Demand for public transport has witnessed a steady growth over the last decade in many densely populated cities around the world. However, capacity has not always matched this increased demand. As such, passengers experience long waiting times and are denied boarding during the peak hours. Crowded platforms and the subsequent customer dissatisfaction and safety issues have become a serious concern. The COVID-19 pandemic has dramatically reduced passengers’ willingness to board crowded trains, causing a surge in demand for real-time crowding information. In this paper, we propose a real-time predictive decision support platform which addresses both, operations control and customer information needs. The system provides crowding predictions on trains and platforms, communicates this information to passengers, and takes into account their response to it. It is demonstrated through a case study that providing predictive information to passengers can potentially reduce denied boarding and lead to better utilization of train capacity.

在过去十年中，全球许多人口稠密的城市对公共交通的需求稳步增长。然而，容量并不总是与这种增加的需求相匹配。因此，乘客会经历漫长的等待时间，并在高峰时段被拒绝登机。拥挤的平台以及随之而来的客户不满和安全问题已成为一个严重的问题。COVID-19 大流行大大降低了乘客乘坐拥挤列车的意愿，导致对实时拥挤信息的需求激增。在本文中，我们提出了一个实时预测决策支持平台，可以同时满足运营控制和客户信息需求。该系统在火车和月台上提供拥挤预测，并将此信息传达给乘客，并考虑到他们对此的反应。案例研究表明，向乘客提供预测信息可能会减少拒绝登机并更好地利用列车容量。