RDRanking

The dataset is constructed using SUMO. It contains two road network datasets of different scales: a small-scale network (SR) and a larger regional network in Shenyang (SY). The dataset was constructed using the SUMO simulation platform, containing two road network datasets at different scales: a small-scale test network (SR) and a regional-level Shenyang network (SY). The SR network comprises 110 road segments, while the SY network contains 514 segments. Each segment includes features (e.g., speed limit, number of lanes, etc.) and importance labels. To obtain the ground-truth ranking of segment importance, we implemented the following procedure: First, a road segment was considered "failed" when its average travel speed dropped below 10% of the speed limit. We then artificially simulated failure conditions by sequentially reducing each segment's maximum speed limit to 10% of its original value. During specified time windows, we recorded the impact of each segment's failure on the overall network efficiency, using this Efficiency Degradation (ED) value as the importance score for the corresponding segment..