1 Introduction
Over the past decade, ground traffic congestion has become an increasingly severe challenge for major cities worldwide. This persistent issue not only disrupts daily commutes but also contributes to increased fuel consumption, higher greenhouse gas emissions, and a decline in overall urban livability (
De Palma and Lindsey, 2011;
Wen et al., 2020). As recently reported by INRIX (
2024), major metropolitan areas in the US such as New York City experience an average of over 100 h of delay per driver annually due to traffic congestion, resulting in a total nationwide economic loss of $74 billion from wasted fuel and productivity declines. In parallel, the average one-way commuting time of the top five most congested cities in China surprisingly reaches 39 min, with average peak hour traffic speeds reducing to about 25 km/h (Baidu Map and Beijing Transport Institude, 2024). The primary causes of worsening traffic congestion include rapid urbanization, which has led to a surge in vehicle ownership, and inadequate expansion of transportation infrastructure to meet growing demands (United Nations Human Settlements Programme, 2024;
Allen and Arkolakis, 2022). Unfortunately, the capacity of existing ground transportation networks in many metropolitan cities has nearly reached its limit. Expanding road infrastructure further in already congested city centers is often impractical and prohibitively expensive (UK National Infrastructure Commission, 2023;
Tennøy et al., 2019). As a result, there is an urgent need for innovative transportation modes to alleviate the growing pressure on ground transportation systems and provide sustainable solutions for urban traffic congestion.
In recent years, the rapid advancement of electric vertical takeoff and landing (eVTOL) technologies and autonomous systems has paved the way for the emergence of urban air mobility (UAM) as a new solution to urban transportation challenges (
Wang and Qu, 2023;
Cohen et al., 2021; UAM Initiative Cities Community and EU’s Smart Cities Marketplace, 2021). By leveraging relatively underutilized low-altitude airspace, UAM offers the potential to reduce reliance on congested ground networks and provide faster, more efficient, and environmentally friendly mobility options for urban residents. According to Markets and Markets (
2025) and Fortune Business Insights (2025), the UAM market is estimated to be $4.59 billion in 2024 and is projected to grow from $5 billion in 2025 to $23.47 billion by 2030. The total addressable market size of UAM across different countries/regions is shown in Fig. 1.
Unlike traditional aviation, which operates at higher altitudes and mainly serves long-distance, intercity, and international travel, UAM focuses on short-range, urban, and intra-city transportation. In addition, traditional aviation is based on large airplane designed for long-distance travel. In contrast, UAM relies on relatively smaller eVTOL aircraft that operate in low-altitude airspace and are integrated into complex urban environments, where airspace is shared with other users. Notably, UAM aircraft also need to accommodate rapid, localized operations with minimal human intervention, often relying on autonomous systems, which further differentiates them from traditional aviation, where manual control and longer operational times are more common (
Stevens et al., 2015;
Wei et al., 2024). Furthermore, the utilization of low-altitude urban airspace for UAM introduces new challenges related to noise pollution, environmental sustainability, and public acceptance, whereas these issues are relatively less important in traditional aviation due to its operation at higher altitudes and more limited interaction with densely populated areas (
NT et al., 2024). In summary, UAM requires a new regulatory framework, technological infrastructure, and safety measures that are different from those applied to conventional aviation. Table 1 provides a detailed comparison of the key characteristics between UAM and traditional commercial aviation.
In recent years, many studies have been conducted for UAM-related problems, focusing on aspects such as infrastructure planning, airspace design, and operation management of UAM systems (
Ale-Ahmad and Mahmassani, 2021;
Cummings and Mahmassani, 2024a;
Conrad et al., 2024). However, as a multidisciplinary and emerging field, these studies remain fragmented and lack a unified research framework. Therefore, a comprehensive review is critically needed to help researchers and stakeholders effectively explore the complex research field and grasp the overall state of knowledge in the UAM domain.
1.1 Review motivation
As an emerging industry, UAM has attracted significant scholarly attention in recent years, with many studies analyzing and summarizing the challenges, opportunities, and future roadmap for UAM systems. Cokorilo (
2020) provided an overall analysis of establishing dominant safety management principles within the aviation industry, with a particular focus on flight crew errors as a potential primary concern for UAM safety. Cohen et al. (
2021) employed a multi-method approach involving interviews and workshops to analyze the history, ecosystem, current state, and potential evolution of UAM. The research classified the development of UAM into six phases and identified several potential barriers to its large-scale adoption, including regulatory issues, community acceptance, and concerns regarding safety, noise, and environmental impacts, as well as infrastructure and business model limitations. Pons-Prats et al. (
2022) offered an in-depth qualitative analysis of relevant aspects of UAM development and implementation, assessing the current status and prospects of key areas by examining both literature and practical perspectives. Recently, Yan et al. (
2024) performed a comprehensive survey regarding UAM’s development and the challenges of integrating UAM with existing urban transport systems. Their study emphasized the need for harmonized collaboration among policymakers, urban planners, and technologists to balance UAM deployment with existing transportation systems while minimizing urban land-use conflicts. In summary, the aforementioned works predominantly focus on summarizing the current development status and challenges facing the UAM industry. The main objective of these studies is to lay the groundwork for UAM’s integration into existing public transportation systems by proposing broad strategic frameworks to inform policy and industry roadmaps.
Additionally, a subset of works specifically focus on research-level reviews with the aim of addressing various practical decision-making problems inherent in the development and operation of UAM systems. For example, Garrow et al. (
2021) conducted a meta-analysis of approximately 800 articles on UAM, electric vehicles (EVs), and autonomous vehicles (AVs) published between 2015 and 2020. Through a review of demand modeling, operational strategies, and infrastructure integration, it identifies some gaps and proposes future research directions in UAM system design. Rajendran and Srinivas (
2020) conducted a literature review to examine the research progress on UAM before 2020, including topics such as demand prediction, network design, air taxi fleet configuration, and dynamic pricing. Bauranov and Rakas (
2021) presented a review of airspace-related concepts and an evaluation framework for airspace performance tailored to UAM operations. Schuchardt et al. (
2023) and Sun et al. (
2021) contributed reviews on the literature concerning the operational aspects of UAM, such as air traffic mobility and operational planning considerations for ground infrastructure. Hwang and Hong (2023) and Fu and Moeckel (2024), on the other hand, synthesized literature investigating the development of UAM from a social perspective, with an emphasis on public acceptance dynamics and equity implications for service accessibility. Quite recently, Ahmed et al. (
2025) reviewed and summarized the findings of studies investigating public perceptions, market demand, and infrastructure requirements related to UAM and advanced air mobility (AAM). However, this review, while broadly including the main elements of the UAM system, did not offer a specific or well-defined research framework for the field.
Although fruitful reviews and surveys have been conducted, there is still a lack of a comprehensive review that synthesizes the research problems related to the planning, operations, and management of current UAM systems. Particularly over the past five years, UAM has transitioned from theoretical exploration to real-world pilot deployments, leading to an increasing number of real-world strategic and tactical problems that need to be properly addressed. Therefore, it is essential to conduct a comprehensive review to identify and analyze these newly arising practical research problems and to guide future research efforts.
1.2 Objectives and contributions
To bridge the aforementioned gaps, we conduct a comprehensive review in this paper for UAM from multiple perspectives. To provide a more accurate understanding of the factors influencing the successful deployment of UAM within urban environments, this review also incorporates social-related issues and various UAM application scenarios. The overall structure of this review is illustrated in Fig. 2.
Specifically, we aim to answer the following three review questions:
(1) What are the main research trends in UAM over the past five years?
(2) What are the main research areas and problems included within the current UAM research frameworks?
(3) What critical challenges does UAM face, and what are the potential directions for future research?
This review can serve as a valuable resource for researchers seeking to understand the current state of UAM research problems, policymakers aiming to make informed decisions regarding its implementation, and industry stakeholders intent on identifying key areas for innovation and investment. The remainder of this review is organized as follows: Following this Introduction, we provide background information on UAM and eVTOL in Section 2, outlining their historical evolution and major technological developments. Section 3 presents a review of research related to UAM system planning, which includes vertiport planning, airspace design, and demand forecasting. The relevant research from the perspectives of air traffic management, vertiport operation management, and flight operation optimization is summarized in Section 4. Section 5 reviews the literature on social issues related to UAM. Section 6 then provides the current commonly envisioned application scenarios for UAM. Section 7 discusses the review’s findings and identifies major research challenges. Finally, Section 8 concludes the paper with a discussion of potential research directions.
