Evaluation and optimization of a vibrotactile signal in an autonomous driving context

Abstract

AbstractAn important issue in autonomous vehicle development is the transition phase between autonomous and manual driving. Here, we focused on a vibrotactile signal that warns the driver 1 min before they must take over. Our goal was to design a signal detectable by, and satisfactory for, all drivers. After listing parameters defining a vibrotactile signal, we performed a design‐of‐experiments study to select 16 signals for evaluation by 80 participants of different ages, body mass indexes, and genders. In a car on the road, autonomous driving conditions were simulated with the participant in the front passenger seat, who performed a task unrelated to driving. Whenever the participant detected a signal, they gave a satisfaction score. Modeling enabled us to evaluate the effects of the signal parameters and participant characteristics on satisfaction and detection. Moreover, we obtained specifications for the design of a tactile signal according to our two criteria.Practical applicationsTo the best of our knowledge, this is the first study to focus on the sensory aspect of a tactile signal in a car environment. Both functional (i.e., signal detection) and hedonic aspects are important. We investigated the influence of gender, age, and body mass index of the participants on signal detection and satisfaction score, and optimized the satisfaction score under detection constraints. We use a 3‐point method to reach those two goals: Constructing the design‐of‐experiments (DoE) based on signal parameters that influence the two criteria and can be tuned. Sensory evaluation of the signals from the DoE. Modeling to evaluate the influence of each parameter and determine optimal values. Understanding the influence of the participant's characteristics, coupled with an optimization approach, will benefit the design of automated cars as well as other tactile interfaces, such as smartphones, connected wristbands, or touchscreens.