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.

得益于追踪技术的发展与普及——如今智能手机已将其作为标配功能，人类移动行为研究已成为一门可及性极高的研究领域。
本文以西班牙巴塞罗那一场公共户外博览会为例，展示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，研究人员对穿梭于设有各类吸引人流的活动展位的开放空间中的参与者进行了追踪。
本研究构建了一套基于朗之万动力学（Langevin Dynamics）的通用建模框架，用于检验两类截然不同的影响因素对移动行为的作用：其一为反应式（或情境依赖型）因素，通过给定空间配置下由吸引点生成的力场进行建模；其二为主动式（或固有型）因素，基于受试者的内在运动模式进行建模。
这套兼具叠加性与构建性的建模框架能够复现部分已观测到的移动行为特征。本研究以最简单的纯随机游走模型作为基准参照，逐步引入持久性、记忆性与感知景观等不同影响因素，旨在厘清主动式与反应式因素各自的贡献程度，并量化其相对重要性。
本研究所提出的方法，有望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。