Data from: Active and reactive behaviour in human mobility: the influence of attraction points on pedestrians

Human mobility is becoming an accessible field of study thanks to the progress and availability of tracking technologies as a common feature of smart phones. We describe an example of a scalable experiment exploiting these circumstances at a public, outdoor fair in Barcelona (Spain). Participants were tracked while wandering through an open space with activity stands attracting their attention. We develop a general modeling framework based on Langevin Dynamics, which allows us to test the influence of two distinct types of ingredients on mobility: reactive or context-dependent factors, modelled by means of a force field generated by attraction points in a given spatial configuration, and active or inherent factors, modelled from intrinsic movement patterns of the subjects. The additive and constructive framework model accounts for some observed features. Starting with the simplest model (purely random walkers) as a reference, we progressively introduce different ingredients such as persistence, memory, and perceptual landscape, aiming to untangle active and reactive contributions and quantify their respective relevance. The proposed approach may help in anticipating the spatial distribution of citizens in alternative scenarios and in improving the design of public events based on a facts-based approach.

得益于追踪技术的进步与普及——如今智能手机已普遍集成此类功能，人类移动行为（human mobility）已成为一门易于开展的研究领域。本文以西班牙巴塞罗那的一场公共户外展会为例，介绍了一项利用上述技术条件开展的可规模化实验：实验过程中，参与者在设有各类吸引注意力的活动展位的开放空间内漫步时，其移动轨迹被追踪记录。本文构建了一个基于朗之万动力学（Langevin Dynamics）的通用建模框架，可用于检验两类截然不同的构成要素对移动行为的影响：一类是反应性/情境依赖型因素，通过给定空间配置下吸引点生成的力场进行建模；另一类是主动性/固有型因素，基于受试者的内在移动模式建模。该叠加式构建框架能够契合部分已观测到的移动行为特征。我们以最简单的模型（纯随机游走者）作为参照基准，逐步引入运动持久性、记忆性与感知景观等不同构成要素，旨在厘清主动性与反应性因素的贡献，并量化二者各自的相关性。本研究提出的方法，可用于预测不同场景下民众的空间分布，并助力基于实证的公共活动设计优化。