Human-aware and so-called social navigation abilities of a robot need to be tested and evaluated in real-life experiments with real humans. Such tests are mandatory to validate a mature system. But they are heavy to set up and can become tiresome when debugging the early stages of a system. Simulation could help solve this issue, but the lack of available intelligent human avatars that can exhibit a rational behavior restricts this to simple scenarios. To address this issue, we propose a system providing first an autonomous intelligent human agent specifically designed to act and interact with a robot navigating in a simulated environment. Then, the system provides a GUI to visualize the paths taken by the agents as well as the produced metrics in order to help evaluate the interaction. Moreover, the system also provides a high-level interface to control the agents and run repeatable scenarios. We show through a set of experiments how the proposed system can help answer the lack of intelligent avatars for tuning and debugging social navigation systems before their final evaluation with real humans.