| # env |
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| CityFlow environment implementation for intersection-level RL with district-type metadata. |
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| ## Main files |
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| - [traffic_env.py](/Users/aditya/Developer/traffic-llm/env/traffic_env.py) |
| Main environment. One episode corresponds to one `(city, scenario)` pair. |
| - [cityflow_adapter.py](/Users/aditya/Developer/traffic-llm/env/cityflow_adapter.py) |
| Thin wrapper around the CityFlow Python engine. |
| - [observation_builder.py](/Users/aditya/Developer/traffic-llm/env/observation_builder.py) |
| Converts variable city topology into fixed-size per-intersection tensors. |
| - [reward.py](/Users/aditya/Developer/traffic-llm/env/reward.py) |
| Configurable local reward calculation. |
| - [utils.py](/Users/aditya/Developer/traffic-llm/env/utils.py) |
| Topology parsing and helper functions. |
| - [intersection_config.py](/Users/aditya/Developer/traffic-llm/env/intersection_config.py) |
| Internal topology dataclasses. |
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| ## How it works |
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| - Reads `roadnet.json`, `district_map.json`, and district types from `metadata.json`. |
| - Identifies non-virtual controllable intersections with at least two green phases. |
| - Uses one action per controllable intersection. |
| - Enforces `min_green_time` inside the environment. |
| - Advances CityFlow for `decision_interval` simulator steps between policy decisions. |
| - Returns a batched observation for all controlled intersections. |
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| ## Observation model |
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| Per intersection: |
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| - padded incoming lane vehicle counts |
| - padded incoming lane waiting counts |
| - incoming lane mask |
| - current green phase index |
| - elapsed time in current phase |
| - optional outgoing congestion summary |
| - district-type one-hot features |
| - optional small district context |
| - boundary-intersection indicator |
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| The observation dimension is exposed as `TrafficEnv.observation_dim`. |
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