Traffic is a self-organising, regulated system, but there are several ambiguous situations where no rules apply. In such situations, communication is important in order to achieve a smooth traffic flow and a safe situation. However, in the majority of traffic conflicts, adequate coordination between road users is lacking. Communication is particularly important for vulnerable users such as pedestrians, given their significant share in traffic accident statistics worldwide.
The increasing amount of automation in vehicles creates a potential social interaction void, which could further impede safety and a smooth traffic flow, as the chances of misinterpreting the behaviour of another road users might increase. Some researchers and companies have suggested that these problems could be addressed by adding additional means of communication to a vehicle. However, there is limited consensus as to what the most effective form and content of such communication would be.
The aim of this study is to investigate the effect of two different types of information on a pedestrian's crossing behaviour. This work describes the development and evaluation of a textual, external human-machine interface (eHMI), with the aim of complementing existing signals, such as vehicle movements, with explicit information addressed to human road users. Three conditions, specifically: (0) no information, (1), a pedestrian advice (Wait/Walk) and (2) a vehicle based status (Drive/Brake) are compared with respect to their effect on four variables related to the pedestrian: the minimum distance maintained to the vehicle, measured as a virtual 'Time to Collision', changes in the decision to cross (Decision Certainty), the feeling of safety as a percentage of the duration of a scenario (Decision Efficiency), and subjective acceptance.
28 participants participated in three repetitions of the same experiment in three different environments: a field test on a public road, an experiment in an animated virtual reality environment and an experiment using 360* video recordings. Participants stood on the pavement along an urban road in a European setting, and were asked to press a button when they felt safe to cross. During the experiment, a car drove by while showing one of the three types of information.
The total time that participants felt safe was significantly higher in scenarios where the car stopped, and significantly lower if the car did not stop, when information was offered. Time to Collision, decision changes and subjective acceptance also showed statistically significant differences in most scenarios, as these variables show a strong correlation among each other. However, one difference was found between the types of information for the Decision Efficiency variable. Here, effect sizes for the Wait/Walk eHMI (egocentric information) were larger than for Drive/Brake (allocentric information).
The results show that providing additional information could improve safety and traffic flow, although the type of information has a limited influence on the behaviour of a pedestrian. This suggests that when choosing a certain type of information, other factors should be taken into account that could perhaps be more decisive. Ultimately, this research contributes to finding the optimal characteristics of a standardised eHMI design.