Simulating the Resilience of Transport Infrastructures Using QUANT

使用 QUANT 模拟交通基础设施的弹性

• 批准号: ST/Y003705/1
• 负责人: Richard Milton
• 金额: $ 6.5万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FY003705%2F1
• 关键词: Simulating; Resilience; Transport; Infrastructures; Using

We have developed a model that simulates the pattern of land use and transportation for Great Britain which is configured in terms of thousands of small zones and three modes of transport which bind together employment at place of work and population at place of residence. The model is called QUANT and it runs in a web-based environment. It is optimised to run very rapidly and deliver results to the user in a matter of minutes so that users can derive and test future scenarios for land use and transport, on-the-fly so-to-speak. Our preliminary explorations of the model using the DAFNI model platform suggest that we can adapt part of the model to this platform and this project presents a proof of concept that this is possible and useful. We will adapt the 'what-if' scenario capability of QUANT to the platform so that users can run thousands of scenarios whose data can be used to train various optimisation models that show how future plans for the location of land uses and transport can be massively improved. The model predicts the impacts of such scenarios and we will fashion various user environments around the use of DAFNI that enable stakeholders to test various plans and to demonstrate how AI techniques can be used to inform the generation of many scenarios. We will demonstrate how models such as these can be used effectively to generate the impacts of shocks to the land use transport system such as those posed by new infrastructure projects such as HS2 which are continually being evolved. The fact that our model deals with different transport networks for Great Britain enables us to trace the repercussions of land use and transport change across networks that are composed of thousands of nodes and links which is key to assessing the repercussions of major changes on the UK's urban system.

我们已经开发了一个模型，模拟了英国的土地利用和交通模式，该模式由数千个小区域和三种交通方式组成，这些交通方式将工作场所的就业和居住地的人口联系在一起。该模型被称为QUANT，它在基于Web的环境中运行。它经过优化，运行速度非常快，并在几分钟内向用户提供结果，以便用户可以推导和测试未来的土地使用和交通情况，可以说是在飞行中。我们使用DAFNI模型平台对模型进行的初步探索表明，我们可以将模型的一部分适应该平台，并且该项目提出了一个概念证明，这是可能的和有用的。我们将使QUANT的“假设”场景功能适应该平台，以便用户可以运行数千个场景，这些场景的数据可用于训练各种优化模型，这些模型显示未来土地使用和交通位置的规划如何得到大规模改善。该模型预测了这些场景的影响，我们将围绕DAFNI的使用设计各种用户环境，使利益相关者能够测试各种计划，并演示如何使用AI技术来生成许多场景。我们将展示如何有效地使用这些模型来产生对土地使用运输系统的冲击的影响，例如由新的基础设施项目（如HS2）所带来的冲击，这些项目正在不断发展。事实上，我们的模型处理不同的交通网络，为英国使我们能够跟踪的影响，土地利用和交通变化的网络，由数千个节点和链接，这是关键，以评估英国的城市系统的重大变化的影响。