Integrating perspectives of mobility for spatially-explicit Agent-Based Modelling

集成空间显式基于代理的建模的移动视角

• 批准号: RGPIN-2022-04342
• 负责人: Sengupta, Raja
• 金额: $ 1.82万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754826
• 关键词: Integrating; perspectives; mobility; spatially; explicit

Agent--Based simulations of mobile objects are widespread, from modeling movement of people inside buildings to animals (and animal groups) in habitats. One integrating factor in simulating movement via Agent--Based Models (ABMs) are wayfinding algorithms, although implementation varies by disciplines. Given that there have been recent calls for integrated approach to mobility, this proposal suggests 3 multidisciplinary strategies to improve wayfinding in ABMs: (1) Utilize least cost -surfaces to generate 3D topology (2) Utilize high frequency movement data to extract probability surfaces guiding movement, and (3) Combine the methods developed above with visual models from pedestrian simulations (e.g., exosomatic visual architecture) to consider multiple factors governing motion. For step one, recent developments, including high resolution satellite imagery and 3D building models, afford the creation of least cost surfaces that can be used to develop detailed wayfinding algorithms with very high spatial and temporal accuracies which are also efficient. Moving in this direction, GIScience research has utilized 3D building models to develop 3D topology to support emergency evacuation planning, and making use of 3D topology for emergency evacuations from multi-storied buildings is a recurrent theme of several journal publications. They primarily work by identifying the shortest path (using standard algorithm such as Djisktra's) in this 3D network, with the goal of showing the user an efficient egress route from their current location to a building exit point. Least cost surfaces can be utilized to develop a global model of spatial distance between points of origin and destination, and then converted into a vector--based 3D topology. The next step is to devise a method of generating "probability surfaces", which utilizes high frequency movement data for both animals and humans. The volume of this data, combined with high resolution remote sensing data, provides an opportunity for the use of geospatial operators and machine learning to extract probabilities of locations where movement may occur (presented as a continous raster layer). The final step will be to link behavioural and visual concepts (e.g., exosomatic visual architecture) from pedestrian simulation and extend to movement ecology, for example, by deriving virtual 3D environments from high resolution satellite data and improving animal behavioural simulations based on a frontal perspective. It is expected that the new algorithms will prove useful in building mobile agents across a wide spectrum of applications. These include ABM models of building evacuation using highly detailed 3D building models, pedestrians in a detailed neighbourhood, and animal movement in their habitats. Combined with higher spatial resolution datasets and 3D building models, such improvements are almost a necessity to improve ABM simulation accuracy as well as reduce computational loads.

基于智能体的移动对象模拟广泛存在，从建筑物内的人的运动建模到栖息地中的动物(和动物群体)。通过基于代理的模型(ABM)模拟运动的一个集成因素是寻路算法，尽管实现方式因学科而异。鉴于最近有人呼吁采用综合的方法来解决移动问题，该建议提出了3种多学科策略来改进ABM中的路径发现：(1)利用最低成本的表面来生成3D拓扑；(2)利用高频运动数据来提取引导运动的概率表面；(3)将上述方法与行人模拟(例如外部视觉建筑)中的视觉模型相结合，以考虑控制运动的多种因素。第一步，最近的发展，包括高分辨率卫星图像和3D建筑模型，提供了创建成本最低的表面，这些表面可以用来开发具有非常高的空间和时间精度的详细路线查找算法，这些算法也是有效的。在这个方向上，GIScience研究已经利用3D建筑模型来开发3D拓扑来支持紧急疏散规划，并且利用3D拓扑来从多层建筑进行紧急疏散是几个期刊出版物反复出现的主题。它们主要通过识别3D网络中的最短路径(使用Djisktra的标准算法)来工作，目标是向用户显示从他们当前位置到建筑物出口点的有效出口路线。最小代价曲面可用于建立起点和终点之间的空间距离的全局模型，然后将其转换为基于矢量的3D拓扑。下一步是设计一种生成“概率面”的方法，该方法利用动物和人类的高频运动数据。这些数据与高分辨率遥感数据相结合，为使用地理空间运算符和机器学习提取可能发生移动的位置的概率提供了机会(以连续栅格层的形式表示)。最后一步将是将行人模拟中的行为和视觉概念(例如，外部视觉结构)联系起来，并扩展到运动生态，例如，通过从高分辨率卫星数据导出虚拟3D环境，以及基于正面视角改进动物行为模拟。预计新算法将被证明在构建广泛应用的移动代理方面有用。其中包括ABM模型，该模型使用非常详细的3D建筑模型、详细社区中的行人以及栖息地中的动物运动来进行建筑物疏散。结合更高的空间分辨率数据集和3D建筑物模型，这样的改进对于提高ABM模拟精度以及减少计算量几乎是必要的。