Agent-based Microsimulation of Land Use, Technology Adoption, and Transportation within an Integrated Urban Modelling Framework

在集成城市建模框架内对土地使用、技术采用和交通进行基于代理的微观模拟

• 批准号: RGPIN-2019-05537
• 负责人: Fatmi, Mahmudur
• 金额: $ 1.89万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=761756
• 关键词: Agent; based; Microsimulation; Land; Use

Canadian cities are experiencing increased traffic congestion, greenhouse gas (GHG) emissions, and energy consumption due to private vehicle dependency and urban sprawl. For example, the transportation sector accounts for around 25% of the GHG emissions in Canada. To address these sustainability challenges, Canada will invest $180 billion over the next 10 years for sustainable city and transportation planning. Advanced simulation models are required to analyze land use and transportation policies within an integrated modelling framework. Travel and location choices are complex inter-dependent decisions, which closely interact with the adoption of technologies such as vehicle technology (e.g. autonomous vehicles), shared mobility (e.g. Uber), and ICT (e.g. smartphones). To analyze such decision interactions, fundamental research on developing innovative simulation techniques for improved prediction, as well as advanced econometric models for better behavioural representation, are required. The goal of my research program is to develop an agent-based urban microsimulation tool-kit that predicts the evolution of population technology adoption, land use, transportation, and environment of an urban region over time and space. The short-term objectives are to: 1) develop an innovative agent-based microsimulation model for predicting technology adoption, housing, and mobility choices, 2) develop novel econometric methods for understanding technology adoption, housing, and mobility behaviour, and 3) develop an advanced activity-based traffic microsimulation and environment model. A hybrid of event-based and discrete-time simulation techniques will be adopted to allow two-way feedback among technology use, land use, transportation, and environment components. Hybrid econometric methods will be developed to accommodate decision interactions and capture multi-layer heterogeneity among agents. The key outputs of this model will be traffic flows, vehicular emissions and dispersion, and residential and transportation energy use. During my PhD and post-doctoral training, I developed agent-based simulation and econometric models. I confirmed one-directional decision interactions, such as the effects of demographic events on location choices and travel activities. I will expand this knowledge to explore the two-way relationships among technology adoption, transportation, and land use decisions, and their environmental implications. This research will have a significant impact as the simulation tool will assist engineers and planners from industries and government agencies to develop sustainable policies, and will support future infrastructure investment decision-making. The development of these new technologies will benefit Canada by facilitating high-quality training (e.g. programming languages such as C#DotNET), creating new jobs (e.g. simulation specialists), and fostering sustained economic growth through ensuring an efficient transportation network.

加拿大城市正在经历增加的交通拥堵，温室气体（GHG）的排放以及由于私人汽车依赖和城市蔓延而引起的能源消耗。例如，运输部门约占加拿大温室气体排放量的25％。为了应对这些可持续发展挑战，加拿大将在未来10年内投资1800亿美元用于可持续城市和运输计划。需要先进的仿真模型来分析集成建模框架内的土地使用和运输政策。旅行和位置选择是复杂的相互依存决定，它们与采用诸如车辆技术（例如自动驾驶汽车），共享移动性（例如Uber）和ICT（例如智能手机）等技术的采用密切相互作用。为了分析这种决策互动，需要开发创新模拟技术以改进预测的基础研究，以及用于更好行为代表的发达计量经济学模型。 我的研究计划的目的是开发一个基于代理的城市微仿真工具套件，以预测人口技术采用，土地利用，运输和城市地区随着时间和空间的发展。短期目标是：1）开发一种基于创新的代理的微仿真模型，以预测技术采用，住房和移动性选择，2）开发新的计量经济学方法，以理解技术采用，住房和移动性行为，以及3）开发基于高级活动的交通流量微仿真和环境模型。将采用基于事件和离散时间模拟技术的混合体，以允许技术使用，土地使用，运输和环境组件之间的双向反馈。将开发混合计量经济学方法来适应决策相互作用并捕获代理之间的多层异质性。该模型的关键输出将是交通流量，车辆排放和分散以及住宅和运输能源使用。 在我的博士学位和博士后培训期间，我开发了基于代理的模拟和计量经济学模型。我确认了单向决策互动，例如人口事件对位置选择和旅行活动的影响。我将扩展这些知识，以探索技术采用，运输和土地使用决策及其环境影响之间的双向关系。这项研究将产生重大影响，因为仿真工具将帮助工业和政府机构的工程师和规划人员制定可持续的政策，并将支持未来的基础设施投资决策。这些新技术的开发将通过促进高质量培训（例如编程语言，例如C＃Dotnet），创造新的就业机会（例如模拟专家），并通过确保有效的运输网络来促进持续的经济增长，从而使加拿大受益。