Model = TrainModel(config['num_layers'],
config['width_layers'],
config['batch_size'],
config['learning_rate'],
input_dim=config['num_states'],
output_dim=config['num_actions'])
Memory = Memory(config['memory_size_max'], config['memory_size_min'])
TrafficGen = TrafficGenerator(config['max_steps'], config['n_v_generated'])
Visualization = Visualization(path, dpi=96)
Simulation = Simulation(Model, Memory, TrafficGen, sumo_cmd,
config['gamma'], config['max_steps'],
config['green_duration'],
config['yellow_duration'], config['num_states'],
config['num_actions'], config['training_epochs'])
episode = 0
timestamp_start = datetime.datetime.now()
gui_episodes = config['gui_episodes']
while episode < config['total_episodes']:
print('\n----- Episode', str(episode + 1), 'of',
str(config['total_episodes']))
epsilon = 1.0 - (
episode / config['total_episodes']
) # set the epsilon for this episode according to epsilon-greedy policy
simulation_time, training_time = Simulation.run(
episode, epsilon, episode in gui_episodes) # run the simulation
#EW traffic generator
TrafficGen_3 = TrafficGenerator(config['max_steps'],
config['n_cars_generated_ew'], 'EW')
#NS traffic generator
TrafficGen_4 = TrafficGenerator(config['max_steps'],
config['n_cars_generated_ns'], 'NS')
#Same visualization
Visualization = Visualization(path, dpi=96)
#Simulation with High traffic
Sim = Simulation(TrafficGen, sumo_cmd, config['gamma'],
config['max_steps'], config['green_duration'],
config['yellow_duration'], config['num_cells'],
config['num_states'], config['num_actions'],
config['training_epochs'])
#Simulation with Low traffic
Simulation_2 = Simulation(TrafficGen_2, sumo_cmd, config['gamma'],
config['max_steps'], config['green_duration'],
config['yellow_duration'], config['num_cells'],
config['num_states'], config['num_actions'],
config['training_epochs'])
#Simulation with EW traffic
Simulation_3 = Simulation(TrafficGen_3, sumo_cmd, config['gamma'],
config['max_steps'], config['green_duration'],
config['yellow_duration'], config['num_cells'],
config['num_states'], config['num_actions'],