IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i4p2429-d753959.html
   My bibliography  Save this article

Simulation Analysis of Bus Passenger Boarding and Alighting Behavior Based on Cellular Automata

Author

Listed:
  • Yunqiang Xue

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China
    School of Transportation, Southeast University, Nanjing 210096, China)

  • Meng Zhong

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Luowei Xue

    (Jiangxi Provincial Institute of Transportation Science, Nanchang 330200, China)

  • Bing Zhang

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Haokai Tu

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Caifeng Tan

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Qifang Kong

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Hongzhi Guan

    (School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China
    College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China)

Abstract

Bus passengers’ boarding and alighting behavior is important content when researching bus operation efficiency. This paper uses an improved cellular automata (CA) model and introduces four dynamic parameters to study individual behavioral characteristics of bus passengers’ boarding and alighting behavior. The research on the relationship between the macro pedestrian flow formed by the interaction between the individual passengers and the stop time of the bus station was realized. Then it was modeled for different situations, and the general update rules of CA were set based on realistic situations. The passenger boarding and alighting behaviors of the No. 245 bus route in Nanchang, China were simulated, and the simulation results of four different door layouts and passenger boarding and alighting modes were compared. It was found that when the passenger loading rate in the bus reaches 65%, the passenger boarding rate has an obvious tendency to slow down; the width of the door has a direct relationship with the passenger alighting efficiency, and the bus stopping time can be reduced by adjusting the width of the alighting door; a strategy which allows passengers board on the bus via the alighting door may effectively reduce the bus stopping time when there are many passengers boarding on the bus. Using strategy four, simulation research found that Bus No. 245 can reduce the stopping time by 40–50% in some station scenarios. Research results show that the CA model has certain practical value and can provide a theoretical reference for public transportation control and management.

