LiDAR system benchmarking for VRU detection in heavy goods vehicle blind spots

This article is related to using modern LiDARs and neural networks based algorithms for vulnerable road users (VRU) detection. The problem is obvious especially when considering blind spots of heavy goods vehicles. LiDARs have developed a lot recently and the results indicate that adults can be detected up-to 75 m distance from the sensor even thought that pattern recognition requires sufficient point cloud-resolution. Two different LiDAR brands have been compared to understand costbenefits between LiDAR technologies. The results have been conducted using an automated passenger car while considering feasibility to big trucks. Due to automotive requirements, the processing rate is also considered since usually, the main bottleneck is computation power, which is limited in automotive products. The used neural network algorithm is Yolo based and has been designed for VRU detection.