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.

由于对私家车的依赖和城市的扩张，加拿大的城市正在经历更多的交通拥堵、温室气体(GHG)排放和能源消耗。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性挑战，加拿大将在未来10年投资1800亿美元，用于可持续的城市和交通规划。需要先进的模拟模型来分析综合模拟框架内的土地使用和交通政策。出行和地点选择是相互依赖的复杂决策，与车辆技术(例如自动驾驶汽车)、共享移动性(例如优步)和信息和通信技术(例如智能手机)等技术的采用密切相关。为了分析这种决策相互作用，需要进行基础性研究，开发创新的模拟技术来改进预测，以及开发先进的计量经济学模型来更好地表现行为。我的研究计划的目标是开发一个基于代理的城市微观模拟工具包，预测城市地区人口技术采用、土地使用、交通和环境随时间和空间的演变。短期目标是：1)开发一个创新的基于主体的微观模拟模型，用于预测技术采用、住房和移动性选择；2)开发新的计量经济学方法，用于了解技术采用、住房和移动性行为；以及3)开发先进的基于活动的交通微观模拟和环境模型。将采用基于事件和离散时间的混合模拟技术，允许技术使用、土地使用、交通和环境组成部分之间的双向反馈。将开发混合计量经济学方法，以适应决策交互作用并捕捉代理人之间的多层异质性。该模型的主要输出将是交通流量、车辆排放和扩散，以及住宅和交通能源使用。在我的博士和博士后培训期间，我开发了基于代理的模拟和计量经济学模型。我证实了单向决策交互作用，例如人口统计事件对地点选择和旅行活动的影响。我将扩展这些知识，探索技术采用、运输和土地使用决策之间的双向关系，以及它们对环境的影响。这项研究将产生重大影响，因为模拟工具将帮助来自行业和政府机构的工程师和规划者制定可持续的政策，并将支持未来的基础设施投资决策。这些新技术的开发将促进高质量的培训(例如C#DotNet等编程语言)，创造新的就业机会(例如模拟专家)，并通过确保高效的交通网络促进持续的经济增长，从而使加拿大受益。