2 Development overview of UAM
This section provides an overview of the development of UAM and eVTOL technologies. We begin by tracing the historical evolution of UAM, from its early conceptualization and initial technological breakthroughs to the modern UAM systems emerging today. Then, the current status of major eVTOL aircraft is also examined to lay a foundation for the subsequent sections.
2.1 History and key driving factors of UAM
UAM and AAM can trace its conceptual origins back to mid-20th century visions of flying cars and personal aerial vehicles, which were initially explored in both science fiction and early engineering proposals. In 1917, American aviator Glenn Curtiss invented the first flying car “Curtiss Autoplane,” which is widely considered to be the first attempt that combined automotive and aeronautical technologies (
Aviationfile, 2023). Following this initial concept, several pioneering projects, such as Pitcairn PCA-2 Autogiro (1920), Waterman Arrowbile (1937) and Convair Model (1946), were proposed to bridge automotive mobility with aerial capabilities, which reflects early ambitions to realize personal aerial mobility (
Charnov, 2003;
Meaden, 1998). Subsequently, particularly after the 1950s, helicopters began to be utilized to provide scheduled passenger transport services within urban areas or between nearby regions (
Dajani et al., 1976). For example, New York Airways operated scheduled helicopter flights between the regional airports and a midtown Manhattan heliport, and similar services existed in cities like Chicago and Los Angeles (
LAWRENCE, 1984). In Asia, Hong Kong, China provided high-frequency flights from its Central district to Macao, China and Chinese mainland cities as early as the 1990s (
Lee et al., 2024a). Despite the operational presence of helicopter-based urban mobility services in megacities, their prohibitively high ticker costs, ranging from $300 to $1000 per one-way trip, have historically restricted accessibility to high-income users and thus prevented widespread adoption.
Modern UAM emerged in the 2010s as a promising urban mobility solution driven by advancements in aerospace technology, electrification trends, and urbanization demands (
Hasan, 2019;
Vascik et al., 2018;
Sengupta et al., 2025). The term “Urban Air Mobility” was first formally introduced by Airbus in its group forum magazine in 2016 (
Airbus Group, 2016). In contrast to earlier attempts, modern UAM represents a new direction toward technology-driven mobility systems that integrate four pillars: electric propulsion, autonomous systems, modular vertiport networks, and participatory governance. Most importantly, UAM was initially designed to serve the everyday needs of urban residents instead of merely catering to niche or luxury markets. A standard UAM system consists of multiple interconnected elements that work together to achieve safe and efficient urban mobility. For instance, dedicated vertiports provide the necessary infrastructure for eVTOL takeoff, landing, maintenance, and passenger boarding, while complementary facilities such as charging stations and communication networks support these hubs (
Schweiger and Preis, 2022;
Zaid et al., 2023). Moreover, reliable airspace planning schemes and advanced air traffic management systems are required to ensure seamless integration with existing air traffic such as low-altitude operations of unmanned aerial vehicles (UAVs) services (
Garg et al., 2023;
Schuchardt et al., 2023). Finally, ground transportation integration strategies should be implemented to create smooth intermodal connections (
Yan et al., 2024;
Jiang et al., 2024). A graphic illustration of the UAM system is depicted in Fig. 3. The vertistop refers to a small-scale takeoff and landing area, which could be located on rooftops or other limited spaces in urban environments. Compared to vertiports, vertistops are designed only for the vertical takeoff and landing of eVTOL aircraft, which focuses on quick passenger drop-off and pick-up. UAM air traffic management refers to the coordination and regulation of UAM operations within low-altitude urban airspace, such as routing, conflict detection, and resolution, to ensure safe and efficient flight operations. Supporting infrastructure includes various physical and technological components necessary for UAM operations, such as charging stations, maintenance facilities, and communication networks. Since UAM would not be affected by traffic congestion due to the characteristics of the low-altitude airspace, it is revolutionizing urban transportation by offering unprecedented time savings, efficiency, and convenience for passengers (
Preis et al., 2023). For example, AutoFlight’s 2024 Shanghai trials demonstrated a 10-min flight between Shanghai Pudong International Airport and downtown (normally 60–90 min by car) (
AutoFight, 2024). Similarly results can be observed from Joby Aviation’s New York demonstration, where their eVTOL aircraft completed the Manhattan-JFK International Airport corridor in 7 min - an 85%–90% reduction from the typical 50–75 min ground transportation duration (
Joby Aviation, 2023).
As a continuously evolving complex field, UAM technology maturity and commercialization progress have been categorized into multi-stage frameworks by leading aviation organizations and regulators worldwide. For example, North-east UAS Airspace Integration Research Alliance (NUAIR) categorizes UAM maturity level (UML) into four stages (UML-1 to UML-4) based on application scenarios, where UML-1 to 3 represent applications such as utility inspection, medical delivery, and cargo transportation, while UML-4 is designated for passenger transport (
NUAIR, 2021). National Aeronautics and Space Administration (NASA) has also defined a four-level UML specifically for low-altitude airspace management (
NASA, 2023), where UML-1 through UML-4 represent a progression in airspace management, moving from preliminary operational concepts to the eventual realization of intelligent air traffic management. The US Federal Aviation Administration (FAA) divides the UAM development into three operational evolutionary stages—Initial, Midterm, and Mature—based on scalability, autonomy levels, and regulatory adaptability (
FAA, 2023). Currently, UAM remains in its early developmental stage, with core technologies achieving progress but facing systemic barriers to widespread adoption. The adequate deployment of necessary infrastructure, reliable operational frameworks, and effective public engagement strategies are critical research issues that have gained considerable attention in recent years.
2.2 Technological progress of eVTOL aircraft
An eVTOL aircraft is an electric-powered vehicle that uses multiple rotors or tilt-rotor systems to achieve vertical takeoff and landing, operates with reduced noise and emissions, and relies on advanced batteries or hybrid-electric propulsion for efficient low-altitude flight (
DEWESoft, 2024;
Thompson et al., 2022;
Silva et al., 2018). These capabilities make eVTOLs ideally suited for UAM systems focused on short- to medium-range passenger transport (15–250 km), where their efficiency, speed, and flexibility address critical urban mobility gaps. The conceptual origins of vertical take-off and landing (VTOL) can be traced back to experimental vertical flight projects in the mid-20th century, such as Bell Aircraft’s XV-3 tiltrotor prototypes in the 1950s (
Thomason, 1990). NASA’s 1970s research on electric aircraft prototypes, such as the “Electrically Powered Flight” initiatives and “Solar Electric Propulsion tests,” pioneered the concept of clean aviation (
NASA, 1974;
NASA, 1970). The modern era of eVTOL aircraft began in the mid-2010s, driven by breakthroughs in electric propulsion, battery technology, and autonomous flight systems. Companies such as Joby Aviation, EHang, CHERY, and AutoFlight, alongside many others globally, have been at the forefront of designing eVTOL aircraft with different configurations and intended use cases. Some leading eVTOL aircraft models are shown in Fig. 4.
An eVTOL aircraft fundamentally consists of several critical subsystems that work together to realize its unique VTOL capabilities and electric propulsion (
Su et al., 2024;
Kadhiresan and Duffy, 2019). Although eVTOL aircraft share some similarities in design with helicopters, eVTOL aircraft are not simply electric versions of helicopters. They represent a new class of aircraft designed with advanced aerodynamics and distributed propulsion systems. Moreover, eVTOL aircraft are not scaled-up UAVs, as they require human-carrying certifications, redundant safety systems, and complex air traffic integration for urban environments. The comparison of key characteristics and parameters across eVTOL aircraft, helicopters, and UAVs is tabulated in Table 2.
3 Strategic planning for UAM systems
UAM planning includes the strategic design and coordination of physical infrastructure and airspace networks to ensure the safe, efficient, and seamless integration of eVTOL systems into the urban transportation network. In this section, we review the research problems from three key perspectives: vertiport design, airspace, and route network design, and UAM demand forecasting.
