School of Architecture and Civil Engineering, University of Wuppertal, Wuppertal, Germany.
Institute for Advanced Simulation, Forschungszentrum Jülich, Jülich, Germany.
PLoS One. 2023 Mar 15;18(3):e0282526. doi: 10.1371/journal.pone.0282526. eCollection 2023.
To investigate the impact of social groups on waiting behaviour of passengers at railway platforms a method to identify social groups through the monitoring of distances between pedestrians and the stability of those distances over time is introduced. The method allows the recognition of groups using trajectories only and thus opens up the possibility of studying crowds in public places without constrains caused by privacy protection issues. Trajectories from a railway platform in Switzerland were used to analyse the waiting behaviour of passengers in dependence of waiting time as well as the size of social groups. The analysis of the trajectories shows that the portion of passengers travelling in groups reaches up to 10% during the week and increases to 20% on the weekends. 60% of the groups were pairs, larger groups were less frequent. With increasing group size, the mean speed of the members decreases. Individuals and pairs often choose waiting spots at the sides of the stairs and in vicinity of obstacles, while larger groups wait close to the platform entries. The results indicate that passengers choose waiting places according to the following criteria and ranking: shortest ways, direction of the next intended action, undisturbed places and ensured communication. While individual passengers often wait in places where they are undisturbed and do not hinder others, the dominating comfort criterion for groups is to ensure communication. The results regarding space requirements of waiting passengers could be used for different applications. E.g. to enhance the level of service concept assessing the comfort of different types of users, to avoid temporary bottlenecks to improve the boarding and alighting process or to increase the robustness of the performance of railway platforms during peak loads by optimising the pedestrian distribution.
为了研究社会群体对铁路月台乘客候车行为的影响，引入了一种通过监测行人间的距离及其随时间的稳定性来识别社会群体的方法。该方法仅使用轨迹即可识别群体，从而为研究公共场所的人群提供了可能性，而不会受到隐私保护问题造成的限制。使用来自瑞士一个铁路月台的轨迹来分析乘客在候车时间以及社会群体规模方面的候车行为。对轨迹的分析表明，在一周内，群体出行的乘客比例高达 10%，周末时增至 20%。60%的群体是两人组，更大的群体则较为少见。随着群体规模的增大，成员的平均速度会降低。个体和两人组经常选择在楼梯旁和障碍物附近的等候点，而较大的群体则在靠近月台入口处等候。结果表明，乘客会根据以下标准和优先级来选择等候位置：最短路径、下一个预期动作的方向、无干扰的地方和确保通信。虽然个体乘客经常选择在不受干扰且不妨碍他人的地方等候，但群体的主要舒适标准是确保通信。有关等候乘客空间需求的结果可用于不同的应用。例如，通过评估不同类型用户的舒适度来增强服务水平概念，避免临时瓶颈以改善上下车过程，或通过优化行人分布来提高铁路月台在高峰负荷期间的性能稳健性。
