Next-Gen Drone Safety: Intelligent Systems, LLM Analytics and Operational Risk
A special issue of Drones (ISSN 2504-446X).
Deadline for manuscript submissions: 18 March 2026 | Viewed by 714
Special Issue Editors
Interests: flight dynamics and control; aerial robotics; UAV design
Special Issues, Collections and Topics in MDPI journals
Interests: aerospace engineering; airports; aviation; operational research; transportation engineering; logistics; biomimetic robot
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid expansion of Unmanned Aerial Vehicles (UAVs) in low-altitude airspace has provided remarkable benefits across multiple sectors including logistics, agriculture, emergency services, and infrastructure inspection. However, the increased operational complexity and frequency of UAV deployments have led to a significant rise in safety incidents and near-miss events. Effective management and thorough analysis of these incidents, particularly minor events, remain critical yet challenging tasks due to resource limitations and reliance on manual expert analysis.
Recent advancements in artificial intelligence (AI), specifically the development of large language models (LLMs) such as GPT-4, offer promising new capabilities for systematic UAV accident investigation. Integrating these advanced language models with established human-factor frameworks like the Human Factors Analysis and Classification System (HFACS) can provide an efficient and effective means to analyse unstructured narrative reports from UAV incidents. This integration facilitates rapid extraction of human errors, preconditions, and organisational influences, enhancing the depth, speed, and consistency of investigations.
This Special Issue aims to gather high-quality original research and review articles that explore and evaluate novel methodologies combining AI technologies, specifically LLMs, with structured human-factors frameworks for UAV safety enhancement. We welcome submissions related to the application, validation, and advancement of AI-driven approaches for incident analysis and human-factor identification in UAV operations. We suggest that the submitted paper be substantial in content and capable of addressing or proposing solutions to the discussed topic. The paper must include research findings. The topics submitted to the special issue include, but are not limited to:
- Comparative evaluations of AI-assisted UAV incident analysis versus traditional methods;
- AI methodologies for extracting human-factor insights from UAV narrative reports;
- Case studies demonstrating AI applications in UAV accident investigations;
- Systematic AI-driven approaches to proactive UAV risk management;
- Field Validation Frameworks for AI-Based UAV Safety Systems;
- AI-based UAV safety monitoring system design;
- Intelligent safety control and advanced AI technology for multiple UAVs;
- AI-based fault-tolerant flight control systems in complex environments;
- Safe Autonomous navigation using intelligent technologies.
We look forward to receiving your original research articles and reviews.
Dr. Boyang Li
Prof. Dr. Gabriel Lodewijks
Dr. Kang Liu
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence in aviation
- aviation accident investigation
- aviation safety
- intelligent systems
- large language models (LLMs)
- UAS accidents
- unmanned aircraft systems
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