Li Aijuan—R&D Team for Trajectory Planning and Control of
Intelligent Electric Vehicles
Li Aijuan holds a PhD in Engineering and has completed postdoctoral research. She is a professor, an “Outstanding Master’s Supervisor” in Shandong Province, and a visiting scholar at the University of Wollongong in Australia. She has been recognized as a Young Scientific and Technological Talent in Transportation by the Ministry of Transport, a urgently needed key-supported talent introduced to key regions in Shandong Province, and a Category-D high-level talent in Jinan’s classified talent program. She serves as a member of both the Academic Committee and the Professorial Committee of Shandong Jiaotong University, a council member of the National Industry–Education Integration Community for Intelligent Connected Vehicle Testing and Evaluation, and a second-tier talent in the “1251” Talent Program of Shandong Jiaotong University. She is also the leader of a Young Innovation Team in Higher Education Institutions of Shandong Province, a member of the China Society of Automotive Engineers, a member of the first Youth Committee of the Shandong Society of Automotive Engineers, vice president of the Jinan Society of Automotive Engineers, a mentor in the first cohort of the Shandong Provincial Innovation and Entrepreneurship Education Mentor Pool, a communication review expert for the National Natural Science Foundation of China, and a peer reviewer for several journals including Science Reports, IEEE Access, and Energies.
Her main research interests include trajectory planning and control for intelligent vehicles and intelligent vehicle detection methods. In the past five years, she has received two First Prizes of the Science and Technology Award for Higher Education Institutions in Shandong Province, one Second Prize of the Science and Technology Progress Award of the China General Chamber of Commerce, and two First Prizes and one Second Prize of the Science and Technology Progress Award of the Shandong Machinery Industry, among others. She has presided over one project funded by the National Natural Science Foundation of China, one Shandong Natural Science Foundation project, one key regional talent introduction project for urgently needed talents in Shandong Province, one project for enhancing the innovation capacity of technology-based SMEs in Shandong Province, one Jiangsu Provincial Postdoctoral Fund project, and two open projects of State Key Laboratories; she has also participated in two National Natural Science Foundation projects, three provincial- or ministerial-level projects, and two Shandong Provincial Key R&D (Major Science and Technology Innovation Project) projects. She has published and had accepted more than 60 papers, including over 30 in SCI-indexed journals, over 20 in EI-indexed journals, 2 indexed by ISTP, and 4 in core Chinese journals. She holds more than 30 authorized national patents.
I. New Methods Empower the Development of Active Obstacle Avoidance Systems for In-Wheel-Motor Electric Vehicles
To develop an active obstacle avoidance system for independently driven in-wheel motor electric vehicles, the research considers three aspects: modeling of the dynamics of four-wheel independently driven electric vehicles and the study of safe, economical, and efficient trajectory planning methods; trajectory generation methods that take into account human behavioral characteristics during vehicle operation; and trajectory optimization methods that ensure stable steering of electric vehicles while driving. On this basis, trajectory planning methods suitable for active obstacle avoidance systems of four-wheel independent-steering electric vehicles are proposed to assist drivers in automatically controlling the vehicle, ensuring stable steering in emergency situations when encountering obstacles. This research has broad application prospects, and its outcomes can be applied to track planning for unmanned aerial vehicles, car-like robots, intelligent vehicles, national defense, and other engineering fields.
II. New Systems Enhance the Tire Appearance Defect Detection Industry
Given the large demand for intelligent tire appearance inspection equipment, the high cost of imported systems, their inability to meet diverse domestic detection needs, and the low efficiency and poor accuracy of existing domestic methods for vehicle tire appearance defect detection, the team has developed an intelligent detection system for vehicle tire appearance defects. By fusing multi-sensor information, the system constructs a 3D image model of the tire, automatically acquires, analyzes, and processes panoramic images of tire appearance, and uses deep learning methods to label and classify defects in images. Products are directed to re-inspection stations based on defect characteristics, thereby improving the degree of mechanization and intelligence of tire inspection production lines and achieving efficient and accurate monitoring. The results can be applied to tire production lines, vehicle inspection stations, highway entrances, and other sites.
III. The Team Supports Research on Active Safety Technologies for Intelligent Electric Vehicles
In response to problems in relevant safety technologies for intelligent electric vehicles in complex driving environments and their practical engineering applications, the team focuses on research into active safety technologies and the development of practical equipment for intelligent electric vehicles. From four aspects—research on autonomous driving technologies for intelligent electric vehicles, research on lateral safety early warning systems, research on multi-target coordinated dynamic control, and development of chassis equipment for intelligent electric vehicles—the team proposes advanced theoretical methods suitable for intelligent electric vehicles and carries out engineering application development of active safety technologies. The aim is to provide real-time and effective new theories and methods for autonomous control systems of intelligent electric vehicles, assist drivers in achieving autonomous vehicle control, ensure stable steering in emergency situations when encountering obstacles, improve the active safety of electric vehicles, and effectively prevent serious and major traffic accidents. The application prospects are broad.
IV. Integrating into Industry and Serving Social Development
The team actively engages in social service and promotes the transformation and application of research outcomes. It has carried out R&D projects with multiple enterprises, including “R&D of Remote Fault Diagnosis System for Commercial Vehicles Based on the Internet of Vehicles,” “R&D of Active Parking and Obstacle Avoidance System for Special Sanitation Vehicles,” “R&D of Offline Detection Equipment for ABS Wheel Speed Sensors of Commercial Vehicle Axles,” and “High-Precision Positioning and Navigation Research for Unmanned Inspection Vehicles Based on BeiDou GNSS,” creating value for enterprises.
E-mail: liaijuan@sdjtu.edu.cn