Doctoral Dissertation Research: Cognitive Agents and Pedestrian Redevelopment Modeling

全国各地的城市都在试图确定如何最好地处理现有的交通基础设施系统，同时纳入关于公共卫生、城市机动性和环境可持续性的不断变化的观点。在许多地方，规划者提出了以步行为导向的重建项目，这将要求城市的空间组织发生根本转变。这一博士论文研究项目将加强对城市环境的结构性变化将如何影响个人行为的理解。这名博士生将使用计算方法来研究个人对环境特征的感知和认知如何影响现实世界的决策和行为。通过经验驱动的认知模型，将提供关于城市行为的理论和实践方面的新见解。该项目将为规划者和政策制定者提供新的信息和见解，因为它将解决更大的社会问题，即适当地重新设计城市空间，以解决更大的环境、经济和公共卫生问题。该项目的结果还将增加对利益相关者和公众如何利用基于主体的建模来评估重建对公民个人和整个社区的影响的知识。作为博士论文研究改进奖，该奖项还将为有前途的学生建立强大的独立研究生涯提供支持。该项目将从计算的、以人为中心的角度探讨以行人为导向的再开发，这将为人们对设计空间的多种感知方式以及这些感知如何转化为个人空间行为提供新的见解。以步行为导向的重建通常被理解为是一种简单的、基于解决方案的方法，以解决城市更大的结构和社会问题。然而，由于嵌入了以汽车为导向的观点，改造现有的街道基础设施并不是一个简单的过程。本项目将集中于三个核心问题：(1)关于环境认知的个体差异的数据如何用于行人运动模型的开发？(2)主体认知的发展如何有助于真实世界行人运动模型的可信度？(3)城市重建项目中的哪些关键设计变量来自认知驱动的行人运动模型？这位博士生将在开发基于主体的空间模型时使用环境认知心理测量测试产生的数据。模型的输出将提供有关城市环境的微小变化如何影响现实世界决策和行为的新信息。研究和模拟城市空间中的个体认知过程将提供一种严格的、数据驱动的方法来回答有关个体主体以及规划的城市环境结构的问题。

Cities across the country are trying to determine how to best deal with existing systems of transportation infrastructure while incorporating shifting views about public health, urban mobility, and environmental sustainability. In many locales, planners have proposed pedestrian-oriented redevelopment projects that would require a fundamental shift in the spatial organization of the city. This doctoral dissertation research project will enhance understanding of how structural changes to the urban environment would impact individual behaviors. The doctoral student will employ computational approaches to examine how individual perception and cognition of environmental features influences real-world decisions and behaviors. New insights will be provided regarding the theoretical and practical facets of urban behaviors via empirically driven cognitive models. The project will provide new information and insights for planners and policy makers, because it will address larger societal questions regarding the appropriate redesign of urban spaces in order to address larger environmental, economic, and public health issues. Findings of the project also will increase knowledge of how agent-based modeling can be used by the stakeholders and the public to evaluate the impacts of redevelopment on both individual citizens and the community at large. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.This project will approach pedestrian-oriented redevelopment from a computational, human-centered perspective, which will offer new insights into the multiple ways designed space is perceived and how those perceptions are translated into individual spatial behaviors. Pedestrian-oriented redevelopment is often understood to be a simple, solution-based approach to address larger structural and social issues of the city. Transforming existing street infrastructure is not a straightforward process, however, because of embedded automobile-oriented perspectives. This project will focus on three core questions: (1) How can data about individual differences regarding environmental cognition be used in the development of a pedestrian movement model? (2) How does the development of agent cognition aid in the credibility of real-world pedestrian movement models? (3) What key design variables in urban redevelopment projects emerge from cognitively driven pedestrian movement models? The doctoral student will use data generated from psychometric tests of environmental cognition as he develops agent-based spatial models. The outputs of the models will provide new information regarding how small changes to the urban environment could impact real-world decision making and behaviors. Examining and modeling individual cognitive processes in urban spaces will provide a rigorous, data-driven approach to answer questions both about individual agency as well as about the structure of the planned urban environment.