Suggested Citation

  • Yunqiang Xue & Meng Zhong & Luowei Xue & Bing Zhang & Haokai Tu & Caifeng Tan & Qifang Kong & Hongzhi Guan, 2022. "Simulation Analysis of Bus Passenger Boarding and Alighting Behavior Based on Cellular Automata," Sustainability, MDPI, vol. 14(4), pages 1-16, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2429-:d:753959
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/4/2429/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/4/2429/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ma, Peijie & Wang, Binghong, 2013. "The escape of pedestrians with view radius," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 215-220.
    2. Guo, R.Y. & Huang, H.J., 2008. "A mobile lattice gas model for simulating pedestrian evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 580-586.
    3. Yue, Hao & Guan, Hongzhi & Zhang, Juan & Shao, Chunfu, 2010. "Study on bi-direction pedestrian flow using cellular automata simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 527-539.
    4. Yue, Hao & Hao, Herui & Chen, Xiaoming & Shao, Chunfu, 2007. "Simulation of pedestrian flow on square lattice based on cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 567-588.
    5. Blue, Victor J. & Adler, Jeffrey L., 2001. "Cellular automata microsimulation for modeling bi-directional pedestrian walkways," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 293-312, March.
    6. Feliciani, Claudio & Nishinari, Katsuhiro, 2016. "An improved Cellular Automata model to simulate the behavior of high density crowd and validation by experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 135-148.
    7. Hua Kuang & Song Tao & Shiqiang Dai & Xingli Li, 2009. "Subconscious Effect On Pedestrian Counter Flow In A Modified Lattice Gas Model With The Variable Transition Probability," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 20(12), pages 1945-1961.
    8. Schelenz, Tomasz & Suescun, Ángel & Karlsson, MariAnne & Wikström, Li, 2013. "Decision making algorithm for bus passenger simulation during the vehicle design process," Transport Policy, Elsevier, vol. 25(C), pages 178-185.
    9. Daganzo, Carlos F., 2009. "A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 913-921, December.
    10. Zheng, Ying & Jia, Bin & Li, Xin-Gang & Zhu, Nuo, 2011. "Evacuation dynamics with fire spreading based on cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(18), pages 3147-3156.
    11. Guo, Xiwei & Chen, Jianqiao & Zheng, Yaochen & Wei, Junhong, 2012. "A heterogeneous lattice gas model for simulating pedestrian evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 582-592.
    12. 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.
    13. Jesús López Baeza & José Carpio-Pinedo & Julia Sievert & André Landwehr & Philipp Preuner & Katharina Borgmann & Maša Avakumović & Aleksandra Weissbach & Jürgen Bruns-Berentelg & Jörg Rainer Noennig, 2021. "Modeling Pedestrian Flows: Agent-Based Simulations of Pedestrian Activity for Land Use Distributions in Urban Developments," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yunqiang Xue & Meng Zhong & Luowei Xue & Haokai Tu & Caifeng Tan & Qifang Kong & Hongzhi Guan, 2022. "A Real-Time Control Strategy for Bus Operation to Alleviate Bus Bunching," Sustainability, MDPI, vol. 14(13), pages 1-18, June.
    2. Maela Madel L. Cahigas & Ferani E. Zulvia & Ardvin Kester S. Ong & Yogi Tri Prasetyo, 2023. "A Comprehensive Analysis of Clustering Public Utility Bus Passenger’s Behavior during the COVID-19 Pandemic: Utilization of Machine Learning with Metaheuristic Algorithm," Sustainability, MDPI, vol. 15(9), pages 1-31, April.
    3. Lu Liu & Zhanglei Bian & Qinghui Nie, 2022. "Finding the Optimal Bus-Overtaking Rules for Bus Stops with Two Tandem Berths," Sustainability, MDPI, vol. 14(9), pages 1-14, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Qian, 2018. "A social force model for the crowd evacuation in a terrorist attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 315-330.
    2. Li, Jun & Fu, Siyao & He, Haibo & Jia, Hongfei & Li, Yanzhong & Guo, Yi, 2015. "Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 304-321.
    3. Yu Song & Jia Liu & Qian Liu, 2021. "Dynamic Decision-Making Process of Evacuees during Post-Earthquake Evacuation near an Automatic Flap Barrier Gate System: A Broken Windows Perspective," Sustainability, MDPI, vol. 13(16), pages 1-19, August.
    4. Sun, Yi, 2018. "Kinetic Monte Carlo simulations of two-dimensional pedestrian flow models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 836-847.
    5. Tianran Han & Jianming Zhao & Wenquan Li, 2020. "Smart-Guided Pedestrian Emergency Evacuation in Slender-Shape Infrastructure with Digital Twin Simulations," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    6. Moonsoo Ko & Taewan Kim & Keemin Sohn, 2013. "Calibrating a social-force-based pedestrian walking model based on maximum likelihood estimation," Transportation, Springer, vol. 40(1), pages 91-107, January.
    7. Zhou, Xuemei & Hu, Jingjie & Ji, Xiangfeng & Xiao, Xiongziyan, 2019. "Cellular automaton simulation of pedestrian flow considering vision and multi-velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 982-992.
    8. Chen, Yanyan & Chen, Ning & Wang, Yang & Wang, Zhenbao & Feng, Guochen, 2015. "Modeling pedestrian behaviors under attracting incidents using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 287-300.
    9. Sun, Yi, 2019. "Simulations of bi-direction pedestrian flow using kinetic Monte Carlo methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 519-531.
    10. Jin, Cheng-Jie & Jiang, Rui & Yin, Jun-Lin & Dong, Li-Yun & Li, Dawei, 2017. "Simulating bi-directional pedestrian flow in a cellular automaton model considering the body-turning behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 666-681.
    11. Sun, Yi, 2020. "Kinetic Monte Carlo simulations of bi-direction pedestrian flow with different walk speeds," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    12. Hou, Lei & Liu, Jian-Guo & Pan, Xue & Wang, Bing-Hong, 2014. "A social force evacuation model with the leadership effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 93-99.
    13. Yue, Hao & Zhang, Junyao & Chen, Wenxin & Wu, Xinsen & Zhang, Xu & Shao, Chunfu, 2021. "Simulation of the influence of spatial obstacles on evacuation pedestrian flow in walking facilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    14. Li, Lin & Yu, Zhonghai & Chen, Yang, 2014. "Evacuation dynamic and exit optimization of a supermarket based on particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 157-172.
    15. Abdelghany, Ahmed & Abdelghany, Khaled & Mahmassani, Hani, 2016. "A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 159-176.
    16. Yamamoto, Hiroki & Yanagisawa, Daichi & Feliciani, Claudio & Nishinari, Katsuhiro, 2019. "Body-rotation behavior of pedestrians for collision avoidance in passing and cross flow," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 486-510.
    17. Yue, Hao & Guan, Hongzhi & Zhang, Juan & Shao, Chunfu, 2010. "Study on bi-direction pedestrian flow using cellular automata simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 527-539.
    18. Leng, Biao & Wang, Jianyuan & Xiong, Zhang, 2015. "Pedestrian simulations in hexagonal cell local field model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 532-543.
    19. Gao, Jin & Zhang, Jingjing & He, Jun & Gong, Jinghai & Zhao, Jincheng, 2020. "Experiment and simulation of pedestrian’s behaviors during evacuation in an office," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    20. Hao, Qing-Yi & Qian, Jia-Li & Wu, Chao-Yun & Guo, Ning, 2021. "Phase behaviors of counterflowing stream of pedestrians with site-exchange in local vision and environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2429-:d:753959. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.