Indicator of Safety and Comfort Performance: Quantifying Different Driving Styles for Automated Vehicles

Quantitative assessment of driving performances and analysis of different driving styles are significantly critical for the mass employment of automated vehicles (AVs). Therefore, this paper presents a synthetical indicator to quantify AVs' driving performance with regard to dynamic safety and comfort and then classifies quantitatively different driving styles based on the proposed indicator. All dynamic signals are analyzed based on vehicle global dynamics modeling, and we develop rigorous performance indicators mathematically. Furthermore, the distribution of our proposed indicator is investigated to reveal different driving styles including normal, aggressive, and conservative driving. Experimental results illustrate the proposed indicator can efficiently evaluate driving performance and can be used to classify different driving styles. These findings suggest our research has great potential to provide a foundation for the design of AVs' planning and control methods.