Measuring trust in automated driving using a multi-level approach to human factors

Abstract

As the driving is shifting towards automation, the maximization of related benefits would profit from improved user acceptance of the new technology. Studies suggest a strong connection between acceptance and trust in technical solutions. We investigate the improvement of user trust to driving automation through demonstrations carried out in a sophisticated driving simulator. The study correlates subjective data with objective psychophysiological measurements. The multi-factorial and multivariate analysis of variance investigates the influence of learning effects and pre-experience with advanced driver assistance systems on trust. Results show improvement in trust through user interaction with a human-machine interface of the demonstrated AD system, hence illustrating the relevance of human-centered development processes. The conclusion is supported by the observation of driver cardiac signals.