A flexible virtual environment for autonomous driving agent-human interaction testing

Abstract

Autonomous driving has, in recent years, gained considerable traction due to commercial interest by car manufacturers, that envision a widespread use of self-driving cars in the next decade. Research has mainly focused on specific topics, that can enable the feasibility of robust artificial autonomous agents for autonomous vehicles (AVs), ranging from artificial vision, to automatic environmental sensing and inference, agent-agent interaction and sensor augmentation and integration. A somewhat reduced effort has been directed towards the evaluation of human-AV interaction and in the direction of defining acceptable rules of engagement when AV deal with human drivers. This aspect of autonomous driving will became extremely relevant in the next years as level 5 AVs will make their appearance on our streets and most of the cars will still be driven by humans. To assess, experimentally, how AVs can successfully interact with human drivers we have constructed a lab setup, which can simulate a large range of situations in which human drivers encounter AVs and interact with them. Based on the Unity Gaming Engine an urban environment has been developed where AVs interact with human driven cars, pedestrians and various agents. This setup allows for human subjects to drive in a virtual reality (VR) environment, and assess their behavior during the interaction with other human drivers and AVs. The goal is to define a set of rules that can be applied in AV design, to make autonomous cars react to human drivers, taking into account the behavioral patterns and variable respect of traffic regulations that human drivers exhibit in real environments. We present an early experimental setup, potentially useful for understanding, in a quantitative and reproducible way, how this approach can contribute in designing AVs that are more suited for large scale deployment.