Effective Communication Between Automated Vehicles and Pedestrians: A Comparative Daytime and Nighttime Experimental Study in Germany and the UK

Effective visual communication is key to improving road safety whenever vulnerable road users (VRUs), e.g., pedestrians and cyclists, interact in daily traffic. The importance of such communication continues to grow as higher levels of automation are achieved and fully automated vehicles (AVs) become increasingly prevalent. This is especially true for AVs above Level 3, which means that the driver is ‘not driving’ when autonomous driving features are engaged—even if the ‘driver’s’ seat is occupied. Current research shows that external human–machine interfaces (eHMIs) may facilitate explicit communication when AVs and VRUs interact. We used a Virtual Reality approach to examine the efficiency of different formats of eHMIs for signaling that an AV was going to give way and stop to let a pedestrian cross a road. Participants’ decision times and judgements of the clarity of the signals were measured in studies conducted in the UK and in Germany. Overall, the findings showed that eHMIs were effective in signaling AV intention compared to a no-signal baseline; signal interpretation was more difficult at night than in the day. In addition, the format and type of information displayed influenced the ease of recognition and interpretation of such interfaces, with larger light segments aiding visibility and numerical information aiding interpretation. The results are discussed in terms of recommendations for eHMI design and future field testing.