Communicating Intent of Automated Vehicles to Pedestrians

While traffic signals, signs and road markings provide explicit guidelines for those operating in and around the roadways, some decisions, such as determinations of “who will go first”, are made by implicit negotiations between road users. In such situations, pedestrians are today often dependent on cues in drivers’ behavior such as eye contact, postures, and gestures. With the introduction of more automated functions and the transfer of control from the driver to the vehicle, pedestrians cannot rely on such nonverbal cues anymore. To study how the interaction between pedestrians and automated vehicles might look like in the future, and how this might be affected if automated vehicles were to communicate their intent to pedestrians, we designed an external vehicle interface called Automated Vehicle Interaction Principle (AVIP) that communicates vehicles’ mode and intent to pedestrians. The interaction was explored in two experiments using a Wizard of Oz approach to simulate automated driving. The first experiment was carried out at a zebra crossing and involved 9 pedestrians. While it focused mainly on assessing the usability of the interface, it also revealed initial indications related to pedestrians’ emotions and perceived safety when encountering an automated vehicle with/without the interface. The second experiment was carried out in a parking lot and involved 24 pedestrians, which enabled a more detailed assessment of pedestrians’ perceived safety when encountering an automated vehicle, both with and without the interface. For comparison purposes, these pedestrians also encountered a conventional vehicle. After a short training course, the interface was deemed easy for the pedestrians to interpret. The pedestrians stated that they felt significantly less safe when they encountered the automated vehicle without the interface, as compared to the conventional vehicle and the automated vehicle with the interface. This suggests that the interface could contribute to a positive experience and improved perceived safety in pedestrian encounters with automated vehicles – something that might be important for general acceptance of automated vehicles. As such, this topic should be further investigated in future studies involving a larger sample and more dynamic conditions.