As travel demand grows in many cities around the world, overcrowding in public transport systems has become a major issue and has many negative effects for both users and operators. Measures to address on-board congestion span from large-scale strategic investments (e.g. increasing infrastructure capacity), through tactical planning (e.g. stopping pattern) to real-time operational measures (e.g. information provision, gate and escalator control). Thus there is a need to evaluate the impact of these measures prior to their implementation. To this end, this study aims at capturing the effective capacity utilization of the train, by considering passengers' distribution among individual train cars into an agent-based simulation model. The developed model is validated and applied to a case study for the Stockholm metro network. The findings suggest that an increase in peak hour demand leads to a more even passenger distribution among individual train cars, which partially counteracts the increased disutility caused by the higher passenger volumes. Interestingly, the closure of the most popular entrance point at one of the stations leads to lower train crowding unevenness at the downstream stops and consequently reduces passengers' experienced discomfort. We find that the user cost is significantly underestimated when passenger distribution among cars is not accounted for.

随着全球许多城市的出行需求不断增长，公共交通系统过度拥挤已成为一个主要问题，并对用户和运营商产生了许多负面影响。解决机上拥堵的措施从大规模战略投资（例如增加基础设施容量）到战术规划（例如停车模式）到实时操作措施（例如信息提供、门和自动扶梯控制）。因此，有必要在实施这些措施之前评估这些措施的影响。为此，本研究旨在通过将乘客在各个列车车厢之间的分布考虑到基于代理的仿真模型中来捕捉列车的有效容量利用率。开发的模型经过验证并应用于斯德哥尔摩地铁网络的案例研究。研究结果表明，高峰时段需求的增加导致各个列车车厢之间的乘客分布更均匀，这在一定程度上抵消了因乘客量增加而导致的不效用增加。有趣的是，其中一个车站最受欢迎的入口点的关闭导致下游车站的列车拥挤程度降低，从而减少了乘客的不适感。我们发现当不考虑汽车之间的乘客分配时，用户成本被显着低估。关闭其中一个车站最受欢迎的入口点可以降低下游车站的列车拥挤程度，从而减少乘客的不适感。我们发现当不考虑汽车之间的乘客分配时，用户成本被显着低估。关闭其中一个车站最受欢迎的入口点可以降低下游车站的列车拥挤程度，从而减少乘客的不适感。我们发现当不考虑汽车之间的乘客分配时，用户成本被显着低估。