Mesoscopic Modelling of Pedestrian Movement Using C arma and Its Tools
Mesoscopic Modelling of Pedestrian Movement Using C arma and Its Tools
复制标题
使用 Carma 及其工具进行行人运动的细观建模
DOI：
10.1145/3155338
复制
发表时间：
2018
影响因子：
0.9
通讯作者：
Galpin V
中科院分区：
文献类型：
--
作者：
Galpin V
在这篇文章中，我们评估的适合性theCarma（集体自适应资源共享马尔可夫代理）建模语言中观建模的空间分布系统，所需的模型之间的个人为基础的（微观）空间模型和人口为基础的（宏观）空间模型。我们的建模方法本质上是介观的，因为它不将个体的运动建模为二维空间中基于代理的模拟，也不使用偏微分方程对个体群体的密度进行连续空间近似。我们考虑的应用程序是行人运动沿着路径表示为一个有向图。在所提出的模型中，行人沿着路径段移动的速率，由其他行人的存在，并使他们的选择的路径段下一个交叉路口的路径。路径网络的拓扑结构和地形的景观信息可以表示为单独的功能和空间方面的模型，利用Carmalanguage结构表示空间。我们使用模拟研究的路径拓扑结构的变化对系统动力学的影响，并显示如何Carmaprovides合适的建模语言结构，使它简单地改变拓扑结构的路径和其他空间方面的模型，而不完全重组Carmamodel。我们的研究结果表明，很难预测网络结构变化的影响，即使是很小的变化也会产生显着的影响。
In this article, we assess the suitability of theCarma(Collective Adaptive Resource-sharing Markovian Agents) modelling language for mesoscopic modelling of spatially distributed systems where the desired model lies between an individual-based (microscopic) spatial model and a population-based (macroscopic) spatial model. Our modelling approach is mesoscopic in nature because it does not model the movement of individuals as an agent-based simulation in two-dimensional space, nor does it make a continuous-space approximation of the density of a population of individuals using partial differential equations. The application that we consider is pedestrian movement along paths that are expressed as a directed graph. In the models presented, pedestrians move along path segments at rates that are determined by the presence of other pedestrians, and make their choice of the path segment to cross next at the intersections of paths. Information about the topology of the path network and the topography of the landscape can be expressed as separate functional and spatial aspects of the model by making use of Carmalanguage constructs for representing space. We use simulation to study the impact on the system dynamics of changes to the topology of paths and show how Carmaprovides suitable modelling language constructs that make it straightforward to change the topology of the paths and other spatial aspects of the model without completely restructuring the Carmamodel. Our results indicate that it is difficult to predict the effect of changes to the network structure and that even small changes can have significant effects.