Integration agent-based models and GIS as a virtual urban dynamic laboratory

被引:0
|
作者
Chen, Peng [1 ,2 ]
Liu, Miaolong [1 ]
机构
[1] Tongji Univ, Dept Surveying & Geoinformat, 1239 Siping Rd, Shanghai 200092, Peoples R China
[2] ECNU, Minist Educ, Key Lab Geog Informat Sci, Shanghai 200062, Peoples R China
关键词
agent-based model; integration GIS and ABM; urban dynamic simulation; pedestrians flows;
D O I
10.1117/12.764945
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] Agent-Based Models and Microsimulation
    Heard, Daniel
    Dent, Gelonia
    Schifeling, Tracy
    Banks, David
    ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 2, 2015, 2 : 259 - 272
  • [42] Agent-based virtual organization architecture
    Rodriguez, S.
    Julian, V.
    Bajo, J.
    Carrascosa, C.
    Botti, V.
    Corchado, J. M.
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2011, 24 (05) : 895 - 910
  • [43] Agent-based virtual organisations for the Grid
    Patel, Jigar
    Teacy, W. T. Luke
    Jennings, Nicholas R.
    Luck, Michael
    Chalmers, Stuart
    Oren, Nir
    Norman, Timothy J.
    Preece, Alun
    Gray, Peter M. D.
    Shercliff, Gareth
    Stockreisser, Patrick J.
    Shao, Jianhua
    Gray, W. Alex
    Fiddian, Nick J.
    Thompson, Simon
    MULTIAGENT AND GRID SYSTEMS, 2005, 1 (04) : 237 - 249
  • [44] Learning in agent-based models
    Kirman A.
    Eastern Economic Journal, 2011, 37 (1) : 20 - 27
  • [45] Econophysics of Agent-Based Models
    LeBaron, Blake
    JOURNAL OF ECONOMIC LITERATURE, 2014, 52 (03) : 855 - 858
  • [46] Features of Agent-based Models
    Heckel, Reiko
    Kurz, Alexander
    Chattoe-Brown, Edmund
    ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE, 2017, (263): : 31 - 37
  • [47] Agent-based models in sociology
    Bianchi, Federico
    Squazzoni, Flaminio
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2015, 7 (04): : 284 - 306
  • [48] An agent-based approach to tool integration
    Corradini F.
    Mariani L.
    Merelli E.
    International Journal on Software Tools for Technology Transfer, 2004, 6 (3) : 231 - 244
  • [49] Agent-Based Supply Chain Integration
    Mark E. Nissen
    Information Technology and Management, 2001, 2 (3) : 289 - 312
  • [50] AGENT-BASED DATA INTEGRATION FRAMEWORK
    Faber, Lukasz
    COMPUTER SCIENCE-AGH, 2014, 15 (04): : 389 - 410