Crowd guidance and control technology for public places
REN Jianqiang1,2, NI Shunjiang1,2
1. Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China; 2. Beijing Key Laboratory of City Integrated Emergency Response Science, Beijing 100084, China
Abstract：[Objective] The accelerated process of urbanization and increased population mobility has led to a surge in population density and frequency in public spaces. This has underscored the importance of addressing health and safety concerns in public spaces, particularly considering the corona virus disease 2019 (COVID-19) pandemic. The effective management of public spaces has become a challenging aspect of urban planning and management. Through research on management and control technologies for populations at high risk of exposure in public spaces, it is possible to achieve efficient management and develop control measures. This will lead to a reduction in overcrowding, lower the risk of epidemic transmission, and ultimately ensure public health and safety. [Methods] This research focuses on a gymnasium in Hangzhou, where the upcoming Asian Games will be held. The study focuses on developing time-based control measures, including time-sharing control measures, classification control measures, and classification and zoning guidance control measures, for large-scale sports events. These measures are developed based on relevant standards and norms. Furthermore, a technical model is constructed to assess personnel evacuation and control in public places, evaluate the level of crowd gathering in public areas, and simulate the number of infected people under various control measures. Thus, the effectiveness of evacuation and control measures is assessed through reverse verification. Finally, different evacuation control schemes are simulated using three-dimensional modeling using the MassMotion software. The technical model of evacuation control for public places is integrated into the MassMotion software development kit (SDK), which is the software's secondary development system. This integration allows for the output of individual density proportion diagrams and COVID-19 virus transmission results under different evacuation control schemes. [Results] The simulation results showed that continuous updates to the guidance and control scheme improved the flow of people in the venue and decreased emergency evacuation time. Moreover, increasing social distance significantly reduced the risk of crowd aggregation and infection. These findings provided evidence supporting the feasibility and effectiveness of the guidance and control scheme for high-risk exposed individuals in public settings. [Conclusions] This study proposes a crowd guidance and control technology for public places aimed at ensuring public safety amidst the COVID-19 pandemic. This research conducted on a gymnasium as a case study provides insights into personnel circulation and COVID-19 transmission under different diversion and control schemes. Further, the research offers valuable support for the implementation of crowd diversion and control measures during large-scale sports events, ensuring the safety of attendees and the broader public.
任建强, 倪顺江. 公共场所内人群疏导与管控技术[J]. 清华大学学报（自然科学版）, 2024, 64(3): 471-477.
REN Jianqiang, NI Shunjiang. Crowd guidance and control technology for public places. Journal of Tsinghua University(Science and Technology), 2024, 64(3): 471-477.
[1] 李垚, 梁丁元, 穆云松, 等. 甲型流感的流行与防控分析及其对新冠肺炎疫情的启示[J]. 环境科学研究, 2020, 33(7):1562-1570. LI Y, LIANG D Y, MU Y S, et al. Epidemic situation, prevention, control of influenza a and its enlightenment for COVID-19[J]. Research of Environmental Sciences, 2020, 33(7):1562-1570. (in Chinese) [2] 陈伟, 王晴, 李媛秋, 等. 我国新型冠状病毒肺炎疫情早期围堵策略概述[J]. 中华预防医学杂志, 2020, 54(3):239-244. CHEN W, WANG Q, LI Y Q, et al. Early containment strategies and core measures for prevention and control of novel coronavirus pneumonia in China[J]. Chinese Journal of Preventive Medicine, 2020, 54(3):239-244. (in Chinese) [3] 郭迟, 王梦媛, 高柯夫, 等. 面向重大公共卫生事件的位置服务技术:以COVID-19疫情为例[J]. 武汉大学学报(信息科学版), 2021, 46(2):150-158. GUO C, WANG M Y, GAO K F, et al. Location-based service technologies for major public health events:Illustrated by the cases of COVID-19 epidemic[J]. Geomatics and Information Science of Wuhan University, 2021, 46(2):150-158. (in Chinese) [4] DE SILVA F N, EGLESE R W, PIDD M. Evacuation planning and spatial decision making:Designing effective spatial decision support systems through integration of technologies[C]//Decision Making Support Systems:Achievements, Trends and Challenges for the New Decade. Hershey, USA:IGI Global, 2002:358-373. [5] YI J F, ZHANG H, MAO J X, et al. Review on the COVID-19 pandemic prevention and control system based on AI[J]. Engineering Applications of Artificial Intelligence, 2022, 114:105184. [6] 莫智锋, 余嘉, 孙跃. 基于泊松分布的微观交通仿真断面发车数学模型研究[J]. 武汉理工大学学报(交通科学与工程版), 2003, 27(1):73-76. MO Z F, YU J, SUN Y. Poisson distribution based mathematic model of producing vehicles in microscopic traffic simulator[J]. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2003, 27(1):73-76. (in Chinese) [7] 孟媛, 龚言红, 尹平, 等. 基于传染病防控基本原则北京冬奥会防疫策略分析[J]. 医药导报, 2022, 41(6):791-793. MENG Y, GONG Y H, YIN P, et al. Analysis of epidemic prevention strategies for Beijing Winter Olympics based on the basic principles of infectious disease prevention and control[J]. Herald of Medicine, 2022, 41(6):791-793. (in Chinese) [8] 中华人民共和国国家卫生健康委员会办公厅, 国家中医药管理局办公室. 新型冠状病毒肺炎诊疗方案(试行第八版)[J]. 中国医药, 2020, 15(10):1494-1499. General Office of National Health Commission of the People's Republic of China, Office of National Administration of Traditional Chinese Medicine. Diagnosis and treatment of corona virus disease-19(8th trial edition)[J]. China Medicine, 2020, 15(10):1494-1499. (in Chinese) [9] 余江, 胡琳, 郭琴, 等. 综合医院门诊新型冠状病毒肺炎疫情防控的策略实践[J]. 重庆医学, 2020, 49(15):2459-2462. YU J, HU L, GUO Q, et al. Prevention and control strategies of corona virus disease 2019 in general hospitals[J]. Chongqing Medicine, 2020, 49(15):2459-2462. (in Chinese) [10] 杨晓霞. 基于社会力模型的地铁枢纽站行人流动态特性与疏散研究[D]. 北京:北京交通大学, 2017. YANG X X. Pedestrian flow dynamic characteristics and evacuation in the metro hub station based on the social force model[D]. Beijing:Beijing Jiaotong University, 2017. (in Chinese) [11] LI M Y, MULDOWNEY J S. Global stability for the SEIR model in epidemiology[J]. Mathematical Biosciences, 1995, 125(2):155-164. [12] HE S B, PENG Y X, SUN K H. SEIR modeling of the COVID-19 and its dynamics[J]. Nonlinear Dynamics, 2020, 101(3):1667-1680. [13] LI Y G, HUANG X H, YU I T S, et al. Role of air distribution in SARS transmission during the largest nosocomial outbreak in Hong Kong[J]. Indoor Air, 2005, 15(2):83-95. [14] NICAS M, JONES R M. Relative contributions of four exposure pathways to influenza infection risk[J]. Risk Analysis, 2009, 29(9):1292-1303. [15] MILTON D K. A Rosetta stone for understanding infectious drops and aerosols[J]. Journal of the Pediatric Infections Diseases Society, 2020, 9(4):413-415. [16] RAZAK F A, EXPERT P. Modelling the spread of COVID-19 on Malaysian contact networks for practical reopening strategies in an institutional setting[J]. Sains Malaysiana, 2021, 50(5):1497-1509.
2024, Vol. 64 
