  Simulations are gaining increasingly significance in the field of autonomous
driving due to the demand for rapid prototyping and extensive testing.
Employing physics-based simulation brings several benefits at an affordable
cost, while mitigating potential risks to prototypes, drivers, and vulnerable
road users. However, there exit two primary limitations. Firstly, the reality
gap which refers to the disparity between reality and simulation and prevents
the simulated autonomous driving systems from having the same performance in
the real world. Secondly, the lack of empirical understanding regarding the
behavior of real agents, such as backup drivers or passengers, as well as other
road users such as vehicles, pedestrians, or cyclists. Agent simulation is
commonly implemented through deterministic or randomized probabilistic
pre-programmed models, or generated from real-world data; but it fails to
accurately represent the behaviors adopted by real agents while interacting
within a specific simulated scenario. This paper extends the description of our
proposed framework to enable real-time interaction between real agents and
simulated environments, by means immersive virtual reality and human motion
capture systems within the CARLA simulator for autonomous driving. We have
designed a set of usability examples that allow the analysis of the
interactions between real pedestrians and simulated autonomous vehicles and we
provide a first measure of the user's sensation of presence in the virtual
environment.
