Education Background Ph.D.(2018.9-2022.9), Vehicle Engineering, Jiangsu University M.E.(2015.9-2018.6), Transportation Engineering, Jiangsu University B.E.(2010.9-2014.6), Traffic Engineering, Chongqing Jiaotong University Working Experience 2022.12-now, Lecturer of Automotive Engineering Research Institute, Jiangsu University |
1. Technologies and methods of vehicle driving environment perception in complex scenes 2. V2X vehicle-road collaborative perception and control 3. Autonomous driving algorithm deployment, debugging and application scenario verification |
1. National key research and development plan, bicycle intelligent perception technology based on multi-source heterogeneous information fusion (participation). 2. Key project of National Natural Science Foundation of China, Research on autonomous perception and Behavioral cognition mechanism of intelligent vehicle based on complex network theory (participation). 3. Key research and development project of Jiangsu Province, key technology of networked sensing system for new energy vehicles oriented to drive-by-wire chassis dynamics (participation). 4. National key research and development plan sub-project, complete driving environment state information reconstruction software system (project leader, research). 5. Jiangsu Provincial Department of Education University natural science research project surface project (project leader, research). |
（1）Liu Z , Cai Y , Wang H , et al. Robust Target Recognition and Tracking of Self-Driving Cars With Radar and Camera Information Fusion Under Severe Weather Conditions[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, PP(99):1-14. IF=9.551 （2）Liu Z , Cai Y , Wang H , et al. Surrounding Objects Detection and Tracking for Autonomous Driving Using LiDAR and Radar Fusion[J]. Chinese Journal of Mechanical Engineering，2020. IF=2.964 （3）Liu Z , Cai Y , Wang H , et al. Vehicle license plate recognition method based on deep convolution network in complex road scene[J]. Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering, 2019, 233(9):2284-2292.，IF=1.828 （4）Cai Y , Liu Z ,Wang H , et al. Vehicle Detection by Fusing Part Model Learning and Semantic Scene Information for Complex Urban Surveillance[J]. Sensors, 2018, 18(10). IF=3.847 |
