{"data":{"kind":"file","path":"README.md","version_id":"ueo0xj8da2r5vxchh5jw8dol","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":2084,"modified_at":"2026-08-27T14:28:53.686000","content_hash":"626c9b7812c23a46ccd9daff895159c44812208758730e462580a83605630903"},"entries":[],"content":"# Smart City Traffic Light Controller\n\nA real-world environment that tests an LLM's ability to design, optimize, and debug intelligent traffic light control systems for smart cities.\n\n## Overview\n\nModern smart cities use adaptive traffic signal control to reduce congestion, prioritize emergency vehicles, minimize emissions, and ensure pedestrian safety. This environment presents realistic traffic engineering challenges that require deep understanding of:\n\n- **Signal phase design**: Green/yellow/red timing for multi-lane intersections\n- **Adaptive control algorithms**: Webster's formula, actuated control, SCOOT/SCATS-style optimization\n- **Emergency vehicle preemption (EVP)**: Priority signal interruption for ambulances, fire trucks\n- **Pedestrian safety**: Walk/don't-walk intervals, accessible signal design\n- **Network coordination**: Green wave, offset optimization, arterial progression\n- **Fault diagnosis**: Debugging malfunctioning signal controllers from logs and sensor data\n\n## Task Types\n\n1. **Signal Timing Design** — Calculate optimal cycle length, phase splits, and clearance intervals for given traffic volumes\n2. **Algorithm Implementation** — Write Python/C code for adaptive signal control logic\n3. **Emergency Preemption** — Design EVP interrupt handlers with safe fallback states\n4. **Traffic Flow Analysis** — Analyze detector data and propose timing adjustments\n5. **Code Debugging** — Find and fix bugs in traffic controller firmware/simulation code\n6. **Network Optimization** — Coordinate multiple intersections for arterial progression\n\n## Evaluation\n\nEach task is scored on:\n- **Correctness** (40%): Does the solution produce valid, safe signal operations?\n- **Safety compliance** (25%): Does it meet MUTCD/traffic engineering standards?\n- **Efficiency** (20%): Does it minimize delay and maximize throughput?\n- **Robustness** (15%): Does it handle edge cases (sensor failure, emergency override)?\n\n## Usage\n\n```python\nimport verifiers as vf\nenv = vf.load_environment(\"everes/smart-city-traffic-light-controller\")\n```\n\n## License\n\nMIT\n","encoding":"utf-8","truncated":false,"total_bytes":2084},"status":null}