Special Session | 专题论坛

Session 1

AI-Driven Perception, Collaborative Control and Clean Emission Technologies for Connected Vehicles
“人工智能驱动的智能网联汽车感知、协同控制与清洁排放技术” 

With the rapid advancement of artificial intelligence, 5G/6G cellular networks, and the Internet of Things, intelligent connected vehicles (ICVs) are reshaping the future of transportation. ICITE 2026 focuses on networked autonomous driving, deep reinforcement learning, and autonomous driving prediction technology, which aligns closely with the emerging research frontiers in this domain. This special session aims to bring together researchers, engineers, and practitioners to present and discuss cutting-edge innovations at the intersection of AI, intelligent vehicles, and green transportation. The session covers three integrated research themes: (1) AI-driven environmental perception for connected vehicles, including deep learning-based object detection, multi-sensor fusion, V2X cooperative perception, and edge computing for real-time processing; (2) collaborative control and intelligent decision-making for autonomous driving, encompassing vehicle-road coordination, adaptive cruise control, path planning, and digital twin simulation; and (3) clean emission and energy efficiency technologies for NEVs, covering real-world driving emission (RDE) measurement, battery thermal management, energy optimization strategies, and lifecycle carbon reduction approaches. We particularly welcome papers that explore the synergy between intelligent perception systems and emission reduction strategies, as well as studies on AI-enabled predictive maintenance and fleet management for sustainable transportation. This session will provide a valuable platform for sharing theoretical breakthroughs, methodological innovations, and practical applications that contribute to the development of safer, cleaner, and smarter transportation systems.

Chair: Assoc. Prof. Meng LYU, Guangdong Polytechnic of Industry and Commerce, China

Dr. Meng LYU is an Associate Professor and Vice Dean of the School of Automotive Engineering at Guangdong Polytechnic of Industry and Commerce, China. He earned his Ph.D. in Vehicle Engineering from Nanjing University of Aeronautics and Astronautics in 2020 and was a joint Ph.D. student at the University of Texas at Austin (2017–2019). His research focuses on vehicle energy efficiency and emission control, intelligent connected vehicles, autonomous driving, and AI applications in automotive systems. He has published over 30 papers (16 SCI/EI indexed), authorized 7 invention patents, and led more than 10 provincial/ministerial research projects. He is the program leader of Intelligent Connected Vehicle Technology and has received the China Invention Association Innovation Award (Second Prize). He has extensive experience in mentoring student competitions in intelligent vehicles and robotics.

Co-chair: Dr. Xiaomin Zhao, Guangdong Polytechnic of Industry and Commerce, China

Dr. Zhao Xiaomin is a Senior Engineer holding a Ph.D. in Computer Science, with research interests in computer vision and artificial intelligence. She previously worked as an algorithm engineer at the Neusoft Automotive Advanced Technology R&D Center and at Continental Automotive Electronics (Germany), where she was responsible for developing passive safety algorithms for a number of domestic and international vehicle platforms. She is currently with the School of Automotive Engineering, Guangdong Polytechnic of Industry and Commerce, China, where she serves as Program Leader of Automotive Intelligent Technology. Her research focuses on deep learning–based computer vision and autonomous driving technologies, with particular emphasis on deep learning algorithms for small object detection. She has filed 2 invention patents and 5 utility model patents. As principal investigator, she has completed several provincial and ministerial research projects, including an Industry–University–Research Innovation Fund project of the Ministry of Education, a Guangdong Young Innovative Talents Project for Higher Education Institutions, a Key Field Research Project and teaching reform projects of the Guangdong Provincial Department of Education. She has also mentored students to more than 20 national and provincial awards in skills competitions.

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