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A Spatial Agent-Based Model of Walking Behavior in Cities

基于空间代理的城市步行行为模型

基本信息

批准号：
8321022
负责人：
Yong Yang
金额：
$ 23.33万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-08-18 至 2014-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8321022
关键词：
Accounting Affect Area Attention Attitude Behavior Cardiovascular Diseases Case Study Characteristics Chronic Cities Communities Complex Data Data Sources Destinations Development Environment Environmental Impact Environmental Risk Factor Epidemiology Esthetics Explosion Feedback Future Generic Drugs Goals Individual Inequality Information Systems Intervention Life Location Malignant Neoplasms Methodology Modeling Neighborhoods Physical activity Physical environment Policies Policy Making Population Property Public Health Research Resistance Safety Science Series Shapes Simulate Social Environment Social Network Spatial Distribution System Time Transportation Violence Walking Work base design disease transmission experience improved interest land use model development novel policy implication population health prevent randomized trial response segregation social socioeconomics

项目摘要

DESCRIPTION (provided by applicant): There has been an explosion of interest in how features of the social and built environments of communities affect the physical activity of residents. Because of the relevance of walking as a component of physical activity, and the possibility of increasing population-levels of physical activity by increasing walking in daily life, the study of the environmental determinants of walking has received special attention. Studies have documented associations of walking with environmental features such as land use mix and proximity of destinations, street connectivity and presence of sidewalks, aesthetic and design features of the environment, and safety and violence levels. However, important questions remain regarding the policy implications of this work. A major challenge is the need to account for the multiple dynamic relations between individuals (e.g. the behavior of one individual affecting those of others around him or her), between individuals and their environments (e.g. the environment changing in response to the behaviors of individuals and vice versa), and between environments (e.g. street connectivity affecting levels of safety). Accounting for these dynamic relationships is fundamental to understanding how environmental factors operate and to identifying plausible effects of various policies. Systems science methodologies (including agent-based models or ABMs) have received increasing attention as a way to better capture the complex set of dynamic relationships inherent in population health problems, but few applications to specific research problems exist. The overall goal of this proposal is to develop a generic agent-based model (ABM) of people's walking behavior within a hypothetical city. This model will be used to enhance scientific understanding of the ways in which environmental factors affect population-levels of walking and socioeconomic inequalities in walking. The Specific Aims are: (1) To build a generic agent-based model to simulate people's walking behavior within a hypothetical city; (2) To use the proposed model to specifically investigate how mixed land use and safety could contribute to population- levels of walking and to socioeconomic inequalities in walking; and (3) To explore the feasibility (including data availability and new data needs) of making the model reflect a real city. This proposal will apply novel systems methodologies to a policy resistant population health problem and will generate one of the first exemplars of applications of this approach in population health. It will develop a generic model useful for understanding dynamics that operate across cities and will lay the ground work for further development of more realistic models specific to real cities. The systems approach we propose has great potential for improving our understanding of the environmental determinants of walking which will be crucial to identifying relevant policies and anticipating their effects in future research. The development of these models represents a paradigm change in the way evidence is used to select and support interventions and policies to prevent major chronic conditions, including cardiovascular disease and cancer.

描述（由申请人提供）：人们对社区的社会和建筑环境特征如何影响居民的身体活动产生了浓厚的兴趣。由于步行作为身体活动的一个组成部分的相关性，以及通过增加日常生活中的步行来增加人口身体活动水平的可能性，因此对步行的环境决定因素的研究受到了特别的关注。研究记录了步行与环境特征的关联，如土地利用组合和目的地的邻近程度、街道的连通性和人行道的存在、环境的美学和设计特征、安全和暴力程度。然而，关于这项工作的政策含义仍然存在重要问题。一个主要的挑战是需要考虑个人之间的多重动态关系（例如，一个人的行为影响他或她周围的其他人的行为），个人与其环境之间的关系（例如，环境随着个人行为的变化而变化，反之亦然），以及环境之间的关系（例如，街道连接影响安全水平）。考虑这些动态关系是理解环境因素如何运作和确定各种政策的合理影响的基础。系统科学方法（包括基于主体的模型或ABMs）作为一种更好地捕捉人口健康问题中固有的复杂动态关系集的方法受到越来越多的关注，但很少应用于具体的研究问题。该提案的总体目标是开发一个基于智能体的通用模型（ABM），用于模拟城市中人们的步行行为。该模型将用于加强对环境因素影响人口步行水平和步行中社会经济不平等的科学理解。具体目标是：(1)建立一个基于智能体的通用模型来模拟假设城市中人们的步行行为；(2)利用所提出的模型具体研究混合土地利用和安全如何影响人口步行水平和步行中的社会经济不平等；(3)探索模型反映真实城市的可行性（包括数据可用性和新数据需求）。这一建议将把新的系统方法应用于有政策阻力的人口健康问题，并将产生在人口健康方面应用这一方法的首批范例之一。它将开发一个通用模型，用于理解跨城市运行的动态，并将为进一步开发针对真实城市的更现实的模型奠定基础。我们提出的系统方法具有很大的潜力，可以提高我们对步行的环境决定因素的理解，这对于确定相关政策并预测其在未来研究中的影响至关重要。这些模型的发展代表了证据用于选择和支持预防主要慢性病（包括心血管疾病和癌症）的干预措施和政策的方式的范式变化。