Can you hear the collision risk? A VR study on beamforming warnings for cyclists at urban intersections

Abstract

Right turns at urban intersections pose a significant risk to cyclists, but existing infrastructure-based warning systems often suffer from high false alarm rates and a lack of specificity. Following a PICO-based research design, this study addresses the research question of whether targeted acoustic warnings using beamforming technology can effectively warn cyclists (target) while simultaneously minimizing the disturbance for pedestrians and residents (non-targets). Using a fully immersive VR environment with spatial audio simulations and realistic traffic noise sounds, the study examined how cyclists, pedestrians, and residents perceive and accept these targeted signals. The experiment compared different warning sounds at varying distances from the intersection to determine their perceptibility and effectiveness. The results show that while all acoustic warnings were reliably perceived as relevant, verbal warnings proved to be the most effective, as speech is immediately understood regardless of the cyclist's distance from the intersection. In terms of environmental impact, the study found that beamforming can significantly minimize disturbance to pedestrians and residents, with narrow-beam signals perceived as the least disturbing. This work contributes to this field of research by demonstrating that spatially controlled acoustic systems offer a more specific and socially acceptable solution for protecting vulnerable cyclists than conventional omnidirectional or purely visual methods. By combining technical precision with intuitive communication, this approach effectively counteracts the “cry wolf” effect and improves overall road safety.