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Digital twins of micro crowd： The concept， framwork， and methods

  • role： First author第一作者
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • Email：liwh@aircas.ac.cn
  • Introduction：李文航，研究方向为微观人群行为模拟。E-mail： liwh@aircas.ac.cn
LI Wenhang,  
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

GONG Jianhua,  
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

HUANG Lin,  
  • Affiliation：

    National Engineering Research Center for Geomatics, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

MA Haonan

Resümee

raditional geography/GIS research on the spatiotemporal behavior of people focus on the meso and macro scale, while the research on the micro spatiotemporal behavior is relatively insufficient. To address this problem, first, a new concept of micro crowd digital twins is proposed. The idea is to map the real crowd and their behaviors into the virtual space, calculate and simulate the crowd behavior, mine the evolution mechanism, discover the operation rules, predict the trends, locate the abnormalities in advance, propose optimization strategies, and improve the efficiency and safety of real crowd and real society. The micro crowd digital twins can be divided into two stages, namely, special digital twins and general digital twins, according to whether they are synchronized in time between the real crowd and the virtual one.Then, the technical basis and research status of micro crowd digital twins are summarized from the aspects of crowd behavior experimental approaches, basic behavior/scenario behavior modeling, and typical applications. (1) According to the types of places and events, the crowd behavior experiment approaches can be divided into “real place-real event,” “real place-simulated event,” “simulated place-simulated event,” and “virtual place-virtual event.” (2) The status of crowd behavior modeling is summarized, which can be divided into basic micro crowd behavior models and scenario behavior models. The basic micro crowd behavior models are to model individual behaviors in a simple and abstracted space, with general interactions between individuals and obstacles. The scenario behavior models are to model crowd behaviors in complex and detailed space, with comprehensive interactions between crowds, environments, and geo-events. The advantages and disadvantages of typical basic micro crowd behavior models such as Social Force Model, Velocity Obstacle model (ORCA model), and Artificial Intelligence (AI) model are analyzed. (3) A typical case of micro crowd digital twins in a school evacuation is analyzed. The platform of digital twins of crowds is developed to simulate and examine the disordered behaviors and orderly behaviors, and the spatial layout of the school and the crowd evacuation strategies are optimized. In this manner, the special micro crowd digital twin is realized.Finally, the future research of crowd behavior experiments, crowd modeling, and theoretical system of micro human-land relationship are awaited from the perspective of geography. (1) New approaches such as credible micro crowd behavior experiment should be developed. In the crowd behavior experiments, the behavior errors caused by subjective and objective factors in crowd experiments need to be calibrated qualitatively and quantitatively, and the deviation correction algorithm should be developed to obtain reliable experimental results. (2) New micro crowd behavior modeling ideas should be proposed. Behavior models should focus on not only emergency disordered behaviors but also those orderly behaviors under the constraints of social rules and social orders in common daily conditions. The rules of individual “self-interest” used in traditional behavior modeling also need to be expanded, and the crowd interests should be introduced to build behavioral models considering “self-interest” and “altruism” rules. (3) The deterministic and stochastic characteristics of crowd behaviors should be considered. In view of the complementary characteristics of AI behavior models and traditional mathematical behavior models as well as the advantages of AI model in stochastic modeling, they can be combined to achieve this goal. (4) On the basis of the digital twinning of micro crowd, the innovative theoretical system of “micro human-land relationship” can be developed in the future, which will break through the traditional concept of “macro human-land relationship” modeling, and will make the theoretical system and modeling system of the study of human-land relationship in geography more complete. Then, the research of geography, geographic information system, and virtual geographic environments on modeling of micro crowd behaviors, micro spaces, and the applications can be promoted.

Schlüsselwort

remote sensing;Digital twins of micro crowd;micro spatiotemporal crowd behavior;behavior modelling;VGE;geography

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