Optimizing roundabout safety: using UAVs and computer vision for driver behavior analysis

Abstract Roundabouts are safer than standard intersections, but traffic accidents remain a major public health issue. Driver behaviour plays a critical role in accident occurrence at roundabouts. To enhance safety, this study examines the relationship between driver behaviours and roundabout traffic accidents. The study utilised Unmanned Aerial Vehicles (UAVs) to collect field data and process it using a computer vision tool. Driver behaviours were studied regarding average speed, pattern, gap acceptance, and idle time. The maximum speed exceeds 40 km/h, with drivers often travelling above safe limits. They also tend to accelerate inside the roundabout and decelerate at the entry and exit. Also, high circulating speeds reduce gap size, limiting roundabout entry and reducing capacity. Light vehicles have shorter idle times of less than six seconds, while heavy vehicles, due to size and inertia, require longer reaction times and larger gaps, leading to long idle times. The research contributes significantly to roundabout safety, efficiency and urban planning. It aids in designing future roundabouts suited for local traffic capacity and behaviour patterns while promoting safe and efficient intersections. This study also highlights the potential of using advanced technologies, like UAVs and computer vision, for further traffic analysis. Ultimately, understanding driver behaviour is key to improving traffic safety and efficiency.