Bottlenecks have significant impact on routing options and network exploitation. Therefore, it is essential to know the location of critical areas in order to use the existing infrastructure more efficiently and to expand the network appropriately. This paper presents a method to identify bottlenecks based on delays and to weight them by their significance. As delays can be derived from operational data or from simulations, statements about past operating conditions or forecasts based on simulated operating conditions are possible.The method considers the occurrence of delays at one location and delay increases based on trains' initial delays. It aims to weight additional delay increases higher for punctual trains compared to already heavily delayed trains. This reflects that a deviation from planned times of trains without initial delays has particularly negative impacts on operational quality as these disruptions are indicators for bottlenecks and can lead to delay propagations. Additional delays for already highly delayed trains however have lower significance for operational quality. Furthermore, such delays are often caused by the already existing deviation from the timetable and do not necessarily indicate a bottleneck. Therefore, delays are categorised.Both delay increases and delay category changes can be weighted based on the affected train type to calculate the bottleneck's severity. This gives information on the specific infrastructure's significance concerning the networks performance. Sorting investigated railway lines and stations by their severity gives an overview on the most
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