3.1 Vertiport planning and urban infrastructure integration
A vertiport is a dedicated ground-based infrastructure hub designed for the vertical takeoff and landing of eVTOL aircraft, which also serves an essential facility for passenger boarding, aircraft charging, maintenance and other related activities (
Brunelli et al., 2023a). It is important to note that there is still no unified definition or terminology in the field, with terms such as “Skyport” (
Mandava and Karatas, 2024), “Air taxi station” (
Rajendran and Zack, 2019), and “Vertihub” (
Adebimpe, 2023) often used interchangeably to describe similar concepts. In this review, we adopt the term “Vertiport” in a broad sense to represent all similar ground-based infrastructure. We also employ the term “Vertistop” to refer to a smaller type of vertiport, typically located on the rooftops of large buildings or other limited spaces, which serves as a facility solely for the takeoff and landing of eVTOL aircraft. In addition, we utilize the term
“Vertipad
” to specifically denote the designated takeoff and landing zone within a vertiport or vertistop.
3.1.1 Vertiport design, location and capacity determination
Compared to traditional public transportation facilities such as bus terminals or train stations, vertiport planning involves unique considerations due to the VTOL nature of the aircraft. For example, the internal layout design of a vertiport must accommodate dedicated landing and takeoff areas, passenger boarding and deboarding zones that are safe and efficient for vertical access, spaces for aircraft charging and potential maintenance, and smooth passenger flow between ground transportation and the aerial platform (
Preis, 2021;
Taylor et al., 2020;
Xiong et al., 2023). Vertiport design focuses on two research issues: vertipad design and vertiport topology optimization. Vertipad design refers to the determination of the minimum physical dimensions (length, width, and clearance zones) and other critical engineering parameters required for safe eVTOL touchdown, liftoff, and ground maneuvering (
Ahn and Hwang, 2022). The standards and guidelines for vertipad sizing are primarily established and mandated by relevant aviation regulatory authorities. According to the regulations set forth by the FAA, the touchdown and liftoff area (TLOF) must maintain a minimum width equivalent to 1 × diameter (D) of the largest intended aircraft, the final approach and takeoff (FATO) area extends to 2D to accommodate aerodynamic transitions, and the surrounding safety area (SA) mandates a 0.25D width clearance to prevent vortex interference and ground collisions (
NREL, 2024). Other critical design parameters (e.g., marking and lighting requirements, gate size, slope of the surfaces) are also detailed in various standards and guidelines to ensure the safe operation of vertipads. Another important aspect is the optimization of vertiport topology. Based on operational requirements, four topological configurations have been used: the single-pad topology (similar to traditional heliports), linear topology, satellite topology, and pier topology (
Zelinski, 2020;
Wille, 2024;
Peng et al., 2022). These topologies differ fundamentally in spatial efficiency and operational scalability: the single-pad design prioritizes simplicity and minimal footprint for low-demand vertiports, whereas the linear topology arranges vertipads in a line and supports sequential operations. The satellite topology includes a central passenger terminal with multiple separate vertipads connected to it, and the pier topology employs vertical stacking to maximize throughput in high-density urban cores. Figure 5 depicts a schematic layout of a vertiport that complies with FAA standards.
Another critical planning aspect related to vertiports is the location selection, which involves a detailed evaluation of potential sites based on various factors such as demand distribution, accessibility via existing ground transportation networks, airspace integration feasibility, environmental impact considerations (
Mercan et al., 2025;
Rohrmeier et al., 2025;
Mendonca et al., 2022). Demand distribution directly influences where vertiports should be strategically placed to capture the highest potential UAM demand (
Jiang et al., 2025). For instance, the vertiports can be located in or near areas with significant travel needs, such as densely populated residential areas, major business districts, transportation hubs like airports and train stations, and popular destinations for leisure or tourism. The location of vertiports not only depends on ground-level land availability but also requires careful consideration of low-altitude airspace usability such as safe approach and departure paths (
Guo et al., 2024). The usability of this airspace is shaped by factors such as surrounding topography, urban morphology, obstacle distribution, and potential conflicts with existing air traffic corridors, which collectively determine the operational feasibility and safety margins of prospective vertiport locations. Importantly, the on-demand nature of UAM services necessitates location strategies that is able to balance real-time demand fluctuations and thus enable rapid response times for users whenever and wherever they require air transportation (
Peng et al., 2022;
Lim and Hwang, 2019). Accordingly, it is crucial to appropriately determine the capacity of the vertiport to ensure optimal utilization of resources (
Rimjha and Trani, 2021;
Swaid et al., 2023). Overestimating capacity can lead to substantial upfront investment costs and underutilized infrastructure, while undersized layouts may result in operational bottlenecks, delays, and an inability to meet user demand. Furthermore, given the anticipated growth in UAM adoption, it is important to design vertiports with scalable capacity solutions that can accommodate future demand without requiring significant reconstruction or operational disruptions. Overall, vertiport location and capacity planning must be closely aligned with subsequent operational strategies and requirements of the UAM system (
Wang et al., 2022;
Jin et al., 2024b). Otherwise, the full potential of UAM cannot be fully realized in the future.
Finally, vertiport location and capacity planning is a classic type of complex optimization problems characterized by their NP-hard nature, which makes finding an optimal solution computationally challenging and time-consuming (
Drezner and Hamacher, 2004;
Shin et al., 2022). As result, it is of vital importance to design effective and reliable solution methods to solve the problem. In the literature, the developed methods can be broadly categorized into three main types: heuristic algorithms, exact algorithms, and data-driven algorithms. Heuristic algorithms are problem-solving methods that employ simplified rules and experience-based strategies to quickly find near-optimal solutions (
Silver, 2004). These algorithms are particularly suitable for large-scale vertiport planning scenarios with high-dimensional and highly nonlinear decision spaces (
Preis and Hornung, 2022a;
Senthilnathan et al., 2025;
Volakakis and Mahmassani, 2024;
Kim et al., 2024). Exact algorithms are optimization methods that guarantee finding the mathematically optimal solution to a problem (
Woeginger, 2003). Many commercial solvers are developed based on various exact algorithms (
IBM ILOG CPLEX, 2024;
Gurobi Optimization LLC, 2024). They are typically suitable for relatively smaller-scale vertiport planning problems with a limited number of potential locations and capacity options where computational time remains manageable (
Jin et al., 2024a;
Sinha and Rajendran, 2023). Data-driven algorithms aim to leverage historical and real-time data to optimize decisions by learning a function approximator. Their recent advantages in vertiport planning stem from the increasing availability of large traffic data sets and amazing advancements in artificial intelligence (AI) technologies (
Cha et al., 2025;
Lippoldt et al., 2021). Some research also employs simulation methods, which differ from the aforementioned algorithmic approaches by focusing on modeling and analyzing systems rather than directly solving optimization problems (
Nagel et al., 2000). Specifically, the main purpose of using simulation is to evaluate the performance of various vertiport planning strategies under different scenarios, where dynamic factors such as traffic patterns, demand fluctuations, and operational uncertainties are incorporated to provide insights into system behavior and inform decision-making (
Zhang et al., 2023;
Sheth, 2023).
In summary, the design, location, and capacity determination of vertiports are fundamental strategic issues in UAM system planning. The performance of vertiports directly influences operational efficiency, passenger accessibility, and system scalability. As UAM systems continue to be deployed in many countries and regions worldwide, vertiport planning remains a pressing research issue in the future.
3.1.2 Vertiport integration with ground transportation
Ground transportation, in the context of UAM, refers to the surface-based transportation systems that passengers utilize to travel between their origin or final destination and the vertiports, which forms a first/last-mile connection that partially determines the overall efficiency and accessibility of the UAM system (
Straubinger et al., 2020). The main structures and components of ground transportation within the UAM system include public transportation networks, such as the widely used train, subway systems, and bus services, which provide high-capacity connections to and from vertiport locations. Road infrastructure can accommodate private vehicles, taxis, and ride-sharing services that provide more options for passengers. Furthermore, active transportation options, including pedestrian walkways and bicycle lanes, are also important for connectivity, particularly for vertiports located within urban centers. Finally, intermodal transportation hubs and facilities, where passengers can seamlessly transfer between different modes of ground transport and the UAM service, are critical for improving travel experience. An example travel structure from the origin to the destination is depicted in Fig. 6.
