DTSO-Mtech_2025/config/config.yaml

53 lines
1.1 KiB
YAML

# Dynamic Traffic Signal Optimization Configuration
experiment:
name: "traffic_rl_mtech"
version: "1.0"
description: "M.Tech Dynamic Traffic Signal Optimization using Deep RL"
environment:
simulation_time: 3600 # 1 hour simulation
step_size: 1 # SUMO step size in seconds
yellow_time: 3
min_green_time: 10
max_green_time: 60
warmup_time: 300 # 5 minutes warmup
network:
type: "single_intersection"
lanes_per_direction: 2
max_speed: 50 # km/h
intersection_size: 50 # meters
agent:
algorithm: "D3QN" # Dueling Double DQN
state_size: 20
action_size: 8
learning_rate: 0.0001
gamma: 0.95
epsilon_start: 1.0
epsilon_end: 0.01
epsilon_decay: 0.995
memory_size: 100000
batch_size: 64
target_update_freq: 100
hidden_layers: [256, 128, 64]
training:
episodes: 2000
max_steps_per_episode: 1000
save_freq: 100
eval_freq: 50
log_freq: 10
evaluation:
test_episodes: 10
baseline_methods: ["fixed_time", "actuated", "random"]
metrics: ["delay", "queue_length", "throughput", "emissions", "fuel"]
paths:
models: "models/"
data: "data/"
logs: "logs/"
results: "results/"
sumo_configs: "sumo_configs/"