提出首个交通信号控制的仿真到现实基准，系统评估迁移失败原因。
Sim2Signal: Sim-to-Real Benchmarks for Traffic Signal Control
- 将仿真到现实差距分解为感知、动作、状态转移和奖励四类，逐项测试
- 18种缓解方法在33种设置下表现差异大，无通用最优策略
- 有效方法多通过估计差距而非让模型对干扰不敏感
强化学习在仿真中表现出色，但部署到真实交通系统时常因仿真到现实差距而失效。该差距源于感知、动作执行、交通动态及控制目标四方面。现有缓解方法的有效性尚不明确，且缺乏统一评估基准。本文提出Sim2Signal基准，将差距分解为观察、动作、转移和奖励四类，采用统一协议分别引入每类差距。在33种差距设置下，评估18种缓解方法在10个基于5个真实路段校准的网络上的表现。结果表明：直接迁移在所有四类差距下均导致性能下降，但下降程度无法预测缓解效果；缓解效果高度依赖具体网络与差距类型。最有效的方法是估计差距变化，而非通过领域随机化或不变表示使策略对干扰不敏感。代码已开源。
原文摘要 · Abstract (English)
Reinforcement learning achieves strong traffic signal control performance in simulation, yet policies trained in simulators often fail once deployed in the real world, a failure known as the Sim-to-Real gap. When RL is applied to traffic signal control, this gap arises from several sources: sensing, action execution, traffic dynamics, and the control objective. Their relative impact and the reliability of existing Sim-to-Real mitigation methods remain insufficiently understood, and the field lacks a standard benchmark for systematically measuring the gap and evaluating mitigation methods. We present Sim2Signal, a benchmark that decomposes the Sim-to-Real gap into observation, action, transition, and reward gaps, corresponding to mismatches in the four components of the underlying MDP, and induces each gap in isolation under a shared protocol. We evaluate 18 mitigation methods on 2 base controllers, across 33 gap settings and 10 calibrated networks built from 5 real-world locations. We find that direct transfer consistently degrades performance across all four gap sources, but the severity of the degradation does not predict the effectiveness of mitigation. Instead, mitigation effectiveness depends strongly on the network and gap setting: outside the action gap, a method that helps in one case may fail in another. The most effective methods generally estimate what the gap changes, rather than make the policy insensitive through domain randomization or invariant representations. Our code is available at https://github.com/Red-Pheonix/Sim2RealTSCBenchMark
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