Since passengers rely on ground transportation to access and depart from vertiports, the integration of vertiports with existing ground transportation networks is another research focus in recent years (
Wang et al., 2024). If the ground transportation connecting to vertiports suffer from severe traffic congestion, the time saved by utilizing UAM could be substantially reduced or even eliminated (
Yu et al., 2023). Therefore, it is necessary to strategically integrate vertiports with existing bus and subway systems without congestion concerns so as to offer a seamless travel experience for passengers (
Rahman et al., 2023;
Volakakis and Mahmassani, 2024;
Zhao and Feng, 2024). Some pilot projects focusing on how to integrate UAM with ground transportation have been explored and launched in some countries and regions. For example, Skyports, a provider of infrastructure for the UAM industry, has collaborated with Dubai parking company Parkin to develop vertiports by transforming existing parking facilities, aiming to integrate with Dubai’s metro and airport transportation networks and launch commercial UAM services by 2026 (
Skyports, 2024). Supernal (Hyundai Motor Group’s AAM subsidiary) is exploring the concept of a multimodal hub including eVTOL connectivity to assess how UAM systems could augment the existing public transport infrastructure (
Airports International, 2024).
Although the integration of vertiports with ground transportation is widely acknowledged as foundational to UAM’s large-scale operation, several notable challenges arise particularly in densely populated urban environments. For example, how to ensure that the roads connect to vertiports do not become congested as UAM scales up, even though this may not be a significant problem in the early stage of UAM. Moreover, the deployment of a large network of vertiports and vertistops throughout a city necessitates the large-scale expansion of the existing public transportation system, which requires significant financial investment and coordinated infrastructure upgrades.
3.1.3 Supporting infrastructure
Beyond basic deployment considerations, vertiport planning requires other supporting infrastructure to ensure operational viability and seamless urban integration. First, it is essential to deploy necessary charging infrastructure in the vertiport for eVTOL aircraft since the electric propulsion systems demand ultra-fast and high-power charging capabilities to reduce turnaround times between flights while maintaining battery health and safety (
Yang et al., 2021;
Hatherall et al., 2024;
Park et al., 2022). If the deployment of charging infrastructure at vertiports is insufficient or inadequately planned, it would inevitably diminish the ability of eVTOLs to realize their potential for medium to long-range transportation and thus reduce the overall efficiency of the UAM system.
Moreover, the fast battery charging of eVTOLs, ground support systems, and other terminal facilities necessitate a stable and uninterrupted power supply. Any power instability or insufficient capacity would cause operational disruptions, such as delays in eVTOL charging and subsequent flight schedules, potential safety hazards, and inconvenience or even safety issues for passengers (
Ishfaq et al., 2023;
Coenen et al., 2024). In the literature, many studies have investigated the potential impact of vertiport electrification on local power grids (
Paudyal et al., 2024;
Menzi et al., 2024;
Ibusuki and Viti, 2023). In general, it is of vital importance to understand the relationship between the scale of vertiport planning and the capacity of the local electricity infrastructure. Similar research and projects in the deployment of EV charging infrastructure can provide valuable insights. Notably, recent studies have shown that simultaneous high-power charging during peak hours can create significant stress on local power grids, potentially leading to overload risks and even outages at charging stations (
Luo et al., 2025;
Li and Jenn, 2024). A viable solution to mitigate the surging load is to coordinate the charging behavior of EVs by developing intelligent scheduling strategies (
Zhao et al., 2024). Similarly, the operation of vertiports should also incorporate intelligent scheduling and management of their electricity consumption.
Finally, a key supporting infrastructure for both vertiports and the entire UAM system is a robust communication network, which is essential for real-time coordination, safe air traffic management, and seamless connectivity between eVTOLs, ground control, and other airspace users (
Ertürk et al., 2020;
Zaid et al., 2023). The UAM communication network consists of ground-based stations, satellite links, onboard avionics, and 5G/6G cellular networks (
Moon and Chae, 2024;
Na et al., 2024). The associated planning problems include spectrum allocation optimization, interference mitigation and data security, with the objective of designing an optimal network to guarantee reliable and low-latency connectivity across the operational airspace.
In summary, the planning of infrastructure related to the operation of vertiports is a complex and systemic research problem that requires the collaborative optimization of the vertiport locations, capacities, integration strategy, and the supporting infrastructure. Given that the social acceptance toward UAM is still questionable, a well-designed ground infrastructure network is pivotal to building public trust and promoting the adoption of UAM in the future.
3.2 Airspace and route network design
In addition to the planning of ground infrastructure, the design of airspace and route networks is fundamentally important for the successful deployment and operation of the UAM system. A well-designed airspace structure and efficient route network can improve operational efficiency and effectively mitigate potential risks. In this section, we review the research problems associated with the design of airspace and route networks within the UAM system, aiming to provide a comprehensive analysis for this emerging field.
3.2.1 Airspace structure and UAM airspace planning
Airspace refers to the designated three-dimensional portion of the atmosphere that is regulated by a governing authority (such as a national government or international aviation body) for the purpose of managing and controlling aircraft operations. The traditional aviation industry has established a highly mature airspace classification system over decades of operational experience and regulatory refinement. This well-defined framework, standardized by ICAO and adopted globally, segments airspace into clearly delineated classes (A-G) with precisely specified dimensions, traffic rules, and communication requirements for each category (
Sridhar et al., 1998).
For the UAM system, the airspace is designed to accommodate low-altitude eVTOL operations in urban environments (
Bauranov and Rakas, 2021;
Cummings and Mahmassani, 2024b). Many countries and regions have introduced policies and guidelines to govern low-altitude airspace usage. For example, the Civil Aviation Administration of China (CAAC) has issued the National Airspace Basic Classification Method, which standardizes Class G and W airspace as uncontrolled airspace and thus pave the way for progressive deregulation of low-altitude zones (
CAAC, 2023). Recently, several Chinese cities including Shenzhen, Chengdu, and Changsha have obtained authorization to manage portions of controlled airspace for potential UAM operations, which is a breakthrough in low-altitude airspace reform. Figure 7 illustrates the diagram of the China’s future national airspace classification incorporating UAM operations. In this figure, Class A-E are controlled airspace types, where air traffic control services are provided to manage aircraft operations. Class G/W represents uncontrolled airspace, where aircraft operate without direct air traffic control oversight. The “
” in the figure refers to the radius of influence or operational range for Class B/C, indicating the area around an airport within which the respective airspace class applies.
UAM airspace, as a part of the low-altitude airspace, differs from conventional airspace in many aspects. First, its operations are constrained by terrain and infrastructure, thus generating a limited three-dimensional envelope that must accommodate exponentially higher traffic density compared to traditional airspace. Second, UAM passengers require frequent short-haul point-to-point urban travel demand rather than conventional aviation’s long-distance. Therefore, UAM airspace is expected to experience significantly higher traffic density, with multiple eVTOLs simultaneously operating at low altitudes. Moreover, safety considerations are particularly important given the inherently more complex and congested nature of urban airspace. Based on these new characteristics compared with traditional airspace, some emerging research problems have been raised in recent years. For example, UAM airspace capacity assessment aims to quantitatively evaluate the maximum number of safe flight operations that can be accommodated within specific urban air corridors and vertiport zones per unit time (
Aarts et al., 2023;
Murça, 2021). The assessment results can be leveraged to further comprehensive airspace risk evaluation by identifying potential bottleneck areas, conflict hotspots, and operational saturation points that could compromise safety margins (
Su et al., 2022;
Yang et al., 2024). Given the fact that operational demands and technological capabilities continue to progress rapidly, the planning of the airspace is not a static optimization problem. Hence, it necessitates a dynamic and demand-responsive scheme to airspace planning that requires close collaboration between regulatory authorities, UAM operators, and end-users. From the operational perspective, the airspace may also require real-time planning to handle fluctuating demand, weather disruptions, and urban obstacles (
Hearn et al., 2023).
