Liao Weichen, Kemloh Wagoum Armel U, Bode Nikolai W F
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, People's Republic of China
Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, Jülich 52428, Germany.
J R Soc Interface. 2017 Feb;14(127). doi: 10.1098/rsif.2016.0684.
In moving pedestrian crowds, the distribution of individuals over different available routes emerges from the decisions of individuals that may be influenced by the actions of others. Understanding this phenomenon not only is important for research into collective behaviour, but also has practical applications for building safety and event management. Here, we study the mechanisms underlying pedestrian route choice, focusing on how time-independent information, such as path lengths, and time-dependent information, such as queue lengths, affect both initial decisions and subsequent changes in route choices. We address these questions using experiments with nearly 140 volunteers and an individual-based model for route choice. Crucially, we consider a wide range of route choice scenarios. We find that initial route choices of pedestrians achieve a balanced usage of available routes. Our model suggests that pedestrians performing trade-offs between exit widths and predicted exit crowdedness can explain this emergent distribution in many contexts. Few pedestrians adjust their route choice in our experiments. Simulations suggest that these decisions could be explained by pedestrians comparing estimates of the time it would take them to reach their target using different routes. Route choice is complex, but our findings suggest that conceptually simple behaviours may explain many movement decisions.
在移动的行人 crowds 中,个体在不同可用路线上的分布源于个体的决策,而这些决策可能会受到他人行为的影响。理解这一现象不仅对集体行为研究很重要,而且对建筑安全和活动管理也有实际应用价值。在此,我们研究行人路线选择背后的机制,重点关注诸如路径长度等与时间无关的信息以及诸如队列长度等与时间相关的信息如何影响初始决策和后续路线选择的变化。我们通过对近 140 名志愿者进行实验以及使用基于个体的路线选择模型来解决这些问题。至关重要的是,我们考虑了广泛的路线选择场景。我们发现行人的初始路线选择实现了对可用路线的平衡使用。我们的模型表明,行人在出口宽度和预测的出口拥挤程度之间进行权衡可以在许多情况下解释这种出现的分布。在我们的实验中,很少有行人调整他们的路线选择。模拟表明,这些决策可以通过行人比较使用不同路线到达目标所需时间的估计值来解释。路线选择很复杂,但我们的研究结果表明,概念上简单的行为可能解释许多移动决策。