Simultaneous Demand Prediction and Planning

Dependencies

Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML

Data

POI: data/poi
Road network: data/roadnet
Transportation: data/transportation
Station profile: data/station_list
Charging records: data/station
Station profile and charging records can be collected in Star Charge APP.

Experiments

1. Evaluations of charging demand prediction
   python model/run.py --source SOURCE_CITY --target TARGET_CITY --model MODEL_NAME
2. Evaluations based on real plans
   
   1. Even, CG, Real, TIO: python real_world.py
   2. Park: python real_world_parking.py
   3. Pop: python real_world_population.py
3. Evaluations with varied budgets
   python evaluation_varied_budget.py
4. Evaluations with optimal solution
   python optimal_comparison_BF_tio.py