Agent Based Modelling in Practical Engineering Applications

实际工程应用中基于代理的建模

• 批准号: 2883675
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 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=studentship-2883675
• 关键词: Agent; Based; Modelling; Practical; Engineering

The proposed description is straight deriving from the post advertisement; see: Why people move the way they do when crossing a bridge? Why they evacuate (e.g., in a fire or earthquake scenario) buildings creating certain outflow patterns? Why they get in step or out of step when just walking side by side or the one behind the other? Why stampede (or crowd crush) tragedies still happen and finally how much behaviour between pedestrians approaches behaviour between car drivers? Agent based, or crowd dynamics, simulations try to capture the underlying mechanisms of all the above, yet not always accurately. There are a number of validation studies towards trying to make such simulations more realistic but these tend to refer to quite limited scenarios with little impact to our everyday lives. The current PhD project would aim to: i) Optimise current agent based simulation approaches using latest numerical (e.g., machine learning) techniques for establishing the interaction component the individual receives when moving inside a crowd. As a starting point, validation would take place in real-world crowd scenarios, such of this of people crossing a bridge. ii) Blend the optimised tool(s) reproducing more realistic crowd motion and interactions between individuals, with standard design software. How good are the structural design approaches currently practiced, and what differences emerge from this blending operation are the novel research question targets. iii) Expand the above agent based simulation approaches to topics like traffic routing (micro-simulation models in SUMO) and designing for more efficient transport infrastructure or more compatible with future trends like that of autonomous driving. The research would be a joint effort between the School of Computing (Dr Evangelos Pournaras) and the School of Civil Engineering (Dr Nikolaos Nikitas) and would have a hybrid numerical and physical testing aspect. Off-the-shelve software like Oasys MassMotion would be used in this research and there will be close interaction with practicing engineers using agent based simulations and design software.

拟议的描述是直接源自邮政广告的；请参阅：为什么人们在越过桥梁时要按照自己的方式行动？为什么他们撤离（例如，在火灾或地震场景中）建筑物创建某些流出模式？当他们并排行走或另一个后面时，他们为什么要踏入脚步或走出脚步？为什么踩踏（或人群压迫）的悲剧仍会发生，最后，行人之间的行为对汽车司机之间的行为进行了多少行为？基于代理或人群动态的模拟试图捕获上述所有内容的基本机制，但并非总是准确的。有许多验证研究试图使此类模拟更现实，但是这些研究往往是指对我们的日常生活影响很小的情况。当前的博士学位项目的目的是：i）使用最新的数值（例如机器学习）技术优化基于当前代理的仿真方法，以确定个人在人群中移动时所收到的相互作用组件。作为起点，将在现实世界中的人群场景中进行验证，例如人们越过桥梁。 ii）混合优化的工具，将更现实的人群运动与个人之间的相互作用以及标准设计软件融合在一起。当前实践的结构设计方法有多好，与这种融合操作的差异是新颖的研究问题目标。 iii）将上述基于代理的仿真方法扩展到诸如交通路由（Sumo中的微型模拟模型）和设计更有效的运输基础架构或与未来趋势（如自主驾驶）兼容的主题。这项研究将是计算学院（Evangelos Pournaras博士）和土木工程学院（Nikolaos Nikitas博士）之间的共同努力，并具有混合数值和物理测试方面。这项研究将使用诸如Oasys MassMotion之类的悬空软件，并使用基于代理的仿真和设计软件与实践工程师进行密切相互作用。