Research in the driving field shows that drivers could benefit from bimodal auditory-visual messages (Ghirardelli & Scharine, 2009), for example when they are approaching a variable message sign (VMS) and an auditory message gives orally such information. In fact, the identification of the information in the VMS can be virtually impossible in some circumstances, for instance, if there are technical problems in the screens or in adverse environmental conditions.  Curiously, there is also evidence that drivers remember better the message if it is received through the auditory system than if it is received through the visual one, for example, those messages that indicate the path to follow (Dalton et al., 2013). However, results from Wickens & Gosney (2003) don’t support a possible general advantage of auditory messages above the visual ones, neither of the auditory-visual messages above the unimodals.

Related to this, the field of the autonomous vehicle entails a paradigm change in the short-medium term, considering that in this modality of driving, the driver is relegated to the role of “supervisor” of the behaviour of the autonomous driving system (Rezvani et al., 2018), and thus, the driving becomes monotonous. In this context, it is essential that the driver identify critical messages such as those provided by a VMS emphasizing unexpected changes in the driving conditions or other imminent dangers, given that these circumstances are unknown to the autonomous vehicle and, when facing them, the driver must consider recover the control.

For these reasons, we decide to address the following objectives:

1. To study whether bimodal messages can improve the perception and understanding of traffic messages with respect to only visual messages or if, on the contrary, they result in greater cognitive saturation for drivers.
2. To analyse the relevant factors that origin one or the other effect.
3. To study the influence of bimodal and unimodal messages in distraction or low vigilance tasks to improve the autonomous driving.

Contact: atenlec@uv.es

Generalitat Valenciana (ACIF/2019/160)