Assessing Ultra-Wideband Technology for Improved Detection of Vulnerable Road Users in Urban Settings

Autonomous Vehicles face significant safety challenges in complex urban environments, particularly in detecting and tracking vulnerable road users (VRUs) like pedestrians and cyclists, who are at higher risk of fatal accidents. Traditional sensor fusion techniques that combine LiDAR with Vision struggle with occlusions and adverse weather or lighting conditions. This paper explores the potential of Ultra-Wideband (UWB) technology as an additional sensing modality, known for its high ranging accuracy and robustness in challenging environments. Through real-world experiments, we compare UWB's performance to that of common vision sensors, demonstrating its effectiveness in improving VRUs' detection and tracking in urban driving scenarios. Finally, we demonstrate the potential applications of the UWB technology in VRU localization scenarios.