Special Sessions丨特别专题

 

Special Session 8: Advanced Theory, Technology, and Model for Transportation Environment Safety (交通环境安全前沿理论、技术与模型)

 

Transportation environment safety is an important foundation for the efficient operation of transportation systems. With the frequent occurrence of extreme climate events, the increasing complexity of urban transportation systems, and the emergence of new transportation modes such as the low-altitude economy, transportation environment safety is facing unprecedented challenges. This special session focuses on frontier theories, advanced technologies, and intelligent models for transportation environment safety, covering seven directions: disaster perception, monitoring, and risk assessment in transportation environments; intelligent inspection equipment and technologies for transportation infrastructure safety; applications of computer vision and low-altitude remote sensing in transportation safety; safety theories and technologies for low-altitude and emerging transportation modes; human behavior and evacuation dynamics in transportation environments; trajectory big data mining and safety modeling for transportation; and intelligent transportation safety models and artificial intelligence safety governance. The session aims to bring together scholars from fields such as transportation engineering, safety science and engineering, artificial intelligence, remote sensing and geographic information science, and human factors engineering to jointly explore the complete innovation chain from perception and monitoring, equipment development, and data mining to behavior analysis, intelligent modeling, and safety governance. It emphasizes interdisciplinary integration and the deep fusion of theory, technology, and models, providing academic support for the sustainable development of transportation environment safety.

This session is distinguished by its systematic perspective across the full chain of "perception–equipment–data–behavior–model–governance" and its deep interdisciplinary character. While regular sessions typically focus on a single dimension of traffic safety (e.g., transportation planning, traffic control, or a standalone intelligent algorithm), this session brings together transportation environmental hazard perception, intelligent inspection equipment for infrastructure, low-altitude remote sensing and computer vision, safety of low-altitude and emerging transportation modes, human behavior and evacuation dynamics, trajectory big data mining, and intelligent safety models and AI governance into a unified framework for cross-disciplinary discussion. This design reflects a key trend in current transportation safety research: solving safety problems increasingly depends on the synergistic advancement of theoretical breakthroughs, technological support, data-driven insights, and model empowerment, and emerging directions such as AI safety governance and low-altitude traffic safety can no longer be adequately covered by traditional classifications. The organizers, from Shenzhen University, The University of Hong Kong, and Wuhan University, bring complementary research strengths in extreme environmental hazard monitoring and low-altitude remote sensing intelligence, traffic behavior dynamics and AI safety governance, geospatial intelligence and spatiotemporal big data analytics, and intelligent transportation and trajectory big data mining. This complementary configuration ensures substantive cross-institutional and interdisciplinary academic dialogue, making the session unsuitable for the regular program.

 

 

Related Topics for this Session （but not limited to）:

1. ** Proactive Safety Perception and Risk Assessment in Transportation Environments

   ** Intelligent Inspection Equipment and Technologies for Transportation Infrastructure Safety

   ** Computer Vision and Low-Altitude Remote Sensing for Traffic Safety

   ** Safety Theories and Technologies for Low-Altitude and Emerging Transportation Modes

   ** Human Behavior and Evacuation Dynamics in Transportation System

   ** Traffic Trajectory Big Data Mining and Safety Modeling

   ** Intelligent Traffic Safety Models and AI Safety Governance

Submit Method:
1, submit it via the link: http://confsys.iconf.org/submission/ictte2026 (after entering the link, click on the corresponding topic)
2, send your manuscript to ictte2016@vip.163.com with subject "Submit+Special Session-8+Paper Title". (请通过邮件发送稿件，邮件题目：Submit+Special Session-8+Paper Title)

 

Special Session Chairman:

