Code for paper:
Optimizing corridor-level transit efficiency: multi-agent reinforcement learning with multi-discrete actions leveraging connected vehicle data for transit priority.
This repository accompanies the publication:
https://doi.org/10.1016/j.ijtst.2025.07.010
This research uses MAPPO and Centralized Training and Decentralized Execution (CTDE) to train and optimize the Transit Signal Priority (TSP) in corridors.
ytj254/TSP-MAPPO
Folders and files
| Name | Name | Last commit date | ||
|---|---|---|---|---|