@article{monechi_2018, author = {Monechi, Bernardo and Gravino, Pietro and Di Clemente, Riccardo and Servedio, Vito DP},journal = {EPJ Data Science},note = {creativity},number = {1},pages = {35},publisher = {Springer},title = {Complex delay dynamics on railway networks from universal laws to realistic modelling},volume = {7},year = {2018},url = {https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-018-0160-x},abstract = {

Railways are a key infrastructure for any modern country. The reliability and resilience of this peculiar transportation system may be challenged by different shocks such as disruptions, strikes and adverse weather conditions. These events compromise the correct functioning of the system and trigger the spreading of delays into the railway network on a daily basis. Despite their importance, a general theoretical understanding of the underlying causes of these disruptions is still lacking. In this work, we analyse the Italian and German railway networks by leveraging on the train schedules and actual delay data retrieved during the year 2015. We use these data to infer simple statistical laws ruling the emergence of localized delays in different areas of the network and we model the spreading of these delays throughout the network by exploiting a framework inspired by epidemic spreading models. Our model offers a fast and easy tool for the preliminary assessment of the effectiveness of traffic handling policies, and of the railway network criticalities.

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