Based on the development of the intelligent driving vehicles and the related key technologies, systematic interdisciplinary research has been carried out from the communications security, laser radar, machine vision, active safety, energy saving such aspects.
1.Perception
Research on the information fusion technology of the vehicle radar and machine vision and new technology of space 3D information construction in visual detection and measurement technology
2.Autonomous driving decision
Based on the framework of deep reinforcement learning, to construct the automatic driving strategy learning model and to improve the training efficiency using parallel computing.
3.Car network communication security
Research on the encryption and decryption, identity authentication and key distribution of vehicle network access, safe driving, billing management, traffic management and data communication.
4.Energy-saving driving
Through the path planning and speed adjustment to achieve energy-saving, combined with large traffic data, so as to achieve energy conservation from the city level.
Simultaneous localization and mapping (SLAM) is the problem of continuously constructing the map of the environment being explored while simultaneously computes the vehicle’s location. Although 3D LIDAR achieves popularity in SLAM technique due to its high robustness, its high cost impairs the widely usage. One alternative approach is to perform SLAM from digital cameras by extracting the vision-based depth information.Due to the nature of electronic devices, it is common to have a certain degree of error with respect to physical phenomenon measured by the individual sensors. In our project, SLAM technique is realized based on both stereo camera and the fusion of other low-cost sensors.
Additionally, the autonomous vehicle gains improved knowledge about the global and local scenes with the collaborative usage of RTK-GPS, which achieves the localization error of less than 10 centimeters. After acquiring sufficient localization information, our further research focuses on the algorithm development of secure, efficient path planning and real-time obstacle avoidance. Our concept of autonomous driving is demonstrated through in-house developed electric vehicle with integrated LIDAR, RTK-GPS and vision sensors.
Selected Papers
Hui Huang , Huiyun Li*, Wenqi Fang and Shaobo Dang, cuiping Shao, Tianfu Sun, Data Redundancy Mitigation in V2X based Collective Perceptions, IEEE Access, Volume: 8, Page(s): 13405 – 13418, 10 January 2020, (IF= 4.098, SCI, JCR Q1)
Lutao Chu; Huiyun Li; Zhiheng Yang,Accurate Scale Estimation for Visual Tracking with Significant Deformation,IET Computer Vision,14(5),2020,（IF= 1.516, SCI, JCR Q3）
Selected Patents
发明及PCT专利：一种基于聚类和极限学习机的自动驾驶决策方法，2017/5/12，PCT/CN2017/084081
发明专利：车辆自动驾驶控制策略模型生成方法、装置、设备及介质，2018/2/27，CN201810163708.7
