This repo contains the raw data found from running experiments and the code for analysis for Analyzing the Robustness of Adaptive Traffic Control System Using Reinforcement Learning for Urban Traffic Flow. A slightly modified version of LibSignal was used as a testbed for the experiments. The details of how the experiment was run is explained in the Modified LibSignal repo. Two scenarios were tested here: Grid 4x4 Scenario and Ingolstadt Scenario.
The raw data from the experiments can be found in grid4x4 and ingo folders. The data is divided into models and cases folderwise. The summary folder contains data regarding recovery time.
The graphs for the Grid 4x4 scenario is found in grid.ipynb and grid_2.ipynb and for the Ingolstadt scenario is found in ingo.ipynb and ingo_2.ipynb. The make_summary.py script was used for making the data in the summary folder.