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.

基于代理的移动物体模拟是广泛的，从建筑物内部建筑物的运动到栖息地中的动物（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，尽管实现会因学科而变化。鉴于最近有一些呼吁综合行动能力，该提案提出了3种改进ABM中寻路的多学科策略：（1）利用成本最低的曲面来生成3D拓扑（2）利用高频移动数据利用概率表面来提取概率表面的指导移动，并将视觉范围的模型（3）结合到驾驶员模型（3））（3）（3）（3） 运动。对于第一步，最近的发展，包括高分辨率卫星图像和3D建筑模型，可以提供最低的成本表面，这些表面可用于开发具有非常高的空间和时间精确度的详细寻路算法，这些算法也有效。 朝着这个方向发展，Giscience Research利用3D建筑模型来开发3D拓扑来支持紧急撤离计划，并利用3D拓扑来从多层建筑物中进行紧急撤离，这是几种期刊出版物的经常性主题。它们主要是通过在此3D网络中识别最短路径（使用标准算法（例如Djisktra's））来工作，目的是向用户展示从当前位置到建筑物出口点的有效出口路线。最低的成本表面可以用于开发出来源点和目的地之间空间距离的全局模型，然后转换为基于矢量的3D拓扑。下一步是设计一种生成“概率表面”的方法，该方法利用动物和人类的高频运动数据。这些数据的体积，结合高分辨率遥感数据，为使用地理空间操作员和机器学习提供了一个机会，以提取可能发生移动的位置的概率（以持续的栅格层表示）。最后一步是将行为和视觉概念（例如，外膜视觉体系结构）从行人模拟链接，并扩展到运动生态学，例如，通过从高分辨率卫星数据中得出虚拟3D环境，并根据额叶的观点改善动物行为模拟。预计新算法将被证明可用于在各种应用程序中构建移动代理。其中包括使用高度详细的3D建筑模型，详细街区的行人以及其栖息地中的动物运动的ABM模型。结合较高的空间分辨率数据集和3D构建模型，此类改进几乎是提高ABM模拟精度并减少计算负载的必要条件。