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.

建议的描述是直接从广告中派生出来的;请参阅：为什么人们过桥时会这样移动？他们为什么撤离（例如，在火灾或地震的情况下）建筑物产生一定的流出模式？为什么他们只是并排或一个在另一个后面走路时会步调一致或不一致？为什么踩踏（或人群拥挤）的悲剧仍然发生，最终有多少行人之间的行为接近汽车司机之间的行为？基于代理或群体动力学的模拟试图捕捉所有上述的潜在机制，但并不总是准确的。有一些验证研究试图使这种模拟更加逼真，但这些研究往往涉及非常有限的场景，对我们的日常生活影响不大。目前的博士项目旨在：i）优化当前基于代理的模拟方法，使用最新的数值（例如，机器学习）技术，用于建立个体在人群中移动时接收的交互分量。作为一个起点，验证将发生在现实世界的人群场景中，比如人们过桥。ii）将优化的工具与标准设计软件相结合，再现更逼真的人群运动和个体之间的互动。如何好的结构设计方法目前实行的，从这种混合操作出现的差异是新的研究问题的目标。iii）将上述基于智能体的仿真方法扩展到交通路线（SUMO中的微观仿真模型）等主题，并设计更高效的交通基础设施或更符合自动驾驶等未来趋势。该研究将是计算机学院（Evangelos Pournaras博士）和土木工程学院（Nikolaos Nikitas博士）之间的共同努力，并将具有混合数值和物理测试方面。Oasys MassMotion等现成软件将用于本研究，并将与使用基于代理的模拟和设计软件的实践工程师进行密切互动。