{"title":"面对静态障碍时,社会属性如何影响子群体的运动过程","authors":"Wenhan Wu;Wenfeng Yi;Erhui Wang;Xiaolu Wang;Xiaoping Zheng","doi":"10.1109/TCSS.2024.3493954","DOIUrl":null,"url":null,"abstract":"With the increasing number of studies on crowd behavior analysis, there has been a widespread interest in treating subgroups as an important topic. A previous experimental study has investigated the decision-making and motion behavior of subgroups when facing a static obstacle during movement. However, it is hard to quantify social attributes (e.g., interpersonal relationships and sense of identity) and little is known about how they affect the movement process of subgroups. Here, we propose a vision-driven model to solve this problem, in which two key model parameters are defined to control the spatial cohesion and attraction intensity, respectively. Numerical simulations demonstrate that the optimal regions of model parameters vary depending on different conditions of the three control variables (obstacle width, time pressure, and subgroup size). The spatial cohesion and attraction intensity barely change the movement process of subgroups in the maintaining state but significantly affect it in the splitting-merging state. This model can reproduce the herding effect of subgroup members in the merging process, which is affected to varying degrees by the modulation of model parameters. Overall, this work contributes to the simulation of subgroup behaviors from a sociopsychological perspective.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":"12 2","pages":"658-670"},"PeriodicalIF":4.5000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How Social Attributes Affect the Movement Process of Subgroups When Facing a Static Obstacle\",\"authors\":\"Wenhan Wu;Wenfeng Yi;Erhui Wang;Xiaolu Wang;Xiaoping Zheng\",\"doi\":\"10.1109/TCSS.2024.3493954\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the increasing number of studies on crowd behavior analysis, there has been a widespread interest in treating subgroups as an important topic. A previous experimental study has investigated the decision-making and motion behavior of subgroups when facing a static obstacle during movement. However, it is hard to quantify social attributes (e.g., interpersonal relationships and sense of identity) and little is known about how they affect the movement process of subgroups. Here, we propose a vision-driven model to solve this problem, in which two key model parameters are defined to control the spatial cohesion and attraction intensity, respectively. Numerical simulations demonstrate that the optimal regions of model parameters vary depending on different conditions of the three control variables (obstacle width, time pressure, and subgroup size). The spatial cohesion and attraction intensity barely change the movement process of subgroups in the maintaining state but significantly affect it in the splitting-merging state. This model can reproduce the herding effect of subgroup members in the merging process, which is affected to varying degrees by the modulation of model parameters. Overall, this work contributes to the simulation of subgroup behaviors from a sociopsychological perspective.\",\"PeriodicalId\":13044,\"journal\":{\"name\":\"IEEE Transactions on Computational Social Systems\",\"volume\":\"12 2\",\"pages\":\"658-670\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Social Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10758305/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10758305/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
How Social Attributes Affect the Movement Process of Subgroups When Facing a Static Obstacle
With the increasing number of studies on crowd behavior analysis, there has been a widespread interest in treating subgroups as an important topic. A previous experimental study has investigated the decision-making and motion behavior of subgroups when facing a static obstacle during movement. However, it is hard to quantify social attributes (e.g., interpersonal relationships and sense of identity) and little is known about how they affect the movement process of subgroups. Here, we propose a vision-driven model to solve this problem, in which two key model parameters are defined to control the spatial cohesion and attraction intensity, respectively. Numerical simulations demonstrate that the optimal regions of model parameters vary depending on different conditions of the three control variables (obstacle width, time pressure, and subgroup size). The spatial cohesion and attraction intensity barely change the movement process of subgroups in the maintaining state but significantly affect it in the splitting-merging state. This model can reproduce the herding effect of subgroup members in the merging process, which is affected to varying degrees by the modulation of model parameters. Overall, this work contributes to the simulation of subgroup behaviors from a sociopsychological perspective.
期刊介绍:
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.