基于车流量检测的道路交通控制系统的设计python代码.zip

# sumolights SUMO adaptive traffic signal control - DQN, DDPG, Webster's, Max-pressure, Self-Organizing Traffic Lights Technical details available at [An Open-Source Framework for Adaptive Traffic Signal Control](https://arxiv.org/abs/1909.00395) ## Setup Install SUMO traffic microsimulator by [following instructions here](https://sumo.dlr.de/wiki/Installing) (v1.2). Using Python 3, create a virtual environment and then install dependancies with: ``` pip install -r requirements.txt ``` ## Comparing adaptive traffic signal controllers First train reinforcement learning controllers: ``` ./train_dqn.sh ./train_ddpg.sh ``` Then execute simulations to generate performance results for all controllers: ``` ./gen_results.sh ``` Visualize results with: ``` python graph_results.py ```   ## Optimizing hyperparameters Search for optimal hyperparameters for each controller: ``` ./hp_optimization ``` Warning, search for reinforcement learning can require significant compute time! Visualize hyperparameters with: ``` python graph_results.py -type hp ```