As we move towards a future with Automated Vehicles (AVs) incorporated in the current traffic system, it is crucial to understand driver-pedestrian interaction, in order to enhance AV design and optimization. Previous research in this area, which has primarily used naturalistic observations or single-actor virtual reality simulations, has been limited by its inability to draw causal conclusions, also due to a lack of real human–human interactions. Our study addresses these limitations by employing a high-fidelity distributed simulation setup that links drivers in a motion-based simulator with pedestrians in a CAVE-based environment. This method allows for the examination of real-time and reciprocal interactions across a range of road-crossing scenarios. Using thirty-two pairs of drivers and pedestrians, we investigated how different factors, such as the presence of zebra crossings and varying time gaps of the approaching vehicle, influence driver behaviour and pedestrian crossing decisions. The effect of drivers’ control of the vehicle during such crossings (e.g., braking behaviour and lateral deviation) on pedestrians’ crossing decisions were also analysed. We found that the distribution of drivers’ average deceleration values were bimodal, where drivers either markedly yielded to pedestrians, or continued in their path, with very few instances of intermediate behaviour. We also found that pedestrian decisions were seemingly influenced by the different braking strategies adopted by the driver, with pedestrians crossing before the vehicles in response to soft and early, or late and hard braking, while late and soft braking often resulted in the vehicle passing first. We also observed a slight lateral movement of the vehicle away from pedestrians when drivers were not yielding, but more of a lateral deviation towards them when yielding. This may be because drivers subconsciously transfer their walking interaction habits to their driving behaviour, to avoid a collision with pedestrians. Finally, our results showed a stronger influence of these kinematic cues on pedestrian crossing decisions, when compared to zebra crossings. As well as highlighting the value of a novel approach for investigating vehicle–pedestrian interactions, this study illustrates how vehicle cues can assist pedestrian decisions, adding new knowledge in the development of human-like behaviour for future AVs.

Introduction: Augmented reality (AR) has been increasingly studied in transportation, particularly for drivers and pedestrians interacting with automated vehicles (AVs). Previous research evaluated AR interfaces using online video-based questionnaires but lacked human-subject research in immersive environments. This study examined if prior online evaluations of nine AR interfaces could be replicated in an immersive virtual environment and if AR interface effectiveness depends on pedestrian attention allocation. 

Methods: Thirty participants completed 120 trials in a CAVE-based simulator with yielding and non-yielding AVs, rating the interface’s intuitiveness and crossing the road when they felt safe. To emulate visual distraction, participants had to look into an attention-attractor circle that disappeared 1 s after the interface appeared. 

Results: The results showed that intuitiveness ratings from the current CAVE-based study and the previous online study correlated strongly (r ≈ 0.90). Head-locked interfaces and familiar designs (augmented traffic lights, zebra crossing) yielded higher intuitiveness ratings and quicker crossing initiations than vehicle-locked interfaces. Vehicle-locked interfaces were less effective when the attention-attractor was on the environment’s opposite side, while head-locked interfaces were relatively unaffected by attention-attractor position. 

Discussion: In conclusion, this ‘AR in VR’ study shows strong congruence between intuitiveness ratings in a CAVE-based study and online research, and demonstrates the importance of interface placement in relation to user gaze direction.

Augmented Reality (AR) technology could be utilised to assist pedestrians in navigating safely through traffic. However, whether potential users would understand and use such AR solutions is currently unknown. Nine novel AR interfaces for pedestrian-vehicle communication, previously developed using an experience-based design method, were evaluated through an online questionnaire study completed by 992 respondents in Germany, the Netherlands, Norway, Sweden, and the United Kingdom. The AR indicated whether it was safe to cross the road in front of an approaching automated vehicle. Each interface was rated for its intuitiveness and convincingness, aesthetics, and usefulness. Moreover, comments were collected for qualitative analysis. The results indicated that interfaces that employed traditional design elements from existing traffic, and head-up displays, received the highest ratings overall. Statistical results also showed that there were no significant effects of country, age, and gender on interface acceptance. Thematic analysis of the textual comments offered detail on each interface design's stronger and weaker points, and revealed unintended effects of certain designs. In particular, some of the interfaces were commented on as being dangerous or scary, or were criticised that they could be misinterpreted in that they signal that something is wrong with the vehicle, or that they could occlude the view of the vehicle. The current findings highlight the limitations of experience-based design, and the importance of applying legacy design principles and involving target users in design and evaluation. Future research should be conducted in scenarios in which pedestrians actually interact with approaching vehicles.

Marie Skłodowska-Curie Actions; Innovative Training Networks (ITN); SHAPE-IT; Grant number 860410

Publication date: 21 February 2023

DOI: 10.1016/j.trf.2023.02.005