Zia, Muhammad Umer, Xiang, Wei, Huang, Tao, Ahmad, Jameel, Chattha, Jawwad Nasar, Naqvi, Ijaz Haider, and Butt, Faran Awais (2025) Unifying ground and air: a comprehensive review of deep learning-enabled CAVs and UAVs. Artificial Intelligence Review, 59. 19.

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Abstract

The tremendous advancements in artificial intelligence (AI) techniques, particularly those pertinent to computer vision and image recognition, are revolutionizing the automotive industry towards the development of intelligent transportation systems for smart cities. Integrating AI techniques into connected autonomous vehicles (CAVs) and unmanned aerial vehicles (UAVs) and their data fusion, enables a new paradigm that allows for unparalleled real-time awareness of the surrounding environment. The potential of emerging wireless technologies can be fully exploited by establishing communication and cooperation among AI-augmented CAVs and UAVs. However, configuring appropriate deep learning (DL) models for connected vehicles is a complex task. Any errors can result in severe consequences, including loss of vehicles, infrastructure, and human lives. These systems are also susceptible to cyber attacks, necessitating a thorough and timely threat analysis and countermeasures to prevent catastrophic events. Our findings highlight the effectiveness of AI-driven data fusion in enhancing cooperative perception between CAVs and UAVs, identify security vulnerabilities in DL-based systems, and demonstrate how V2X-enabled UAVs can significantly improve situational awareness in corner cases.

Item ID:	90305
Item Type:	Article (Research - C1)
ISSN:	1573-7462
Copyright Information:	This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
Date Deposited:	19 Jan 2026 22:01
FoR Codes:	40 ENGINEERING > 4006 Communications engineering > 400608 Wireless communication systems and technologies (incl. microwave and millimetrewave) @ 50% 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460299 Artificial intelligence not elsewhere classified @ 50%
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