Work

Understanding cyclists’ perception of driverless vehicles through eye-tracking and interviews

Year: 2024

Type: article

Abstract: As automated vehicles (AVs) gain traction, questions arise about the interaction between AVs and cyclists. Amidst conflicting views on the necessity of substituting drivers’ social cues with external human-machine interfaces (eHMIs) on AVs, our research investigated whether cyclists could detect the absence of a driver in an AV and how this influences their perceptions. Using a Wizard-of-Oz method with a concealed driver, 37 participants cycled a designated route and encountered the AV multiple times in two experimental sessions. In Session 1, participants cycled the route uninstructed, while in Session 2, they were explicitly instructed to detect the presence or absence of a driver. We recorded the participants’ gaze behaviour with eye-tracking and their responses in interviews. The results showed that thirty percent of the cyclists spontaneously noticed the absence of a driver, and when prompted, they detected a driver with 93% accuracy. The eye-tracking data revealed that cyclists looked more frequently and longer at the vehicle in Session 2 compared to Session 1. Furthermore, cyclists exhibited intermittent sampling of the vehicle, and they looked in front of the vehicle when it was far away and towards the windshield region when it was closer. The post-session interviews indicated that participants were curious but felt safe and acknowledged the need to receive information about the AV’s driving state. In conclusion, cyclists can detect the absence of a driver in the AV, and this detection may influence their perceptions of safety. Further research is needed to explore these findings in real-world traffic conditions.

Source: Transportation Research Part F Traffic Psychology and Behaviour

DOI: 10.1016/j.trf.2024.11.015