README.md

metadata

title: Traffic Control Env
emoji: 🚦
colorFrom: green
colorTo: blue
sdk: docker
app_port: 7860
tags:
  - openenv
  - reinforcement-learning
  - traffic-control
  - fastapi

Indian Traffic Signal OpenEnv

A deterministic, seedable RL environment for Indian urban traffic signal control. The simulator models mixed traffic, pedestrian pressure, rain, emergency vehicles, unsafe switching, and hidden driver behavior.

Observation Space

GET /state and every step() result return:

• lane-wise queues for cars, bikes, autos, buses, and trucks
• lane waiting times
• current signal phase and time since last phase switch
• pedestrian count and pedestrian waiting time
• emergency vehicle presence, lane, type, and wait time
• rain level
• seeded random inflow from the most recent tick

Hidden dynamics include driver aggression, random blockage probability, and peak-hour multiplier. These affect traffic flow but are exposed only in info for debugging and grading transparency.

Action Space

Discrete actions:

• NS_GREEN
• EW_GREEN
• LEFT_PRIORITY
• PEDESTRIAN_CROSS
• EXTEND_GREEN
• EMERGENCY_OVERRIDE
• ALL_RED

The environment penalizes unsafe rapid switching, emergency override without an emergency, and pedestrian phases without demand.

Tasks

• single_intersection: easy, balanced four-way control.
• rush_hour: medium, heavier asymmetric commuter traffic and rain.
• emergency_priority: hard, frequent emergency vehicles and stricter emergency handling.

Setup

pip install -r requirements.txt
uvicorn api:app --host 0.0.0.0 --port 8000

Run tests:

pytest -q

Run the submission validator once the Hugging Face Space is deployed:

bash scripts/validate-submission.sh https://your-space.hf.space .

Run the baseline inference script after starting the API:

python inference.py --task-id single_intersection --seed 42 --steps 30

API

• POST /reset
• POST /step
• GET /state
• GET /tasks
• POST /grader
• GET /baseline

Baseline Scores

Scores are reproducible for a fixed seed through GET /baseline?seed=42. The baseline is intentionally simple: fixed cycles, queue switching, and immediate emergency override.