Developing Robot Driver Etiquette Based on Naturalistic Human Driving Behavior

TL;DR

This paper investigates the driving etiquette of human-driven vehicles using naturalistic driving data to inform the development of automated vehicle algorithms that better integrate with human driving behaviors.

Contribution

It provides the first comprehensive analysis of human driving etiquette parameters from real-world data to improve automated vehicle behavior modeling.

Findings

Identified key behavior parameters of human drivers from a large naturalistic database.

Results can guide the design of automated vehicle algorithms for better human-like interaction.

Data supports realistic simulation of human-driven vehicle behaviors.

Abstract

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.