Nocturne - A Real-Time Driving Assistant at Night for Sri Lanka

Nighttime driving presents significant challenges, including detecting pedestrians, cyclists, and potholes in low-visibility conditions, leading to frequent road accidents. In Sri Lanka, there is a lack of automated systems capable of addressing these challenges. This research proposes a system leveraging AI and real-time video processing to enhance driver safety by improving pedestrian and cyclist visibility and developing a reliable pothole detection system for night time. These enhancements rely on extensive data collection and preprocessing for training specialized computer vision and machine learning models tailored for real-time, low-light scenarios. The application provides real-time alerts and visual cues to reduce nighttime driving accidents. Additionally, a software framework is proposed to offer real-time feedback for drivers leveraging available hardware capabilities, enhancing awareness of vulnerable road users. Through rigorous data collection, testing, and development, this approach significantly helps to enhance nighttime driving safety in Sri Lanka.