Improving target selection accuracy for vehicle touch screens

Abstract

When operating the touch screen in a car, the touch point can shift due to the vibration, resulting in selection errors. Using larger target is a possible solution, but this significantly limits the amount of content that can be displayed on the touch screen. Therefore, we propose a method for in-vehicle touch screen target selection that can be used with a variety of sensors to increase selection accuracy. In this method, the vibration feature is learned by Variational AutoEncoder based model, and it is used for estimating touch point distribution. Our experimental results demonstrate that the proposed method allows users to achieve higher target selection accuracy than conventional methods.