School of Mathematical and Computing Science, Fiji National University, Ba, Fiji.
School of Science and Technology, University of New England, Armidale, NSW, Australia.
PLoS One. 2023 Sep 7;18(9):e0286810. doi: 10.1371/journal.pone.0286810. eCollection 2023.
Force mapping is an established method for inferring the underlying interaction rules thought to govern collective motion from trajectory data. Here we examine the ability of force maps to reconstruct interactions that govern individual's tendency to orient, or align, their heading within a moving group, one of the primary factors thought to drive collective motion, using data from three established general collective motion models. Specifically, our force maps extract how individuals adjust their direction of motion on average as a function of the distance to neighbours and relative alignment in heading with these neighbours, or in more detail as a function of the relative coordinates and relative headings of neighbours. We also examine the association between plots of local alignment and underlying alignment rules. We find that the simpler force maps that examined changes in heading as a function of neighbour distances and differences in heading can qualitatively reconstruct the form of orientation interactions, but also overestimate the spatial range over which these interactions apply. More complex force maps that examine heading changes as a function of the relative coordinates of neighbours (in two spatial dimensions), can also reveal underlying orientation interactions in some cases, but are relatively harder to interpret. Responses to neighbours in both the simpler and more complex force maps are affected by group-level patterns of motion. We also find a correlation between the sizes of regions of high alignment in local alignment plots and the size of the region over which alignment rules apply when only an alignment interaction rule is in action. However, when data derived from more complex models is analysed, the shapes of regions of high alignment are clearly influenced by emergent patterns of motion, and these regions of high alignment can appear even when there is no explicit direct mechanism that governs alignment.
力场映射是一种从轨迹数据中推断出潜在相互作用规则的方法，这些规则被认为是控制集体运动的基础。在这里，我们使用三个已建立的通用集体运动模型的数据，检查力场映射在多大程度上能够重建个体在移动群体中定向或对齐其头部的倾向的相互作用，这是驱动集体运动的主要因素之一。具体来说，我们的力场映射提取了个体如何根据与邻居的距离和相对头部对齐来平均调整其运动方向，或者更详细地根据邻居的相对坐标和相对头部来调整其运动方向。我们还研究了局部对齐图与潜在对齐规则之间的关联。我们发现，简单的力场映射检查了作为邻居距离和头部差异的函数的头部变化，可以定性地重建定向相互作用的形式，但也高估了这些相互作用适用的空间范围。更复杂的力场映射检查了作为邻居相对坐标的函数的头部变化（在二维空间中），在某些情况下也可以揭示潜在的定向相互作用，但相对难以解释。简单和更复杂的力场映射中对邻居的响应都受到群体运动模式的影响。我们还发现，局部对齐图中高对齐区域的大小与仅在存在对齐相互作用规则时对齐规则适用的区域的大小之间存在相关性。然而，当分析来自更复杂模型的数据时，高对齐区域的形状显然受到运动模式的影响，并且即使没有明确的直接机制来控制对齐，这些高对齐区域也可能出现。
