Application of agent based modelling and complex systems to national and regional transport planning

基于代理的建模和复杂系统在国家和地区交通规划中的应用

• 批准号: 400168
• 金额: $ 48.42万
• 依托单位: MDS TRANSMODAL LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=400168
• 关键词: Application; agent; based; modelling; complex

Project ABI3L has constructed a prototype Agent-based model (using complex systems thinking) of the UK freight transport system under the TSB Intelligent Logistics call for funding. ABI3L stands for Agent-Based Intelligent Logistics which is also Innovative and Integrating. The goal of the project has been to develop complex systems models of UK freight and logistics to help to determine the investments and policies that will be needed to move to a low carbon world whilst also delivering economic productivity. At present such policy and investment choices are not supported by tools that can evaluate radical change, including the need to change behaviours, policies and attitudes to freight at both a regional and national level and how the complexity interacts.The opportunity is to model step changes in logistics networks, operating practices, regulatory control and fiscal measures to better inform both policy makers and investors on the real value of the options available, providing insights into how the total system can be improved, covering modal shift, behavioural and economic responses to policies and the requirement for capacity at key points in the network. Fully deployed, the modelling will allow both public sector planners and private sector actors to understand and forecast impacts, reduce risk and focus investment.

ABI3L项目在TSB智能物流项目的资助下，构建了一个基于代理的英国货运系统原型模型（使用复杂系统思维）。ABI3L代表基于Agent的智能物流，也是创新和集成的。该项目的目标是开发英国货运和物流的复杂系统模型，以帮助确定向低碳世界迈进所需的投资和政策，同时提高经济生产力。目前，这些政策和投资选择没有得到能够评估根本变化的工具的支持，包括在区域和国家层面改变行为、政策和对货运的态度的必要性，以及复杂性如何相互作用。监管控制和财政措施，以更好地告知决策者和投资者现有选择的真实的价值，提供如何改进整个系统的见解，包括模式转换，对政策的行为和经济反应以及网络关键点的能力要求。该模型全面部署后，将使公共部门规划者和私营部门行为者能够了解和预测影响，减少风险并集中投资。