Libo Cao

About

Dr. Libo Cao is a leading researcher in intelligent vehicle safety and autonomous driving systems, with a particular focus on pedestrian protection and advanced robotics for automotive testing. His most impactful work includes the development of specialized test equipment for Pedestrian-Automatic Emergency Braking (PAEB) systems, aligned with the China-New Car Assessment Program (C-NCAP) 2018 standards. This contribution, detailed in his highly cited 2020 paper (9 citations), provides a critical framework for evaluating and improving pedestrian safety in modern vehicles. Dr. Cao has also innovated in the field of computer vision, proposing a novel dandelion segmentation method that leverages background transfer learning and an RGB-attention module (2022, 9 citations), enhancing object detection in complex environments. His research extends to motion control for ultra-flat carrying robots used in functional safety road tests, where he developed an improved Particle Swarm Optimization (PSO) algorithm to achieve superior control performance (2023, 3 citations). Through these diverse yet interconnected contributions, Dr. Cao has established himself as a key figure in advancing both the evaluation and operational safety of intelligent driving technologies.

Research Focus

Key Achievements

Top Papers

1. 1
   Development of Test Equipment for Pedestrian-Automatic Emergency Braking Based on C-NCAP (2018)

   9 citations · 2020
2. 2
   Dandelion segmentation with background transfer learning and RGB-attention module

   9 citations · 2022
3. 3
   Research on system of ultra-flat carrying robot based on improved PSO algorithm

   3 citations · 2023

Key Collaborators

Contact & Links