Resilience of Traffic Networks under Non-Equilibrium Learning

The dataset used in the paper is a transportation network, which is a directed, finite, and connected graph G = (V, E) without self-loops. The vertices V represent road junctions, and the edges E represent road segments. The set of distinct origin-destination (OD) pairs is W ⊆ V × V, indexed by w, with cardinality W.