Building occupant transient agent-based model - Movement module

被引:17
|
作者
Dziedzic, Jakub Wladyslaw [1 ]
Yan, Da [2 ]
Sun, Hongsan [2 ]
Novakovic, Vojislav [1 ]
机构
[1] Norwegian Univ Sci & Technol, Dept Energy & Proc Engn, NO-7491 Trondheim, Norway
[2] Tsinghua Univ, Sch Architecture, Beijing 100084, Peoples R China
关键词
Occupant behaviour; Agent-based modelling; Building performance simulation; Human-building interaction; Personalised design; BOT-ABM; SIMULTANEOUS LOCALIZATION; ENERGY SIMULATION; BEHAVIOR; DESIGN;
D O I
10.1016/j.apenergy.2019.114417
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Simulation of occupant behaviour (OB) in buildings is a challenging task. Available software uses a broad spectrum of tools that try to reproduce the patterns of human activity. From building energy perspective, the main emphasis in research has been focused on discovering behaviour directly related to energy. In recent years, more attention has been given to simulating occupant actions that are indirectly influencing building energy use. In most of the cases, this is achieved with the use of agent-based modelling which allows describing occupant actions on a room level. According to the existing methodologies review, it is a proper step, but to include occupant behaviour in energy simulations, spatial and temporal resolution of the occupant behaviour model must be improved. Addressing this issue requires the development of a comprehensive model supported by numerous modules that would cover various significant occupant actions. This paper focuses on the development of the high-resolution, data-driven movement engine of occupants. It is one of the fundamental modules necessary to simulate occupant behaviour with high granularity. Once the model is developed within its essential functionalities, it will deliver a bottom-up model capable of testing various energy use strategies. It will allow for testing different heat, ventilation and air conditioning solutions and the responses provided by simulated occupants. The data used to develop this module was obtained thru in-situ measurements, with the use of depth registration. Information obtained from experiments is similar to previous research, but it also extends the investigation scope with an additional transition-based variable.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] An Agent-based Test Bed for Building Controls
    Goyal, Siddharth
    Wang, Weimin
    Brambley, Michael R.
    2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 1464 - 1471
  • [42] An Agent-based Model for the Humanities
    Roman, Belinda
    DIGITAL HUMANITIES QUARTERLY, 2013, 7 (01):
  • [43] An Agent-Based Model of Procrastination
    Procee, Ruurdje
    Kamphorst, Bart A.
    Vanwissen, Arlette
    Meyer, John-Jules
    21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014), 2014, 263 : 747 - +
  • [44] Building Agent-Based Appliances with Complementary Methodologies
    Sterling, Leon
    Taveter, Kuldar
    KNOWLEDGE-BASED SOFTWARE ENGINEERING, 2006, 140 : 223 - 232
  • [45] A level-of-details framework for representing occupant behavior in agent-based models
    Malik, Jeetika
    Azar, Elie
    Mahdavi, Ardeshir
    Hong, Tianzhen
    AUTOMATION IN CONSTRUCTION, 2022, 139
  • [46] Agent-Based Intelligent Interface for Wheelchair Movement Control
    Barriuso, Alberto L.
    Perez-Marcos, Javier
    Jimenez-Bravo, Diego M.
    Villarrubia Gonzalez, Gabriel
    De Paz, Juan F.
    SENSORS, 2018, 18 (05)
  • [47] Pigs in space: An agent-based model of wild boar (Sus scrofa) movement into cities
    Toger, Marina
    Benenson, Itzhak
    Wang, Yuqi
    Czamanski, Daniel
    Malkinson, Dan
    LANDSCAPE AND URBAN PLANNING, 2018, 173 : 70 - 80
  • [48] AgentSeal: Agent-based model describing movement of marine central-place foragers
    Chudzinska, Magda
    Nabe-Nielsen, Jacob
    Smout, Sophie
    Aarts, Geert
    Brasseur, Sophie
    Graham, Isla
    Thompson, Paul
    McConnell, Bernie
    ECOLOGICAL MODELLING, 2021, 440
  • [49] A hybrid workflow connecting a network and an agent-based model for predictive pedestrian movement modelling
    Ullrich, Anita
    Hunger, Franziska
    Stavroulaki, Ioanna
    Bilock, Adam
    Jareteg, Klas
    Tarakanov, Yury
    Gosta, Alexander
    Quist, Johannes
    Berghauser Pont, Meta
    Edelvik, Fredrik
    FRONTIERS IN BUILT ENVIRONMENT, 2024, 10
  • [50] Modeling Movement Direction Choice and Collision Avoidance in Agent-Based Model for Pedestrian Flow
    Liu, S. B.
    Lo, S. M.
    Tsui, K. L.
    Wang, W. L.
    JOURNAL OF TRANSPORTATION ENGINEERING, 2015, 141 (06)