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Studies show that drivers’ intention to use automated vehicles is strongly modulated by trust. It follows that their benefits are unlikely to be achieved if users do not trust them. To date, most studies of trust in automated vehicles have relied on self-reports. However, questionnaires cannot capture real-time changes in drivers’ trust, and are hard to use in applied settings. In previous work, we found evidence that gaze behaviour could provide an effective measure of trust. In this study we tested whether combining gaze behaviour with Electrodermal Activity could provide a stronger metric. The results indicated a strong relationship between self-reported trust, monitoring behaviour and Electrodermal Activity: The higher participants’ self-reported trust, the less they monitored the road, the more attention they paid to a non-driving related secondary task, and the lower their Electrodermal Activity. We also found evidence that combined measures of gaze behaviour and Electrodermal Activity predict self-reported trust better than either of these measures on its own. These findings suggest that such combined measures have the potential to provide a reliable and objective real-time indicator of driver trust. © 2019 Elsevier Ltd

In road-crossing situations involving negotiation with approaching vehicles, pedestrians need to take into account the behavior of the car before making a decision. To investigate the kind of information about the car that pedestrians seek, and the places where do they look for it, we conducted an eye-tracking study with 26 participants and analyzed the fixation behavior when interacting with a manually-driven vehicle that approached while slowing and displaying a yielding behavior. Results show that a clear pattern of gaze behavior exists for pedestrians in looking at a vehicle during road-crossing situations as a function of the vehicle’s distance. When the car is far away, pedestrians look at the environment or the road space ahead of the car. With the approach, the gaze gradually shifts to the windshield of the car. We conclude by discussing the implications of this insight in the user-centered-design of optimal external Human-Machine-Interfaces for automated vehicles.

Can interactions between automated vehicles and pedestrians be evaluated in a quantifiable and standardized way? In order to answer this, we designed an input device in the form of a continuous slider that enables pedestrians to indicate their willingness to cross a road and their feeling of safety in real time in response to an approaching vehicle. In an initial field study, 71% of the participants reported that they were able to use the device naturally and indicate their feeling of safety satisfactorily. The feeling-of-safety slider can consequently be used to evaluate and benchmark interactions between pedestrians and vehicles, and compare communication interfaces for automated vehicles.

Overtrust and undertrust are major issues with partially automated vehicles. Ideally, trust should be calibrated ensuring that drivers’ subjective feelings of safety match the objective reliability of the vehicle. In the present study, we examined if drivers’ trust toward Level 2 cars changed after on-road experience. Drivers’ self-reported trust was assessed three times: before having experience with these vehicles, immediately after driving two types of vehicles, and two weeks after the driving experience. Analysis of the results showed major changes in trust scores after the on-road driving experience. Before experiencing the vehicles, participants tended to overestimate the vehicle capabilities. Afterwards they had a better understanding of vehicles’ limitations, resulting in better calibrated trust.

A crucial factor influencing the validity of VR is sense of presence. The aim of this study is, firstly, to increase sense of presence of simulator driving by introducing an anxiety-inducing risk factor. Secondly, to add clarification to the partly inconclusive relationship between sense of presence, anxiety and physiological markers. The study consisted of two groups. The control group drove in the simulator normally. The threat group expected an electric shock in case of collision. Self-report ratings (on sense of presence, anxiety and task load), behavioral (speed, steering reversal rate, brake pedal use) and physiological measurements (EDA, HR) were taken. We expected an increase in the sense of presence, arousal, steering reversals, brake pedal use, task load and anxiety ratings, and a decrease of speed in the threat group. Analyses revealed partial group differences in speed and steering reversal rate. Sense of presence was identical and notably high in both groups. This implies that either a more aversive stimulus might be needed to induce anxiety and increase sense of presence, or that it can hardly be increased at all in highly immersive VR systems.