{"title":"大空间城市的人群模拟","authors":"Panich Sudkhot, Chattrakul Sombattheera","doi":"10.23919/INCIT.2018.8584878","DOIUrl":null,"url":null,"abstract":"We present a multiagent-based framework for crowd simulation in large space urban area on a standalone PC. We use Belief-Desire-Intention (BDI) for modeling individual agent behavior. We use RVO for handling a large number of agents. The simulation engine is Unity3d which also take care of the visualization. We experimented our framework with up to 20,000 agents, navigating them from origins to destinations. We found that we can navigate agents successfully. The execution time increases when the number of agent increase. The visualization becomes slow when the number of agent is higher than 1000 agents. We found that the the simulation steps also increases when the number of agent is not higher than 5005.","PeriodicalId":144271,"journal":{"name":"2018 International Conference on Information Technology (InCIT)","volume":"47 13","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Crowd Simulation in Large Space Urban\",\"authors\":\"Panich Sudkhot, Chattrakul Sombattheera\",\"doi\":\"10.23919/INCIT.2018.8584878\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a multiagent-based framework for crowd simulation in large space urban area on a standalone PC. We use Belief-Desire-Intention (BDI) for modeling individual agent behavior. We use RVO for handling a large number of agents. The simulation engine is Unity3d which also take care of the visualization. We experimented our framework with up to 20,000 agents, navigating them from origins to destinations. We found that we can navigate agents successfully. The execution time increases when the number of agent increase. The visualization becomes slow when the number of agent is higher than 1000 agents. We found that the the simulation steps also increases when the number of agent is not higher than 5005.\",\"PeriodicalId\":144271,\"journal\":{\"name\":\"2018 International Conference on Information Technology (InCIT)\",\"volume\":\"47 13\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Information Technology (InCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/INCIT.2018.8584878\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information Technology (InCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/INCIT.2018.8584878","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a multiagent-based framework for crowd simulation in large space urban area on a standalone PC. We use Belief-Desire-Intention (BDI) for modeling individual agent behavior. We use RVO for handling a large number of agents. The simulation engine is Unity3d which also take care of the visualization. We experimented our framework with up to 20,000 agents, navigating them from origins to destinations. We found that we can navigate agents successfully. The execution time increases when the number of agent increase. The visualization becomes slow when the number of agent is higher than 1000 agents. We found that the the simulation steps also increases when the number of agent is not higher than 5005.
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