3.2.2 Design and optimization of UAM route networks
In the aviation industry, a route network is the interconnected system of flight paths and destinations that an airline operates to transport passengers and cargo between cities or countries. In contrast, UAM route networks are three-dimensional urban corridor systems designed specifically for eVTOL aircraft, where corridors are virtual highways in the low-altitude airspace to ensure safe and efficient point-to-point transit within urban areas (
Muna et al., 2021). Unlike traditional airways that follow fixed ground-based navigation routes at higher altitudes with standardized separation, the corridors in low-altitude airspace must be designed with special consideration for the unique characteristics of UAM operations.
In recent years, some studies have focused on developing more reliable and robust corridor networks to improve the operational efficiency of the UAM system (
Nguyen, 2020). First, it is essential to analyze the key factors influencing corridor planning, such as urban morphology (building density/distribution), regulatory constraints, vertiport locations and capacity, noise/emission restrictions, and demand patterns (
Toratani et al., 2023;
Verma et al., 2022). It is worth noting that the corridor planning is a classic multi-objective optimization problem that requires simultaneously balancing competing objectives (
Zhang et al., 2025). For example, the maximization of traffic throughput may conflict with noise reduction goals in residential areas. Second, the structural design of corridors is also a practical research problem that attracts attention from both the academia and industry. The FAA has proposed three corridor configurations to address diverse UAM operational needs (see Fig. 8): (1) conventional one-way corridors; (2) corridors with vertical or lateral passing zones in which the aircraft can temporarily deviate from standard routing; and (3) multi-track corridors incorporating parallel sub-routes within a master pathway to facilitate simultaneous multi-directional flows (
FAA, 2023).
3.2.3 Integrated planning for UAM airspace
UAM serves not only as an emerging transportation solution to alleviate ground traffic congestion but also extends to multiple application scenarios such as low-altitude logistics, emergency rescue services, and city management. For example, eVTOL aircraft can be utilized to swiftly transport critically ill patients to hospitals or deliver firefighting equipment to inaccessible wildfire zones (
Angelini et al., 2024). Moreover, eVTOL is able to offer aerial sightseeing experiences, which allows passengers to enjoy panoramic views of city skylines and landmarks from unique vantage points that traditional ground transportation cannot provide (
Rahman, 2024). Hence, the integration and systematic planning of low-altitude airspace is another research focus to ensure the scalable operation of these diverse UAM applications.
From the planning perspective, the division of the low-altitude airspace must prioritize layered altitude allocations and mission-specific corridors to prevent conflicts between heterogeneous operations. However, given the current immaturity of UAM commercialization, research in this domain remains underdeveloped. Nonetheless, it is beneficial to conduct preliminary studies to explore scalable network architectures that accommodate future traffic density growth while maintaining backward compatibility with other emerging application scenarios.
3.3 UAM demand forecasting and analysis
In this section, we review the related research problems associated with UAM demand forecasting and analysis. The prediction and evaluation of future transportation needs for UAM services can help policymakers, service operators, and other stakeholders make informed decisions about infrastructure planning and airspace design. Without accurate demand forecasting, there is a risk of either underbuilding infrastructure (leading to congestion and inefficiency) or overbuilding (resulting in wasted resources).
3.3.1 UAM market analysis
The objective of market analysis is to determine the attractiveness of a market and to understand and analyze its evolving opportunities and potential threats (
NetMBA, 2002). In the context of UAM service, market analysis plays a crucial role in the planning stage since it provides the necessary data required to make decisions and formulate policies regarding the system design, operational strategy, and investment priorities (
Goyal et al., 2018). From a macro perspective, many institutions and research organizations have projected the future market size of UAM (
Morgan Stanley Research Estimates, 2021;
Markets and Markets, 2025;
Fortune Business Insights, 2025). These projections are typically developed through comprehensive methodologies that combine technology adoption modeling with demand estimation frameworks, where analysts examine historical data from similar transportation innovations while considering new characteristics of the UAM service. In general, there is a promising outlook for the UAM market, with most reports forecasting exponential growth as technology matures and gains regulatory approval. However, these broad market estimates offer limited practical value for specific UAM planning problems. Therefore, in addition to macro-level projections, we also need to identify and analyze the core factors that truly determine market size and viability.
From a micro perspective, a straightforward approach for market analysis is to conduct surveys with experts and potential users (
Fu et al., 2019). For instance, stated preference surveys are particularly suitable for capturing user acceptance and willingness-to-pay in the UAM market where revealed preference data are relatively limited (
Chae et al., 2024;
Hwang and Hong, 2023). These surveys typically present respondents with carefully designed choice scenarios that vary key service attributes such as travel time, cost, safety records, and waiting time, allowing researchers to quantify trade-offs between different choices. To analyze these choices, various discrete choice models are employed including, for example, logit-based discrete choice model, which estimates the probability of selecting a particular transportation mode based on its utility relative to competing alternatives. (
Cho and Kim, 2022). An example of the SP survey used in the context of UAM service is illustrated in Fig. 9. Given that UAM is a novel transportation mode, more refined questionnaire designs might incorporate visual aids or detailed descriptions of the UAM service experience to guarantee respondents have a clear understanding of the options presented.
3.3.2 Demand forecasting
For specific urban scenarios, it is required to forecast future UAM service demand as accurately as possible during the planning stage to assist subsequent infrastructure design (e.g., vertiport locations and air traffic corridors) and optimize operational strategies (e.g., fleet sizing, pricing models, and service coverage) for sustainable UAM integration. Generally, transportation demand forecasting often relies on analyzing historical travel patterns and socioeconomic data using various models. For instance, traditional methods might involve time series analysis of past ridership on similar transit systems or regression models that correlate travel demand with factors like population density, employment rates, and income levels (
Banerjee et al., 2020;
Profillidis and Botzoris, 2018).
Since UAM remains in the pilot phase with no commercial operations, it is impractical to obtain real-world data that can be directly used for UAM demand forecasting. Additionally, the UAM market is still in a dynamic and iterative development process with evolving technologies, regulatory frameworks, and public acceptance, which often limits the effectiveness of traditional static demand forecasting methods (
Ghalehkhondabi et al., 2019). Hence, researchers have increasingly turned to hybrid methods with more flexible incorporation of different considerations. For instance, the results obtained from the aforementioned SP survey can be combined with real-world ground transportation data (e.g., ride-hailing trip records, traffic congestion patterns, and public transit ridership) to identify which scenarios have a greater impact on potential future outcomes related to the UAM adoption (
Pukhova et al., 2021). A notable use case is Uber Elevate scenario, which could generate UAM demands by shifting a portion of conventional ride-hailing services to UAM options (
Bridgelall, 2023). The scenario framework can be defined based on the available technologies, infrastructure placement, pricing schemes, and operational strategies. These pre-specified scenarios can be integrated into a well-established simulation platform to identify which factors which of these factors have a greater impact on UAM demand (
Fu et al., 2022). Finally, the demand can be thus forecasted based on the specific characteristics and conditions of the city.
Notably, recent advancements in artificial intelligence (AI) have provided more reliable solutions for complex demand forecasting problems that are not easily handled by commonly used methods (
Yao et al., 2018). Deep neural networks (DNNs) can serve as powerful nonlinear function approximators to learn the underlying relationships between various demand-influencing factors and travel behavior patterns. This capability makes them particularly effective when considering a broader range of predictive variables that would be statistically insignificant in conventional models, such as month of the year (to capture seasonal variations), day of the week (for weekly commuting patterns), and time of day (for intraday demand fluctuations) (
Rajendran et al., 2021). Environmental factors like temperature, precipitation, wind speed, visibility, and air quality indices can be integrated to model weather-related impacts on UAM operations and user preferences.
In summary, recent research on UAM demand forecasting and analysis remains limited due to the lack of real data set. However, this field is expected to gain significant attention with the future commercialization and widespread adoption of UAM.
4 Operations and management of UAM systems
While strategic planning lays the foundation for UAM system deployment, the operational and managerial aspects of this emerging transportation mode have also received considerable attention. Unlike traditional ground transportation, UAM relies on low-altitude operations, which presents unique characteristics that require tailored management approaches. In this section, we review key research problems in UAM operations management to provide an overview of the current state of the field.
