###### Abstract  
Integrating unmanned aerial vehicles (UAVs) into intelligent transportation systems (ITSs) will be pivotal in shaping next-generation smart cities. This paper proposes a novel three-layered framework for integrating UAVs into intelligent transportation systems (ITSs) and reviews the current developments, challenges, and future directions in this emerging field. This framework provides a comprehensive overview of the key components of UAV-integrated ITSs, encompassing UAV specifications and deployment strategies, communication networks, and data utilization for traffic management. The first layer explores UAVs' technical specifications, deployment strategies, and trajectory optimization, essential for maximizing UAV performance in transportation contexts. The second layer addresses the communication networks between UAVs and vehicles, along with the use of UAVs for responsive traffic monitoring. This includes the development of robust communication protocols and real-time traffic analysis to enhance system efficiency. The third layer focuses on advanced data collection processing techniques and complexities, reviewing the methods for analyzing the traffic data collected by UAVs for decision-making in transportation management. Moreover, the paper presents the current UAV-enabled ITS implementation, highlighting key challenges and future research directions. By providing a comprehensive overview of UAV-enabled ITSs, this study presents a significant portrayal of the current landscape of UAV integration in ITSs and serves as a foundation for future advancements in smart city infrastructure. u 2024 14 9455 15 October 2024  
widely implemented in all possible applications. Upcoming technologies, such as connected autonomous vehicles and unmanned aerial vehicles (UAVs), are crucial components of the large-scale, global deployment of ITSs [4,5]. Their integration can significantly improve traffic management by alleviating congestion and enhancing traffic flow [6]. Traffic congestion increases yearly with the increasing number of cars and insufficient road capacity, which has social and economic impacts [7]. In 2019, American drivers lost an average of 99 h annually due to traffic congestion, costing approximately USD 1377 per person [7]. By 2020, the average time lost was reduced to 26 h, primarily due to the COVID-19 pandemic, which translated into a savings of USD 51 billion or about USD 980 per driver [8]. This suggests that alleviating traffic congestion will reduce time lost and associated costs, enhancing social and economic conditions. However, more recent data from 2022 indicate that congestion has begun to return to pre-pandemic levels, with drivers experiencing an average of 51 h of delay, costing around USD 1300 per driver [9]. Therefore, the primary goal of ITSs is to ensure efficient traffic flow, improve transportation safety, and enhance productivity through the implementation of advanced information technologies [10]. To achieve this goal, UAVs can be integrated into the transportation system, including tracking and monitoring ground vehicles, supporting logistics by replacing conventional methods, and providing real-time emergency response with autonomous UAVs. Many logistics companies have recently adopted UAV-based transportation to bypass traffic congestion and ensure faster deliveries. The global market for UAV-assisted logistics and transportation is projected to grow significantly from USD 5.3 billion in 2019 to USD 11 billion by 2026 [11]. Additionally, UAVs can be utilized in other transportation-related areas, including traffic monitoring, urban planning, and disaster response. As the number of automated vehicles increases, UAVs will play a crucial role in advancing computerized transportation systems [4]. Ongoing developments in this field are opening up new research opportunities and applications, with many researchers and transportation professionals actively working towards establishing UAV-enabled ITSs [5,12]. The benefits of UAV-enabled ITSs have been mainly described in Ref.