"DeepQ-Charge Dataset for MCS Routing"

"The dataset contains the processed inputs used to generate the simulation environment for evaluating the DeepQ-Charge framework. It is derived from publicly available urban mobility records and includes spatial grid mappings, spatio-temporal demand distributions, and derived charging-demand attributes used to simulate EV charging requests. The processed data provide the inputs required to generate charging-demand intensity maps, demand prediction features, and request-generation streams used by the simulation framework. These data enable the evaluation of mobile charging station dispatch policies under realistic large-scale urban mobility conditions. The dataset supports reproducibility of the experiments and enables benchmarking of alternative mobile charging dispatch strategies under the same demand conditions. The original raw mobility dataset used for preprocessing is publicly available from the NYC Taxi and Limousine Commission (TLC) Open Data portal."