Theme: Low-altitude Transportation Systems: AI-driven Planning, Sensing, and Optimization

With the rapid advancement of AI technologies in drone logistics, urban air mobility, low-altitude highway maintenance inspections, and administrative patrols, low-altitude transportation systems have emerged as a key driver in the development of the low-altitude economy. As a cutting-edge research frontier in both academia and industry, this system not only embodies cross-disciplinary innovations spanning transportation, aerospace, electronic information, and highway operations management, but also carries the strategic mission of enabling intelligent maintenance of transportation infrastructure, alleviating urban congestion, improving the efficiency of logistics distribution and highway inspections, expanding personal mobility options, and reshaping the future urban transportation ecosystem.

Driven by low-altitude innovation, highway transportation systems face extreme requirements for real-time, high-frequency responses amid aerial dynamic loads and vibration disturbances. Advanced AI algorithms (such as deep learning and reinforcement learning) integrated with multi-source aerial sensing data (including vibration, visible/infrared imagery, video, and LiDAR point clouds) hold great potential in applications such as intelligent inspection of low-altitude transportation infrastructure, structural health monitoring, traffic planning optimization, 3D defect reconstruction, traffic safety assessment, and predictive maintenance. The development of these technologies can effectively address the complex challenges brought by the growth of the low-altitude economy and promote the transformation and upgrading of highway transportation systems toward greater intelligence and sustainability.

Objective:

The purpose of this special issue is to highlight advancements in integrating artificial intelligence with the low-altitude industry to enhance intelligent perception, predictive maintenance, and sustainable development of modern transportation systems.

Scope:

We welcome submissions that address, but are not limited to, the following topics:

• Current status and prospects of low-altitude transportation systems.
• Planning and scheduling of low-altitude, multi-modal, three-dimensional highway transportation networks.
• Layout and plan of ground infrastructure in support of low-altitude transportation system development.
• Low-Altitude big data mining for highway transportation systems.
• Task planning and route optimization for low-altitude, multi-modal logistics and delivery.
• Health monitoring and risk assessment of transportation infrastructure under dynamic environments (e.g., moving UAVs, weather disturbances).
• Intelligent services and safety assurance for low-altitude travel.
• AI-enhanced structure anomaly detection and degradation early warning for highway infrastructure.
• Sensor fusion frameworks integrating UAV-acquired highway traffic data with Internet of Things (IoT) networks.

Submission Guidelines:

Manuscripts should be original and not previously published elsewhere.

• All submissions will undergo rigorous peer review based on research merit and quality.
• Papers should be submitted through the journal's online submission system selecting the "Low-altitude Transportation Systems: AI-driven Sensing, Planning, and Optimization". This is to ensure that your submission will be considered for this special issue instead of being handled as a regular paper.
• Your paper can be submitted via https://mc03.manuscriptcentral.com/htrd.
• Author Guidelines: https://www.sciopen.com/journal/join_journal/submission_guidelines?id=1810149294156099586&issn=2095-6215
• HTRD Manuscript Template: https://www.sciopen.com/journal/join_journal/submission_guidelines?id=1810149294156099586&issn=2095-6215#a1

Special Submission Requirements: 

An article processing charge (APC) of CNY6,000.00 applies to papers accepted after peer review.

Submission Deadline: 31 May 2026

Expected Publication Date: 30 September 2026

Guest Editors:

Zhang Xiaoliang, Professor-level Senior Engineer, Research Institute of Highway, Ministry of Transport; Zhonglu Hi-Tech Transportation Technology Group Co., Ltd., China.

E-mail: 361624832@qq.com

She has long engaged in research on intelligent transportation, big data analytics, urban traffic, and road traffic.

Wu Yunpeng, Ph.D., Associate Professor, Master’s Supervisor. Kunming University of Science and Technology, China.

E-mail: wuyunpeng@kust.edu.cn.

His research interests include traffic safety monitoring, computer vision, and image processing.

Du Bowen, Ph.D., Professor, Doctoral Supervisor, National Leading Talent.

School of Transportation Science and Engineering, Beihang University (Beijing University of Aeronautics and Astronautics), China.

E-mail: dubowen@buaa.edu.cn

His work focuses on cross-disciplinary innovation integrating AI with civil and transportation engineering.

Sun Lishan, Ph.D., Professor, Doctoral Supervisor, and Dean of the College of Urban Transportation. Beijing University of Technology, China.

E-mail: lssun@bjut.edu.cn

He has long engaged in research on intelligent transportation and travel behavior.

Zhang Jian, Ph.D., Professor, Doctoral Supervisor. Southeast University, China.

E-mail: zhangjian8seu@163.com

Zhang Jian, male, He has long been engaged in research in transportation engineering, intelligent transportation, big data, and artificial intelligence.

Jiang Haifeng, Ph.D., Researcher. Research Institute of Highway, Ministry of Transport; Zhonglu Hi-Tech Transportation Technology Group Co., Ltd., China.

E-mail: 147942293@qq.com

He has long been engaged in research, technical consulting, and standardization in traffic safety and informatization.

Dr. Geng Yixuan, Post-doctoral Fellow. The University of Hong Kong, China.

E-mail: geng@hku.hk

He focuses on innovative research applying AI and computer vision to low-altitude UAV technology and intelligent safety monitoring of transportation systems.

Cao Zhiwei, Ph. D., Post-doctoral Research Fellow. Beijing Jiaotong University, China.

E-mail: zhiwei@bitu.edu.cn

His work focuses on intelligent sensing of transportation environments and detection of defects in infrastructure equipment.

Dr. Chang Xin, Ph.D., Master’s Supervisor. Civil Aviation University of China, China.

E-mail: xchang@cauc.edu.cn

His research interests include intelligent transportation systems, airport operations management and support, and urban air mobility (UAM) operational safety.