Skybound Surveillance: Enhancing Road Network Efficiency with Drone Inspections

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: 30 January 2027 | Viewed by 2274

Special Issue Editors


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Guest Editor
Information Technologies Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Interests: UAV detection and classification; video surveillance applications; artificial intelligence; image and video processing; video coding
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Aeronautics and Naval Architecture, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem Rkp. 3., 1111 Budapest, Hungary
Interests: UAV systems; transportation engineering; traffic engineering; human factors; aviation safety; UAV-based road inspection; intelligent transportation systems; sustainable and renewable-energy-powered UAV platforms

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Guest Editor
Department of Civil Engineering, College of Engineering, Amman Arab University, Amman, Jordan
Interests: traffic engineering; highway engineering; transportation safety; accident modeling; intelligent transportation systems; UAV applications in transportation monitoring and infrastructure management

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Guest Editor
Department of Aircraft Maintenance, College of Aviation Sciences, Amman Arab University, Amman, Jordan
Interests: solar and renewable energy systems; sustainable energy integration in UAV and aviation applications; energy-efficient power systems for drone operations in transportation engineering; hybrid and renewable-energy-based UAV propulsion technologies

Special Issue Information

Dear Colleagues,

The rapid evolution of unmanned aerial vehicles (UAVs) is transforming the way transportation systems and road networks are monitored, inspected, and managed. Rising traffic demand, aging infrastructure, safety challenges, and sustainability pressures are common to both developing and developed countries. Traditional inspection and monitoring practices are often time-consuming, costly, and limited in spatial and temporal coverage. In contrast, UAVs offer flexible, high-resolution, and timely data acquisition capabilities that can support more efficient, safer, and smarter transportation systems.

The aims of this Special Issue include the following:

  • Advancing the scientific foundations and applied methodologies of UAV-based monitoring in transportation and traffic engineering;
  • Promoting interdisciplinary integration between UAV technologies, aviation systems, human factors, and intelligent transportation systems;
  • Supporting the development, adoption, and operational deployment of UAVs for road network efficiency, safety, and asset management;
  • Encouraging the application of sustainable and renewable energy technologies in UAV platforms for transportation-related missions;
  • Facilitating global knowledge exchange through studies relevant to both developed and developing countries.

This Special Issue aligns fully with the scope of Drones by addressing UAV design, sensing, operations, safety, autonomy, and real-world civil applications in transportation infrastructures.

This Special Issue will welcome manuscripts that link (but are not limited to) the following broad themes:

  • UAV-based inspection, monitoring, and management of road, bridge, tunnel, and transportation infrastructure.
  • UAV-assisted traffic monitoring, congestion analysis, mobility assessment, and intelligent transportation systems.
  • Human factors, operator performance, training, workload, decision-making, and human–UAV interaction.
  • Aviation systems, UAV flight performance, operational frameworks, and low-altitude airspace integration.
  • Artificial intelligence, computer vision, big data, and digital twins for UAV-based transportation applications.
  • Sustainable, solar-powered, hybrid, and renewable-energy-based UAV systems for transport monitoring.
  • Safety, reliability, risk assessment, and regulatory frameworks for civil and transportation UAV operations.
  • Case studies, pilot projects, and large-scale implementations in urban, rural, and inter-urban road networks.
  • Policy, governance, economic, and societal aspects of UAV adoption in transportation.
  • UAV applications in both developing and developed countries' transportation systems.

We look forward to receiving your original research articles and reviews.

Dr. Anastasios Dimou
Dr. Omar Alharasees
Dr. Haitham A. Al Hasanat
Dr. Mohammad Saleh Fawaier
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 250 words) can be sent to the Editorial Office for assessment.

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

  • unmanned aerial vehicles (UAVs)
  • road infrastructure and bridge inspection
  • transportation and traffic engineering
  • human factors and operator performance
  • aviation systems and UAV safety
  • sustainable and renewable-energy UAV applications

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Published Papers (2 papers)

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22 pages, 15702 KB  
Article
Assessment of Asphalt Pavement Skid Resistance Using Ground-Based and UAV-Based Hyperspectral Synergy
by Qing Xia, Bin Li, Qiong Zheng, Yunfei Zhang, Xiegui Wu, Lihong Zhu, Jia Song, Xiaolong Chen and Tingting He
Drones 2026, 10(3), 209; https://doi.org/10.3390/drones10030209 - 17 Mar 2026
Viewed by 374
Abstract
Accurate assessment of the skid resistance of asphalt pavement is crucial for traffic safety. However, traditional detection methods suffer from inefficiency, high costs, and limited coverage, making them inadequate for large-scale road network monitoring. This paper proposes a method for assessing the skid [...] Read more.
Accurate assessment of the skid resistance of asphalt pavement is crucial for traffic safety. However, traditional detection methods suffer from inefficiency, high costs, and limited coverage, making them inadequate for large-scale road network monitoring. This paper proposes a method for assessing the skid resistance of asphalt pavements based on hyperspectral remote sensing. First, hyperspectral data of asphalt pavements with different aging degrees were acquired through ground-based spectral measurements, and feature bands correlated with the aging process were selected using the successive projections algorithm. Based on these results, the feature bands were applied to unmanned aerial vehicle (UAV)-based hyperspectral images to construct an aging spectral index capable of characterizing pavement aging conditions. Combined with the decision tree method, assessment of pavement aging conditions was achieved, with an overall accuracy of 96.52% and a Kappa coefficient of 0.948. Finally, a quantitative relationship model between the aging spectral index and skid resistance was established using regression analysis, with the coefficient of determination (R2) and root mean square error (RMSE) of the model being 0.869 and 3.26, respectively. The proposed method enables efficient, contactless and large-scale assessment of pavement skid resistance, expanding the application of UAV remote sensing technology in road maintenance. Full article
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Review

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40 pages, 2292 KB  
Review
Uncrewed Aerial System (UAS) Applications in Bridge Inspection: A Comprehensive Review of Platforms, Sensors, and Operational Effectiveness
by Bhupesh Chand, Frezer Ayele, Ian Pineiro-Dakers, Reihaneh Samsami and Byungik Chang
Drones 2026, 10(2), 144; https://doi.org/10.3390/drones10020144 - 18 Feb 2026
Cited by 2 | Viewed by 1090
Abstract
The growing number of older bridges has resulted in an increase in structural flaws, demanding frequent inspections and maintenance. Structural degradation accelerates post-damage recovery, emphasizing the necessity of preventive interventions. The use of Uncrewed Aerial Vehicle Systems (UASs) for bridge inspections represents a [...] Read more.
The growing number of older bridges has resulted in an increase in structural flaws, demanding frequent inspections and maintenance. Structural degradation accelerates post-damage recovery, emphasizing the necessity of preventive interventions. The use of Uncrewed Aerial Vehicle Systems (UASs) for bridge inspections represents a significant development in structural health monitoring (SHM). Traditional inspection methods are labor-intensive, time-consuming, expensive, and require access to high or difficult-to-reach areas, posing safety risks to inspectors. This study focuses on identifying drones that can efficiently support bridge inspection activities. Key factors influencing UAS selection include flight performance, flying modes, cost, sensor capabilities, payload capacity, and controller communication. The primary objective of this paper is to provide guidance to inspectors and transportation agencies regarding the capabilities and limitations of commercially available drones. It also outlines potential cost considerations associated with drone selection, including pilot skill level, platform cost, and sensor integration. These factors may vary depending on the type and complexity of the bridge being inspected. By addressing these aspects, this paper aims to assist decision-makers in making informed choices regarding the use of UASs for bridge inspection applications. Full article
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