Zero-Shot MARL Benchmark in the Cyber-Physical Mobility Lab

• URL: http://arxiv.org/abs/2601.16578v1
• Date: Fri, 23 Jan 2026 09:26:36 GMT
• Title: Zero-Shot MARL Benchmark in the Cyber-Physical Mobility Lab
• Abstract summary: We present a benchmark for evaluating sim-to-real transfer of Multi-Agent Reinforcement Learning (MARL) policies for Connected and Automated Vehicles (CAVs)<n>The platform integrates simulation, a high-fidelity digital twin, and a physical testbed, enabling structured zero-shot evaluation of MARL motion-planning policies.
• Score: 0.13398445165628464
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a reproducible benchmark for evaluating sim-to-real transfer of Multi-Agent Reinforcement Learning (MARL) policies for Connected and Automated Vehicles (CAVs). The platform, based on the Cyber-Physical Mobility Lab (CPM Lab) [1], integrates simulation, a high-fidelity digital twin, and a physical testbed, enabling structured zero-shot evaluation of MARL motion-planning policies. We demonstrate its use by deploying a SigmaRL-trained policy [2] across all three domains, revealing two complementary sources of performance degradation: architectural differences between simulation and hardware control stacks, and the sim-to-real gap induced by increasing environmental realism. The open-source setup enables systematic analysis of sim-to-real challenges in MARL under realistic, reproducible conditions.

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