Abstract

A foreseeable challenge with a substantial increase in railway mode share will be how to uphold punctuality. Higher volumes of train traffic will result in timetables that are more sensitive to disruptions; whose severity and frequency is also expected to increase in light of greater asset utilization and climate change. This calls for a definitive understanding of the relationship between incidents and train delays as a prerequisite to developing robust timetables and disruption management strategies. In this paper we propose a novel framework for quantifying the impact of railway incidents on train delays. Using a case of the Swedish Railway Network, we compare the impact of different incidents on train delays. The impact of delay is defined as a factor of the incident rate, exposure rate, delay rate and historical average delay minutes per incident. A logistic model that estimates the probability of delay for any train, in the event of a failure, is also developed. Snow on track was established as most critical, resulting in the highest normalized delay minutes per train and the largest increase in the odds of delay for individual trains. The proposed framework & approach can be applied to other networks.

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