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README.md
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### Performance Metrics Comparison by Model *
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| Model | Avg Saturation | Avg Queue Length (veh/
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|:---:|:---:|:---:|:---:|:---:|
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| [`GPT-OSS-20B (thinking)`](https://huggingface.co/openai/gpt-oss-20b) | 0.380 |
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| **DeepSignal-4B (Ours)** | 0.422 |
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| [`Qwen3-30B-A3B`](https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct) | 0.431 |
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| [`Qwen3-4B`](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) | 0.466 |
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| Max Pressure | 0.465 |
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| [`LightGPT-8B-Llama3`](https://huggingface.co/lightgpt/LightGPT-8B-Llama3) | 0.523 |
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`*`: Each simulation scenario runs for 60 minutes. We discard the first **5 minutes** as warm-up, then compute metrics over the next **20 minutes** (minute 5 to 25). We cap the evaluation window because, when an LLM controls signal timing for only a single intersection, spillback from neighboring intersections may occur after ~20+ minutes and destabilize the scenario. All evaluations are conducted on a **Mac Studio M3 Ultra**.
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`**`: Max Pressure is a fixed signal-timing optimization algorithm (not an LLM), so we omit its Avg Response Time; this metric is only defined for LLM-based signal-timing optimization.
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### Performance Metrics Comparison by Model *
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| Model | Avg Saturation | Avg Queue Length (veh/min) | Avg Throughput (veh/5min) | Avg Response Time (s) |
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|:---:|:---:|:---:|:---:|:---:|
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| [`GPT-OSS-20B (thinking)`](https://huggingface.co/openai/gpt-oss-20b) | 0.380 | 14.088 | 77.910 | 6.768 |
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| **DeepSignal-4B (Ours)** | 0.422 | 15.703 | **79.883** | 2.131 |
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| [`Qwen3-30B-A3B`](https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct) | 0.431 | 17.046 | 79.059 | 2.727 |
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| [`Qwen3-4B`](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) | 0.466 | 57.699 | 75.712 | 1.994 |
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| Max Pressure | 0.465 | 23.022 | 77.236 | ** |
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| [`LightGPT-8B-Llama3`](https://huggingface.co/lightgpt/LightGPT-8B-Llama3) | 0.523 | 54.384 | 75.512 | 3.025*** |
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`*`: Each simulation scenario runs for 60 minutes. We discard the first **5 minutes** as warm-up, then compute metrics over the next **20 minutes** (minute 5 to 25). We cap the evaluation window because, when an LLM controls signal timing for only a single intersection, spillback from neighboring intersections may occur after ~20+ minutes and destabilize the scenario. All evaluations are conducted on a **Mac Studio M3 Ultra**.
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`**`: Max Pressure is a fixed signal-timing optimization algorithm (not an LLM), so we omit its Avg Response Time; this metric is only defined for LLM-based signal-timing optimization.
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