Vulnerable Road User

Vulnerable road users (VRUs), such as pedestrians and cyclists, experience disproportionately high crash rates and severe injuries, prompting research focused on improving their safety. Current research employs various methods, including advanced sensor technologies (like lidar) and machine learning models (e.g., LSTM networks) to predict VRU behavior, detect potential conflicts, and even develop proactive safety alert systems using digital twin technology. This work aims to enhance safety through improved detection algorithms, more accurate risk assessment, and the development of targeted interventions like infrastructure improvements and driver/VRU education programs. Ultimately, these efforts seek to reduce VRU accidents and fatalities through data-driven insights and technological advancements.