Jiang Wenyu is an Assistant Professor and Appointed Associate Researcher at the College of Civil and Transportation Engineering, Shenzhen University, and a Category C talent in the Shenzhen Special Appointment Talent Program. His main research interests include transportation environmental disaster monitoring (wildfires, avalanches, floods, and typhoons), computer vision and low-altitude remote sensing intelligence, and disaster prevention and mitigation, and emergency management. He currently serves as Deputy Director of the Joint Laboratory of Artificial Intelligence of Things (AIoT) at Shenzhen University, Secretary of the Professional Committee of the Guangdong Federation of Academicians, and Assistant in the Director’s Office of the National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environments (Shenzhen). He has led and participated in multiple longitudinal research projects, including the National Natural Science Foundation of China Young Scientists Fund (Category C), the National Key R&D Program of China, the Guangdong Provincial Key R&D Program, the Tibet Autonomous Region Key R&D and Transformation Program, the Consulting Research Project (Major) of the Guangdong Research Institute for Development Strategy, Chinese Academy of Engineering, the Shenzhen Discipline Layout Project, and the Shenzhen Natural Science Foundation Youth Fund (Category C). As first author/corresponding author, among others, he has published more than 20 papers in top domestic and international academic journals such as the International Journal of Applied Earth Observation and Geoinformation, Environmental Modelling & Software, the International Journal of Disaster Risk Reduction, Tunnelling and Underground Space Technology, the Journal of Safety Science and Resilience, China Safety Science Journal, and the Journal of Tsinghua University (Science and Technology). He has been granted 9 invention patents and 6 software copyrights, and has received two Special Prizes of the Guangdong Provincial Emergency and Safety Science and Technology Progress Award (2023, 2024) and the Fire Best Doctoral Dissertation Award. His research results have been applied and demonstrated in emergency management departments (bureaus) in Guangdong, Sichuan, Zhejiang, Heilongjiang, and other places, playing an important role in practical emergency response.

 

Shen Liangchang is a Postdoctoral in the Department of Civil Engineering at The University of Hong Kong. He received his Ph.D. degree in Safety Science and Engineering from Tsinghua University in 2024. His research interests include human behavior and evacuation dynamics in transportation environments, risk analysis and safety management of dense crowds, intelligent safety models, and the global governance of artificial intelligence. He is the principal investigator of a Young Scientists Fund project supported by the National Natural Science Foundation of China and has participated in research projects funded by the National Key Research and Development Program of China and the National Science Fund for Distinguished Young Scholars. He has also contributed to the preparation of national policy recommendations and think-tank reports.

 

Dehua Peng is a Hongyi Postdoctoral Fellow in the Department of Geographic Information Engineering, School of Remote Sensing and Information Engineering, Wuhan University, advised by Academician Jianya Gong. He received his Ph.D. in Cartography and Geographic Information Systems from the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, in June 2024, under the supervision of Prof. Huayi Wu and Prof. Zhipeng Gui. His research lies at the intersection of geospatial intelligence and spatiotemporal big data analytics. He has published over 20 peer-reviewed papers in top-tier journals in the fields of geospatial science, artificial intelligence, and computer science, including first-author papers in Nature Machine Intelligence and Nature Communications. He holds eight invention patents and two software copyrights. He is the Principal Investigator of a National Natural Science Foundation Young Scientists Fund project, a sub-project of a National Key R&D Program, and a China Postdoctoral Science Foundation General Grant. He was selected for the 2025 Postdoctoral Innovation Talents Support Program and the Hubei Provincial Postdoctoral Top-Tier Talent Introduction Program. His honors include ACM China Doctoral Dissertation Award Nomination, ACM SIGSPATIAL China Doctoral Dissertation Award, College GIS Rising Star Award. He serves as an Executive Committee Member of ACM SIGSPATIAL China, and a reviewer for TPAMI, TFS, TKDE, JAG, CEUS, IJGIS, and other prestigious journals.

 

Dr. Guan Huang is currently an Assistant Professor in Shenzhen University. His main research interests include intelligent transportation and transportation planning, spatiotemporal big data mining and modeling, machine learning, and spatial intelligence. He has published 16 academic papers, 10 of which were published as first/corresponding author in internationally renowned journals such as Transportation Research Part C: Emerging Technologies, Transportation Research Part A: Policy and Practice, Computers, Environment and Urban Systems, and Cities.