选择雪崩：陌生人之间的互动如何塑造人群动态
Avalanches of choice: how stranger-to-stranger interactions shape crowd dynamics
AI总结：
研究通过分析真实人群在列车站路线分流中的行为，发现个体倾向于跟随前方人的路径，即使导致更长的行程时间，这种倾向导致人群动态的突发性模式，揭示了局部模仿行为对集体路线选择的主导作用。
摘要：
行人路线选择在塑造集体人群动态中起关键作用，但陌生人之间互动的影响仍不明确。本研究利用三年高分辨率轨迹数据，分析了列车站路线分流处的真实行人行为，发现个体即使在无社会联系且行程时间更长的情况下，也倾向于跟随前方人的路径，导致突发性动态，即连续行人做出相同决策，形成集体运动的强模式。我们采用包含路线成本、随机性和社会模仿的随机模型，准确重现了观察到的行为，强调局部模仿行为是集体路线选择的主要驱动因素。这些发现突显了陌生人之间短暂、低层次互动如何影响大规模人群运动，对人群管理、城市设计和公共空间的社会行为理解具有重要影响。
英文摘要：
Pedestrian routing choices play a crucial role in shaping collective crowd dynamics, yet the influence of interactions among unfamiliar individuals remains poorly understood. In this study, we analyze real-world pedestrian behavior at a route split within a busy train station using high-resolution trajectory data collected over a three-year time frame. We disclose a striking tendency for individuals to follow the same path as the person directly in front of them, even in the absence of social ties and even when such a choice leads to a longer travel time. This tendency leads to bursty dynamics, where sequences of pedestrians make identical decisions in succession, leading to strong patterns in collective movement. We employ a stochastic model that includes route costs, randomness, and social imitation to accurately reproduce the observed behavior, highlighting that local imitation behavior is the dominant driver of collective routing choices. These findings highlight how brief, low-level interactions between strangers can scale up to influence large-scale pedestrian movement, with strong implications for crowd management, urban design, and the broader understanding of social behavior in public spaces.
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