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