Integration Of Microclimate Into The Multi-Agent Simulation In The Use Efficiency Evaluation Of Urban Public Space

Urban public space is the main place for human outdoor activities.The quality of urban public space is directly related to the quality of life and the competitiveness of the city.As urbanization continues to accelerate,people have higher demands on the spatial quality of public spaces in cities,and it has become particularly urgent to evaluate the usage of buildings and environments.Nowadays,most of the relevant assessment methods currently used are based on the built environment,and there are no effective assessment and simulation methods at the design development phase that can directly guide the design.The algorithm for optimizing the Multi-Agent Simulation(MAS)in urban public space can provide an effective method for the design of urban public space and the evaluation of the built environment,which can be reasonably and effectively used in the design and post-completion transformation optimization of urban public space.Simulation of human behavior by Multi-Agent models is one of the important methods to study public space.However,most of the Multi-Agent Simulations are applied to evacuation simulations of indoor environments,and the research is concerned with the way people behave or the correlation with the spatial layout,while ignoring that in outdoor spaces,environmental factors such as microclimate tend to have a more important influence on human behavior.Based on the study of urban public space,microclimate and Multi-Agent Simulation,this study transforms microclimate factors into the two main factors of comfort perception and sunlight perception,and other environmental factors into visual perception and facility needs,and multiple environmental factors are integrated into the traditional Multi-Agent model,improving the authenticity of the Multi-Agent model's representation of outdoor environment.At the same time,the study also developed the Multi-Agent model algorithms,including an integrated environmental evaluation algorithm,a dwell point location selection algorithm and a pedestrian motion algorithm,etc.The study refines the Agent motion rules,construct the Multi-Agent model that integrates environmental factors such as microclimate.In addition,the study broadens the applicability of the Multi-Agent Simulation in the field of pedestrian simulation,making it more realistic for the simulation of pedestrian behavior in outdoor public spaces.The new Multi-Agent simulation model,developed based on the Processing platform,which can display the activity of the subject in space dynamically and visually.The study takes Nanjing Gulou Square and Shaoxing Yuanjiao Square as examples,and selects reasonable times in spring,summer and winter as typical weather days to conduct site investigation and model simulations.The new Multi-Agent model was found to be more effective in expressing people's outdoor performance under microclimatic influences by comparing the simulation results with the fit of the survey results.Using the Multi-Agent model to complete pedestrian simulation of urban public space can not only efficiently assess the use of the urban built environment and provide reference for the renovation of the existing built environment,but also become an effective tool in the scheme design stage and provide guidance for the optimization of the construction and improvement of urban public space.The whole thesis contains about 45000 words,60 pictures and charts.