa & Nagatani, Takashi, 1999. "Jamming transition in pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 267(3), pages 487-498.
    6. Tie-Qiao Tang & Hai-Jun Huang & Hua-Yan Shang, 2010. "A Dynamic Model For The Heterogeneous Traffic Flow Consisting Of Car, Bicycle And Pedestrian," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 159-176.
    7. B. Jia & X.-G. Li & R. Jiang & Z.-Y. Gao, 2007. "Multi-value cellular automata model for mixed bicycle flow," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 56(3), pages 247-252, April.
    8. Xue, Shuqi & Jia, Bin & Jiang, Rui & Li, Xingang & Shan, Jingjing, 2017. "An improved Burgers cellular automaton model for bicycle flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 164-177.
    9. Lam, William H. K. & Lee, Jodie Y. S. & Chan, K. S. & Goh, P. K., 2003. "A generalised function for modeling bi-directional flow effects on indoor walkways in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(9), pages 789-810, November.
    10. Hughes, Roger L., 2002. "A continuum theory for the flow of pedestrians," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 507-535, July.
    11. Zhao, Yongxiang & Zhang, H.M., 2017. "A unified follow-the-leader model for vehicle, bicycle and pedestrian traffic," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 315-327.
    12. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    13. Burstedde, C & Klauck, K & Schadschneider, A & Zittartz, J, 2001. "Simulation of pedestrian dynamics using a two-dimensional cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 507-525.
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    2. Fu, Libi & Zhang, Ying & Qin, Huigui & Shi, Qingxin & Chen, Qiyi & Chen, Yunqian & Shi, Yongqian, 2023. "A modified social force model for studying nonlinear dynamics of pedestrian-e-bike mixed flow at a signalized crosswalk," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    3. Luo, Lin & Luo, Yangqi & Feng, Yujing & Li, Tao & Fu, Zhijian, 2022. "Experimental investigation on pedestrian–bicycle mixed merging flow in T-junction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    4. Che, Maohao & Wong, Yiik Diew & Lum, Kit Meng & Liu, Shuai, 2024. "Impact of “keep left” measure on pedestrians, cyclists and e-scooter riders at a crossing of a signalised junction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    5. Wang, Qiao & Chen, Juan & Jiang, Rui & Song, Weiguo & Li, Ruoyu & Lian, Liping & Ma, Jian, 2023. "Experimental study on the zebra crossing traffic flow characteristics of mixed bicycles and pedestrians," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).

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