IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v646y2024ics0378437124003856.html
   My bibliography  Save this article

A deep reinforcement learning traffic control model for Pedestrian and vehicle evacuation in the parking lot

Author

Listed:
  • Zhang, Zhao
  • Fei, Yuhan
  • Fu, Daocheng

Abstract

As a necessary component of connecting the building interior and urban road network for evacuation, the evacuation of parking lots significantly impacts overall evacuation efficiency. However, existing emergency evacuation studies have ignored the control of pedestrian-vehicle mixed flow in parking lot environments, leading to underestimated evacuation time estimates. Therefore, this paper proposes a pedestrian-vehicle mixed-flow model to simulate the parking lot evacuation process at the microscopic level. Moreover, a deep reinforcement learning (DRL)-based evacuation control model is developed to control pedestrian evacuation speed. The numerical study shows that this control model can effectively reduce evacuation clearance time by 7.75 % when faced with enormous evacuation demands.

Suggested Citation

  • Zhang, Zhao & Fei, Yuhan & Fu, Daocheng, 2024. "A deep reinforcement learning traffic control model for Pedestrian and vehicle evacuation in the parking lot," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 646(C).
    • Handle: RePEc:eee:phsmap:v:646:y:2024:i:c:s0378437124003856
    DOI: 10.1016/j.physa.2024.129876
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124003856
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2024.129876?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Zhao & Fu, Daocheng, 2022. "Modeling pedestrian–vehicle mixed-flow in a complex evacuation scenario," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    2. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    3. Yuan, Weifeng & Tan, Kang Hai, 2011. "A model for simulation of crowd behaviour in the evacuation from a smoke-filled compartment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4210-4218.
    4. Stepanov, Alexander & Smith, James MacGregor, 2009. "Multi-objective evacuation routing in transportation networks," European Journal of Operational Research, Elsevier, vol. 198(2), pages 435-446, October.
    5. Muñoz, Juan Carlos & Soza-Parra, Jaime & Didier, Arturo & Silva, Constanza, 2018. "Alleviating a subway bottleneck through a platform gate," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 446-455.
    6. 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).
    7. Fu, Libi & Qin, Huigui & He, Yangjian & Shi, Yongqian, 2024. "Application of the social force modelling method to evacuation dynamics involving pedestrians with disabilities," Applied Mathematics and Computation, Elsevier, vol. 460(C).
    8. Nicholas Molyneaux & Riccardo Scarinci & Michel Bierlaire, 2021. "Design and analysis of control strategies for pedestrian flows," Transportation, Springer, vol. 48(4), pages 1767-1807, August.
    9. Chao Wang & Jian Wang, 2016. "A Modified Floor Field Model Combined with Risk Field for Pedestrian Simulation," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, February.
    10. Hoogendoorn, S. P. & Bovy, P. H. L., 2004. "Pedestrian route-choice and activity scheduling theory and models," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 169-190, February.
    11. Xinhua Mao & Changwei Yuan & Jiahua Gan & Jibiao Zhou, 2019. "Optimal Evacuation Strategy for Parking Lots Considering the Dynamic Background Traffic Flows," IJERPH, MDPI, vol. 16(12), pages 1-20, June.
    12. Paula Tătulea & Florina Călin & Remus Brad & Lucian Brâncovean & Mircea Greavu, 2019. "An Image Feature-Based Method for Parking Lot Occupancy," Future Internet, MDPI, vol. 11(8), pages 1-17, August.
    13. Zhe Zhang & Limin Jia & Yong Qin, 2016. "Level-of-Service Based Hierarchical Feedback Control Method of Network-Wide Pedestrian Flow," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-14, December.
    Full references (including those not matched with items on IDEAS)

    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. Tian, Jiangtao & Li, Xingli & Guo, Qinghua & Kuang, Hua, 2024. "Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    2. Li, Xingli & Guo, Fang & Kuang, Hua & Geng, Zhongfei & Fan, Yanhong, 2019. "An extended cost potential field cellular automaton model for pedestrian evacuation considering the restriction of visual field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 47-56.
    3. Xianing Wang & Zhan Zhang & Ying Wang & Jun Yang & Linjun Lu, 2022. "A Study on Safety Evaluation of Pedestrian Flows Based on Partial Impact Dynamics by Real-Time Data in Subway Stations," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    4. Mohammed Mahmod Shuaib, 2016. "Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior," Modern Applied Science, Canadian Center of Science and Education, vol. 10(7), pages 1-1, July.
    5. Zhang, Yihao & Chai, Zhaojie & Lykotrafitis, George, 2021. "Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    6. Xiao, Yao & Yang, Mofeng & Zhu, Zheng & Yang, Hai & Zhang, Lei & Ghader, Sepehr, 2021. "Modeling indoor-level non-pharmaceutical interventions during the COVID-19 pandemic: A pedestrian dynamics-based microscopic simulation approach," Transport Policy, Elsevier, vol. 109(C), pages 12-23.
    7. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2019. "When ‘push’ does not come to ‘shove’: Revisiting ‘faster is slower’ in collective egress of human crowds," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 51-69.
    8. Guo, Ren-Yong, 2014. "Simulation of spatial and temporal separation of pedestrian counter flow through a bottleneck," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 428-439.
    9. Ziyou Gao & Yunchao Qu & Xingang Li & Jiancheng Long & Hai-Jun Huang, 2014. "Simulating the Dynamic Escape Process in Large Public Places," Operations Research, INFORMS, vol. 62(6), pages 1344-1357, December.
    10. Li, Shengnan & Li, Xingang & Qu, Yunchao & Jia, Bin, 2015. "Block-based floor field model for pedestrian’s walking through corner," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 337-353.
    11. Huang, Rong & Zhao, Xuan & Zhou, Chenyu & Kong, Lingchen & Liu, Chengqing & Yu, Qiang, 2022. "Static floor field construction and fine discrete cellular automaton model: Algorithms, simulations and insights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    12. 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.
    13. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    14. He, Mengchen & Wang, Qiao & Chen, Juan & Xu, Shiwei & Ma, Jian, 2023. "Modeling pedestrian walking behavior in the flow field with moving walkways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    15. Liu, Qian, 2018. "The effect of dedicated exit on the evacuation of heterogeneous pedestrians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 305-323.
    16. Johansson, Fredrik & Peterson, Anders & Tapani, Andreas, 2015. "Waiting pedestrians in the social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 95-107.
    17. He, Mengchen & Qiu, Yunfei & Ge, Xinru & Huang, Ran & Chen, Juan & Wang, Qiao & Lo, Jacquline & Ma, Jian, 2024. "Effect of moving walkway arrangement on unidirectional crowd flow characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    18. Geng, Zhongfei & Li, Xingli & Kuang, Hua & Bai, Xuecen & Fan, Yanhong, 2019. "Effect of uncertain information on pedestrian dynamics under adverse sight conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 681-691.
    19. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Route choice in the pedestrian evacuation: Microscopic formulation based on visual information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    20. Li, Maosheng & Shu, Panpan & Xiao, Yao & Wang, Pu, 2021. "Modeling detour decision combined the tactical and operational layer based on perceived density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(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:eee:phsmap:v:646:y:2024:i:c:s0378437124003856. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.