Agent Based Modelling in Practical Engineering Applications

所提出的描述直接来源于邮政广告；看：为什么人们在过桥时要这样移动？为什么他们会疏散（例如，在火灾或地震的情况下）建筑物，从而产生特定的外流模式？为什么当他们肩并肩或一个跟着另一个走路时，他们会步调一致或不一致？为什么踩踏（或人群挤压）悲剧仍然发生，最后行人之间的行为接近汽车司机之间的行为有多少？基于主体或群体动力学的模拟试图捕捉上述所有潜在机制，但并不总是准确的。有许多验证研究试图使这样的模拟更真实，但这些往往是指相当有限的场景，对我们的日常生活几乎没有影响。当前的博士项目将旨在：i)使用最新的数值（例如，机器学习）技术来优化当前基于代理的模拟方法，以建立个体在人群中移动时接收到的交互组件。作为起点，验证将在现实世界的人群场景中进行，例如过桥的人。ii)将优化的工具与标准的设计软件混合在一起，重现更真实的人群运动和个人之间的互动。目前实践的结构设计方法有多好，以及这种混合操作产生的差异是新的研究问题目标。iii)将上述基于智能体的仿真方法扩展到交通路由（SUMO中的微观仿真模型）和设计更高效的交通基础设施或更适应自动驾驶等未来趋势等主题。这项研究将由计算机学院（Evangelos Pournaras博士）和土木工程学院（Nikolaos Nikitas博士）共同努力，并将有一个混合的数值和物理测试方面。像Oasys MassMotion这样的现成软件将在这项研究中使用，并且将与使用基于代理的模拟和设计软件的实践工程师密切互动。

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.