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In order for autonomous vehicles to adapt to local norms in human driving, it is critical to profile how human driving differs across geographical locations. While ethnographers have qualitatively described regional differences in driving style, data-driven statistical models might help computer-driven cars drive like locals and recognize how local drivers might be signaling through hand/body movement and motion of their vehicles. To this end, we have created an experimental system and method to profile driving behavior and interaction using a multi-participant virtual reality (VR) driving simulation environment. The system was designed to be portable and to support cross-cultural experimental deployments. We aim to make sure the system is operational and functional, can model diverse scenarios, generates data fit for analysis, and captures expected behaviors. We describe the system, test scenarios, and findings of …