4.1 Air traffic management
Traffic management is a broad concept including the procedures and systems used to improve the efficiency and safety of transportation networks. In ground transportation, traffic management refers to the coordinated planning and control of movement to enhance flow, reduce congestion, and minimize delays for both vehicles and pedestrians (
De Souza et al., 2017). Air traffic management (ATM), by contrast, aims to govern the movement of aircraft within three-dimensional airspace, focusing on collision avoidance, route optimization, and communication between air and ground systems (
Chen et al., 2024c). In the context of UAM, the relatively constrained airspace and high-density operations introduce new challenges for the efficient ATM.
4.1.1 UAM traffic management system
In this section, we will first introduce the overall architecture of the UAM traffic management (UTM) system. As reported by NASA (
2023), UTM is a complex system engineering that involves the collaboration of multiple stakeholders including vertiport manager/operator, airspace user, ATM service provider, ATM support industry, and regulatory authority. The objective and function of the UTM will move through a series of progressive stages, with each stage introducing different levels of operational complexity and service quality. At each stage, the overall UTM framework should integrate a series of operational capabilities derived from diverse sources. Figure 10 illustrates the identified UAM airspace capabilities.
From this figure, we can see that there are ten categories of capabilities to support effective UTM implementation. For example, the airspace management capability serves the purpose of safely and equitably organizing and allocating UAM airspace resources, including components such as airspace configuration management, ATM interoperability, and cooperative information exchange network. The airspace and procedure design capability involves designing structured three-dimensional airspace configurations to accommodate UAM activities. The airspace system regulations and policy operational capability establishes legal frameworks and compliance mechanisms that govern UAM operations, including regulations, certifications, guidelines, standards, and other related policies. The communications services and systems operational capability ensures reliable and secure data exchange between eVTOLs, ground infrastructure, and other airspace users through integrated communication networks.
To equip the UTM system with these capabilities, it is essential to establish top-level regulations, standards, and policies to guide its development and implementation. Moreover, strategic and tactical issues directly related to specific planning and operational aspects require more detailed solutions. In Section 3, we have reviewed the fundamental research questions concerning vertiport infrastructure design and airspace configuration planning. In this section, we will shift our focus to the operation and management of the UAM system, examining the current research landscape associated with the UAM operations.
4.1.2 Traffic flow coordination and demand control
The air traffic flow refers to the movement of eVTOL aircraft within urban airspace, including key parameters such as flight density, aircraft speed, route allocation, departure and arrival timetable, and separation distances (
Bertsimas and Patterson, 1998). To manage UAM operations, the first task is to model the traffic flow and analyze its characteristics. Generally, the modeling of the traffic flow is highly related with three interactive perspectives: airspace density assessment, flow rate estimation, and conflicts prediction (
Cummings and Mahmassani, 2024a;
Qu et al., 2023;
Schuchardt et al., 2023). In the early stages of UAM operation with limited flight routes and relatively low eVTOL density in the airspace, traffic flow management is often relatively simple. However, as UAM commercialization progresses, the system must accordingly evolve to coordinate and control traffic flow to prevent potential congestion and safety risks, especially considering the spatial-temporal demand patterns in urban environments (
Wang et al., 2021;
Shrestha et al., 2021;
Schuchardt et al., 2023). During peak demand periods, when demand surges in specific corridors or around major vertiports, the controller must intervene in the operation of the UAM system in order to maintain safety while satisfying the demand.
One of the most straightforward approaches is to optimize the eVTOL fleet size. By carefully determining the appropriate number of eVTOLs required to meet demand without causing congestion or underutilization, operators can strike a balance between service efficiency, operational costs, and travel demand (
Kang and Kim, 2023;
Rakas et al., 2021). Furthermore, fleet optimization can incorporate more operational considerations such as cruise speed, battery state-of-charge (SoC) and payload capacity (
Husemann et al., 2024).
Another commonly used strategy is to optimize the UAM operation through scheduling, which can be categorized into two main types: demand scheduling and service scheduling. Demand scheduling focuses on managing and controlling the spatio-temporal demand to ensure system efficiency and prevent congestion (
Paterakis et al., 2017). In other words, demand scheduling can flatten the demand profile, thereby facilitating peak load reduction. Taking EV charging as an example, grid overload risk during peak demand periods can be mitigated by reducing or shifting charging demand. To achieve this goal, decision-makers need to formulate incentive mechanisms to influence passenger decisions. Since the cost of UAM services is considerably higher than ground transportation modes, passengers may exhibit high sensitivity to the price. As a result, a dynamic pricing scheme can be used to influence the demand by offering differentiated price at different time periods (
Kirste and Stumpf, 2024). The demand scheduling mechanism for peak load reduction is visualized in Fig. 11.
Since some passengers may resist differentiated service treatments (e.g., dynamic pricing), one risk of demand scheduling is potential passenger dissatisfaction (
Haws and Bearden, 2006). Especially when passengers fail to receive scheduling information promptly or lack transparency about the rationale behind demand-based adjustments, perceived unfairness may significantly hinder their willingness to choose UAM services. Another scheduling approach is service scheduling, which, in contrast to demand scheduling, does not directly influence passenger decisions. Instead, service scheduling focuses on optimizing the provision of the UAM service itself by adjusting factors such as flight timetable, ground time and cruise speed (
Song and Yeo, 2021;
Wei et al., 2021). For example, the reservation-based service model is a more robust and reliable option because it transforms the demand into a predictable framework that enables precise resource planning and allocation (
Kang and Kim, 2024). Moreover, the coordinated adjustment of eVTOL cruise speeds on select routes and ground handling times can alleviate operational strain without requiring explicit passenger behavior modifications.
In conclusion, traffic flow coordination and demand control are two interactive components within UAM operations. The traffic flow coordination requirements can be effectively addressed through strategic demand control measures. Conversely, dynamic adjustments to traffic flow parameters can indirectly regulate demand patterns by improving system throughput and reliability.
4.1.3 Safety management
The safety requirements for UAM operations are extremely strict since any accident could lead to catastrophic consequences and significantly undermining public acceptance in this emerging transportation mode. The safe integration of UAM into dense urban environments requires robust safety management systems and emergency response schemes tailored to the unique challenges of low-altitude airspace operations (
Ellis et al., 2021;
Torens et al., 2021). The safe operation of UAM systems necessitates multi-stakeholder collaboration and coordination, where ATM plays a key role in maintaining operational safety of the eVTOL aircraft. Specifically, safety management from an ATM perspective encompasses preventive measures and contingency management. Preventive measures refer to proactive safety strategies, such as the development of collision avoidance systems, designed to eliminate hazards before they escalate into incidents in UAM operations (
Sun et al., 2025;
Ortlieb et al., 2024;
Baek and Kim, 2025). In particular for high-risk scenarios such as intersections or merging points in urban airspace, collision risks significantly increase due to converging traffic flows (
Yahi et al., 2024a). Yang et al. (
2024) summarized the mainstream methodologies for UAM airspace design and collision risk assessment models for the safe operation of eVTOL aircrafts. Specifically, they reviewed categorization methods and structural approaches such as gridding, stratification, and networking, compared representative airspace models, and analyzed four types of collision risk assessment frameworks. The paper also discussed the applicability, advantages, and limitations of these methods and highlighted promising directions for future research. Su and Xu (
2024) proposed a comprehensive risk assessment method for mid-air collisions in UAM operations that integrates strategic, tactical, and collision avoidance barriers. Yahi et al. (
2024b) developed a risk assessment framework for UAM safety that includes simulation-based and probabilistic analysis to evaluate mid-air collision risks caused by Loss of Control In-flight (LOC-I) trajectories. Charnsethikul et al. (
2025) reviewed the potential safety risks of UAM aircraft operations in urban environments, with a particular focus on foreign object collisions such as bird and drone strikes.
A straightforward collision avoidance approach is to dynamically analyze the operational state of the entire airspace and then generate routes to minimize the likelihood of potential conflicts (
Yang and Wei, 2021). For instance, UAM operations can be modeled as a Markov decision process (MDP), where the state represents key parameters such as aircraft positions and environmental conditions, while actions correspond to routes adjustments or speed changes (
Bertram et al., 2022;
Bacon, 2022).
