Effects of Social Interactions in Self-Organising Railway Traffic Management (opens in new tab)

Fabio Oddi, Federico Naldini, Leo D'Amato, Grégory Marlière, Paola Pellegrini, Vito Trianni Recent research is exploring self-organised traffic management as a solution for scaling to complex real-world networks. In such a system, trains predict their neighbourhood, produce traffic plan hypotheses, and agree via consensus with neighbours on a future traffic plan to be implemented. This paper investigates a structural parameter within this pipeline: the predictive neighbourhood horizon. The ho...