Researchers in Utrecht have used a large database of railway data to analyse the main causes of nation-wide railway network disruptions. This delay model will make it possible to calculate at any moment in time the likelihood of such a severe disruption occurring. The researchers published their results earlier this month in the academic journal PLOS ONE.
For their publication, the researchers studied the development of nation-wide disruptions of the Dutch rail network. Mark Dekker, the publication’s lead author: “These are cases in which delays accumulate and expand, for example because several conductors find themselves stuck in a delayed train. In these cases, delays can spread through the rail network like an oil stain. It doesn’t happen very often; only around five times per year. But when it does happen, it’s very serious.”
“My first challenge was to capture the macro-dynamics of the entire rail system in a single diagram”, Dekker explains. His analysis resulted in a two-dimensional ‘delay index’, which reflects the total amount of delays on every route, as well as the general location of the delay, at a chosen moment in time. This allows Dekker to calculate the likelihood that the current situation will get out of control and cause a nation-wide rail service disruption at a given time. “For example, the system can issue an alarm if the probability rises above a certain percentage. At that point, measures may have to be taken to prevent such an ‘oil stain’ effect from occurring.”
Two main sources
Two railway trajectories appear to be main sources of national rail disruptions. “A disruption around Groningen normally has little influence on the total amount of delays in the Netherlands. But the rail connections to our neighbouring countries appear to have much more of an effect.” That means the routes from Amsterdam to Germany via Arnhem, and from Amsterdam to Belgium via Rotterdam. “And the problem can be exacerbated by the interplay between those two routes. The interaction between these two trajectories can have a decisive effect on delays elsewhere in the network.”
Dekker is currently conducting his PhD research at Utrecht University’s Centre for Complex Systems Studies, with PhD supervisors from the fields of Computer Science and Physics. “Before this, I did a Master’s in Climate Physics. That might sound like a strange switch, but some methods I’m currently using for the railway network are also used in climate research. I made a deliberate choice to study this subject, because I wanted to do something with applications for society at large.”
Predicting transitions across macroscopic states for railway systems
Mark M. Dekker, Debabrata Panja, Henk A. Dijkstra, Stefan C. Dekker
PLOS ONE, 6 June 2019, DOI 10.1371/journal.pone.0217710
* All authors are affiliated with Utrecht University.
This project was financed under an NWO Complexity in Transport and Logistics grant.Be the first to comment