Another key component to achieve the safe ATM is contingency management, which focuses on predefined response schemes for abnormal or emergency situations when standard operating procedures become inadequate (
Fernandes et al., 2025). The contingencies mainly include: (1) loss of propulsion power; (2) onboard system failures (e.g., flight control or navigation systems); (3) unexpected airspace incursions by unauthorized drones or other aircraft; (4) adverse weather conditions (e.g., sudden wind shear or thunderstorms); and (5) communication failures. Although preventive measures can significantly reduce the occurrence of these contingencies, it is practically impossible to eliminate all potential risks in urban airspace operations. Thus, the inherent uncertainty necessitates the development of a contingency management framework that can handle unexpected scenarios. As the last line of defense in UAM safety systems, a series of strategies must be established in advance. For example, how to formulate effective collision resolution strategies for eVTOLs has attracted increasing attention in recent years. Compared with collision avoidance which focuses on proactive prevention, collision resolution emphasizes reactive mitigation via immediate emergency maneuvers when conflicts become unavoidable (
Ribeiro et al., 2020). When multiple eVTOL aircraft face conflicting flight paths due to system failures or other unexpected circumstances, standardized path replanning and speed adjustment procedures are executed to determine the alternative path while minimizing deviation from intended routes and ensuring passenger comfort (
Bilgin et al., 2023;
Deniz and Wang, 2024). It should be noted that conflict resolution is often by centralized solutions, thus imposing high demands on response speed. Although some AI-based technologies, such as deep reinforcement learning, have been proven capable of solving large-scale dynamic optimization problems, their application in UAM operations remains questionable due to stability concerns (
Chen et al., 2024b). When emergency situations make continued flight impossible, an emergency landing scheme will be activated, including dynamic identification of optimal ditching zones and generation of minimum-risk landing paths (
Pinto Neto et al., 2025;
Baleghi and Malaek, 2025). Figure 12 illustrates the conflict resolution process for 11 eVTOLs when one aircraft requires emergency landing (adapted from Xue (
2020)).
4.2 Vertiport operations and management
In addition to the ATM for UAM airspace and eVTOL aircraft, vertiport operations management is another crucial aspect to achieve large-scale UAM commercialization. It mainly consists of three core research problems: eVTOL handling operations, passenger flow management, and vertiport performance evaluation. The operational efficiency of vertiports directly impacts the UAM system throughput capacity, passenger experience, and even commercialization viability.
4.2.1 Ground handling operations for eVTOLs
Ground handling operations at a vertiport include all the activities performed on the ground that are essential for supporting UAM flights and passenger processing. Unlike conventional airports with expansive aprons and lengthy turnaround times, vertiports must facilitate rapid eVTOL turnarounds within tightly constrained spaces. More specifically, the ground handling sequence of eVTOLs from landing to takeoff must be highly streamlined, involving efficient passenger disembarkation and embarkation, rapid charging or servicing, and quick pre-flight checks to minimize dwell time at the vertiport (
Preis and Hornung, 2022b). This necessitates dedicated development of optimized eVTOL scheduling schemes to assign and sequence eVTOLs on the vertiport components (
Espejo-Díaz et al., 2023a;
Li et al., 2020). A scheduling example with four taking-off eVTOLs (1-4) and four landing eVTOLs (5-8) is depicted in Fig. 13, where taxiways refer to the designated ground pathways that guide eVTOLs between vertipads and gates. Gates, in this context, serve as transitional zones for boarding, disembarking, or standby between the vertipad and the staging stand zone, functioning similarly to terminals in conventional airports but tailored for the quick turnover and compact infrastructure of UAM operations. For example, eVTOL-1, which is scheduled for takeoff, first moves from the staging stand zone to Gate-3 via Taxiway-1 for final passenger boarding and preparation. It then enters Taxiway-2 and proceeds toward Vertipad-1, where it takes off as shown in Fig. 13.
The key scheduling and optimization objectives include minimizing eVTOL turnaround times/operational costs and maximizing vertipad utilization rate/total profit. The vertiport operation scheduling problem is similar to job shop scheduling problem (JSSPs) and thus can be solved by employing methods developed for JSSPs while incorporating vertiport-specific constraints (
Xiong et al., 2022). Real-world operations are more complicated due to additional charging and maintenance workflows. Therefore, scheduling frameworks should further integrate these workflows to better reflect reality. For instance, charging requirements depend on SoC levels, charging station availability, and eVTOL turnaround times. Given the nonlinear nature of lithium-ion battery charging curves (where charging speeds vary significantly between different charging stages), scheduling charging operations require careful coordination with other ground activities.
4.2.2 Operation mode for passengers
How to handle the passenger flow at vertiports is another pressing research issue before large-scale UAM adoption. In other words, we need to determine what operational models should be provided for passengers. Traditional transportation modes are briefly divided into two types: on-demand and on-schedule services (
Wang et al., 2023). On-schedule services operate like clockwork metro and bus systems, following predetermined timetables with fixed routes and stops, i.e., passengers must align their trips with published departure times (
Kumar and Khani, 2023). Under this model, passenger handling primarily involves managing their arrival and waiting at designated stations according to the published schedule. For example, queuing theory can be utilized to estimate the waiting time at the station and thereby provide operational management recommendations for optimizing service frequency and passenger flow (
Xu et al., 2014). On-demand services are more flexible transportation options in which vehicles are dispatched based on real-time passenger requests. Examples of on-demand services include ride-hailing and car-sharing services provided by transportation companies such as DiDi and Uber (
Young and Farber, 2019).
The determination of operational models for new transportation systems is normally demand-driven. In the early stages of UAM adoption, an on-demand service model is a more reasonable choice due to the flexibility it offers in responding to potentially sparse and unpredictable demand (
Wu and Zhang, 2021;
Chen et al., 2024a). Through dynamic vertiport-passenger matching and passenger pooling, the eVTOL utilization rate and operational cost can be optimized. As UAM demand grows and large-scale vertiports are deployed, the operational model may accordingly evolve into a hybrid adaptive system or on-schedule services. Since there is no existing large-scale implementations, current research on vertiport ground handling operations largely rely on simulation-based methodologies (
Preis and Cheng, 2022;
Unverricht et al., 2024). Commonly used frameworks include discrete-event simulation, multi-agent systems, and hybrid methods (
Rajendran, 2021;
Rajendran and Shulman, 2020;
Preis and Hornung, 2022b).
In summary, the research on operations and management of UAM systems remains relatively underexplored compared with planning problems. Most existing studies heavily rely on established concepts and models from traditional aviation sector, existing UAV (drone) operations, and ground transportation systems. As UAM deployment scales, further dedicated research into the unique complexities of its operations will be crucial to promote large-scale commercialization.
5 Social issues related to UAM
Assessing public acceptance and social impact is a prerequisite for UAM deployment. The goal is to systematically identify the factors that are of greatest concern to the public and thereby make targeted improvements in planning, operations, and regulation. The widespread deployment of UAM systems presents a unique set of societal concerns that are, in many ways, unprecedented due to their integration into dense urban environments. Considering the increasing maturity of eVTOL technology, how to enhance social acceptance is one of the most important factors for the current advancement and successful integration of UAM (
Biehle, 2022;
EASA, 2021).
5.1 Safety concerns
Due to the lack of real-world data, surveys and questionnaires are currently the predominant approach for collecting insights into public perceptions, attitudes, and concerns regarding UAM services (
Kalakou et al., 2023;
Karami et al., 2024). Safety concerns have been consistently identified as one of the most significant factors affecting public acceptance of UAM in the literature (
Al Haddad et al., 2020;
Ahmed et al., 2021). For ground transportation modes, even if a traffic accident occurs, its impact scope is often limited since their operation is always confined to a two-dimensional plane on the ground. However, eVTOL aircraft operations at lower altitudes within urban areas have a much more direct and potentially significant impact on people’s daily lives. Although UAM systems will undergo very rigorous safety testing, airworthiness certification, and trial operations before commercialization, it is practically impossible to fully alleviate public concerns. In 2024, a total of 40.6 million flights were conducted globally, with only 7 fatal accidents, resulting in an accident rate of 1.13 per million flights. The total number of fatalities was 244 with a death risk of only about 0.06% (
IATA, 2024). For comparison, the United States alone recorded 39,345 traffic fatalities in 2024, marking the lowest number of fatalities since 2019 (
NHTSA, 2024).
