A methodology for generating driving styles for autonomous cars

This work is about the generation of driving styles for autonomous cars. Here, we propose a definition of driving style based on the partition of controller parameters for self-driving vehicles. The main contributions of this work are the following. 1) A methodology based on the controllers' parameters for creating comfortable driving styles that can be used as autonomous cars' operation modes. 2) A proposal to use virtual reality as a testbed for the evaluation of driving styles by users. 3) As an illustration of our methodology, we determine and evaluate distinguishable driving styles by partitioning the time-to-collision parameter of the Intelligent Driver Model (IDM) controller using the Just Noticeable Difference (JND). 4) A proposal of four driving styles that are equally preferable among passengers.