Developing Robot Driver Etiquette Based on Naturalistic Human Driving Behavior
This addresses the challenge of integrating automated vehicles into mixed traffic with human drivers, though it is incremental as it focuses on data analysis rather than new algorithms.
The paper tackles the problem of robotic vehicles lacking human-like driving etiquette by analyzing a large naturalistic driving database to extract key behavior parameters from human-driven vehicles, which can inform future algorithm design or simulation models.
Automated vehicles can change the society by improved safety, mobility and fuel efficiency. However, due to the higher cost and change in business model, over the coming decades, the highly automated vehicles likely will continue to interact with many human-driven vehicles. In the past, the control/design of the highly automated (robotic) vehicles mainly considers safety and efficiency but failed to address the "driving culture" of surrounding human-driven vehicles. Thus, the robotic vehicles may demonstrate behaviors very different from other vehicles. We study this "driving etiquette" problem in this paper. As the first step, we report the key behavior parameters of human driven vehicles derived from a large naturalistic driving database. The results can be used to guide future algorithm design of highly automated vehicles or to develop realistic human-driven vehicle behavior model in simulations.