Code implementation for "DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning"
This repo is contributed by Prof. Xinwu Qian (U Alabama), Shuocheng Guo (U Alabama), and Vaneet Aggarwal (Purdue).
This research work is accepted by Transportation Research Part C: Emerging Technologies, and the preprint (initial version) can be found at ArXiv.
We are happy to help if you have any questions. If you used any part of the code, please cite the following paper:
@article{qian2022drop, title={DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning}, author={Qian, Xinwu and Guo, Shuocheng and Aggarwal, Vaneet}, journal={Transportation Research Part C: Emerging Technologies}, volume={145}, pages={103923}, year={2022}, publisher={Elsevier} }
The preprocessed large files as data inputs can be fecthed via OneDrive.
** Note: if the link doesn't work, please contact Shuocheng (sguo18@ua.edu) for updated link.
1.1. INSTALL: conda install skimage conda install -c anaconda sqlalchemy conda install -c conda-forge polyline
2.0. root folder - experiment: initalize vehicle location, populate vehicles, enter market, match, dispatch, and update. - main: run the simulation and DQN learning(if enabled), record metrics. - parse_results: preliminary result processing and visualization
2.1. central agent: MATCH vehciles and request, calculate cost per request
2.2. common: get and solve spatial infomation, get current time
2.3. config: spatial settings and time/time step settings.
2.4. data: preprocessed data
2.5. db: path for database
2.6. dqn agent: vehicles that learning DISPATCH policy with DQN
2.7. dummy agent: vehicles that follows fixed DISPATCH and MATCH policy.
2.8. logger: a directory for paths that saves results
2.9. logs:
2.10. novelties: sets of codes to present various types of agents, vehicle category, vehicle status, customer perferences.
2.11. osrm/osrm-backend: for OSRM Engine deployment
2.12. simulator
- models: customer and vehicles
- service: demand generation, routing, sending requests to OSRM engine
- simulator: key processes of vehcile-customer interaction
- settings: config for simulation
2.13. tools: driver for saving files, dot dictionary to save parameters.