These statistics highlight that air travel is an extremely safe transportation mode. Nevertheless, a significant portion of the population still prefers less efficient travel options due to safety concerns. This hesitation stems from psychological factors rather than objective risk assessments. Fear of flying (aerophobia) is an extreme and irrational fear, anxiety, or panic of flying on a plane (
Howard et al., 1983). In the US, about 25 million people suffer from aerophobia, while studies suggest that up to 40% of the population in industrialized nations experience significant flight-related anxiety (
Cleveland Clinic, 2022). The main cause of aerophobia is the fear of aircraft crashes and fatal accidents because of the low survival rates in such rare but catastrophic events. Moreover, VTOL aircraft such as helicopters demonstrate significantly higher accident rates compared to fixed-wing aircraft. According to a report released in 2024, helicopter accidents occur at a rate of 72 incidents per 100,000 flight hours, whereas commercial airlines maintain a substantially lower rate of just 16 incidents (
Mighty Travels, 2024). The accident, injury, and fatality rate data in the US for various transportation modes in 2023 are summarized in Table 3. The data are sourced from Injury Facts, an authoritative statistical database maintained by the US National Safety Council.
Unfortunately, the safety challenges faced by UAM are even more severe. As an alternative to ground transportation, eVTOLs are designed to operate in a relatively congested low-altitude urban airspace, where any accident could have a wide-ranging impact (
Royal Aeronautical Society, 2022). Hence, aerophobia may affect not only passengers but also people on the ground. This “non-involved persons hazard” necessitates transparent risk communication beyond merely demonstrating regulatory compliance. Vertiport safety is another public concern because these facilities will inevitably be located in some core urban areas to mitigate the ground traffic congestion (
Rice et al., 2022;
Ison, 2023). Particularly, rooftops of certain large buildings may need to serve as vertistops for transit operations, which introduces more safety concerns to the public.
In summary, it can be anticipated that any safety incident, even if statistically rare compared to other transportation modes, will likely provoke significant public questioning and heightened concerns about the safety of UAM operations. Since it is realistically impossible to achieve a zero-accident rate, how to effectively build and maintain social trust in UAM is a pressing issue for operators, regulators, and policymakers.
5.2 Noise impact
One of the key advantages of eVTOL aircraft is their potential for reduced noise impact than conventional aircraft, particularly helicopters, due to the nature of their electric propulsion and rotor systems. Comparisons with cars suggest that eVTOL noise during cruises can be comparable to or even quieter than typical urban sounds (
Aerospace America, 2022). Nonetheless, the exploration of the noise impact during all flight phases will be beneficial to ensure public acceptance and successful adoption (
Farazi and Zou, 2024;
Greenwood et al., 2022).
The dominant source of noise in eVTOL aircraft is the aerodynamic noise generated by the rotors and propellers instead of electric motors. Research and experiments indicate that eVTOL aircraft produce the highest noise levels during takeoff and landing phases, typically ranging from 60 dB to 80 dB (
Lee et al., 2024b;
Yunus et al., 2023). During the cruise phase (approximately 500–600 m), noise levels decrease to 40-50 dB. This is comparable to the sound of a refrigerator running or light rainfall, and is even quieter than a normal conversation (typically around 60 dB) (
Aerospace America, 2022). For comparison, helicopters can produce noise levels of 100–120 dB during takeoff and landing, with cruise noise typically around 100 dB. Although eVTOL noise is relatively low, the cumulative impact of frequent operations can still raise public concern. Furthermore, studies suggest that the visibility of eVTOLs influences annoyance levels caused by noise, i.e., even at similar decibel levels, people perceive noise as more disruptive when they can see the aircraft overhead (
ZAG DAILY, 2025). Hence, the noise impact of eVTOLs cannot be assessed solely through decibel measurements. For instance, since eVTOLs operate in three-dimensional low-altitude airspace, the noise may affect different populations to varying degrees based on factors such as proximity, frequency of operations, and ambient environmental conditions.
5.3 Environmental impact and sustainability
Since there are no carbon dioxide emissions during operation, eVTOLs are considered a promising way to achieve the “net-zero emissions” target by 2050 proposed by the International Air Transport Association (IATA) (
Russo and Tan, 2023). However, research indicates that while electric propulsion has the potential to reduce emissions at the local level, the overall environmental benefits of UAM are complex and influenced by various factors such as energy sources, infrastructure construction, and life cycle assessments (
Zhao et al., 2022;
Mudumba et al., 2021;
Liberacki et al., 2023). For example, if electricity is drawn from traditional fossil fuel power plants, the energy production process will generate greenhouse gases and other air pollutants.
In fact, there is still a huge ongoing debate among scholars and the industry about whether electric mobility solutions (e.g., EVs and electric bus) are really more environmentally friendly than fossil-fueled vehicles (
Picatoste et al., 2022;
Franzò and Nasca, 2021). The mainstream view suggests that electric mobility is always more environmentally friendly, even when accounting for greenhouse gas emissions from power plants. The main reason is the increasing adoption of renewable energy sources such as solar, wind, or nuclear power, which will reduce the carbon footprint associated with charging batteries (
Olabi and Abdelkareem, 2022). Based on this premise, some studies have been conducted to compare UAM and other transportation modes from the environmental perspective. For example, for a 100-km trip, the emissions of an eVTOL carrying three passengers and one driver were 52% lower than those of a gasoline-powered car and 6% lower than those of an EV (
4AIR, 2025). However, for trips shorter than 35 km, the pollution from eVTOLs may be higher than that of gasoline-powered cars if the energy is fully drawn from non-renewable energy sources. This interesting reversal can be attributed to the fact that the energy consumption in take-off and landing phases in significantly higher than the cruise phase. As reported by Sripad and Viswanathan (2021), the total energy consumption per unit distance is directly proportional to the proportion of time spent in vertical flight, which indicates that energy consumption of eVTOLs is highly related to the travel distance. Figure 14 depicts the generalized eVTOL mission and battery output power profiles adapted from Li et al. (
2025) and Sarkar et al. (
2024).
Green hydrogen-powered VTOL aircraft, equipped with high energy density and fast refueling technologies, can achieve truly zero-emission operation compared with eVTOLs (
Yue et al., 2021;
Ng et al., 2021). However, the high production cost of green hydrogen and the lack of widespread hydrogen refueling infrastructure currently limit its scalability for mass adoption in the near future.
In summary, the environmental impact of UAM is a complex issue that requires comprehensive consideration of emissions, energy consumption, and energy sources. Although eVTOLs have the advantage of zero local emissions during operation, their overall environmental benefits depend on the cleanliness of the electricity source and the life cycle management of batteries.
5.4 Equity and accessibility issues
As an emerging technology, UAM services may face high operating costs in the early stages, which could lead to pricing significantly higher than traditional ground transportation modes. As recently studied in Husemann et al. (
2024), the travel cost can range from $27 to $46 per requested travel, which is generally cheaper than traditional taxi services for same distances but remains significantly more expensive than public transit. AutoFlight claims that its UAM service is priced at about 6 yuan (approximately $0.8) per kilometer (
Global Times, 2024). Since UAM is primarily designed for medium- to long-distance travel, this price is still relatively expensive in China. Moreover, it is somewhat unfair to compare UAM with taxi services as they are adopted in different scenarios. In fact, passengers often prefer more economical alternatives for medium- to long-distance travel.
If UAM services are accessible only to a small group of wealthy individuals, it may exacerbate existing social inequalities and create a new “transportation divide” (
Groth, 2019). Under such a scenario, its potential to alleviate ground traffic congestion will inevitably be diminished and the social acceptability will be negatively affected due to the inequitable access.
6 Representative UAM practice
In this section, the potential application scenarios and typical use cases of UAM services are reviewed to examine their roles in modern transportation systems in a more practical perspective. Specifically, we consider four representative scenarios: (1) urban and suburban commuting; (2) airport shuttle services; (3) emergency rescue and medical transport; (4) tourism and special event mobility.
6.1 Urban and suburban commuting
One of the main motivations of developing UAM systems is to mitigate ground traffic congestion, in which the core application scenario is urban and suburban commuting. The initial goal is to establish commuting connections between city centers and suburban areas using eVTOL aircraft (
Asmer et al., 2021;
Rimjha et al., 2021;
Zhao and Feng, 2025;
Perez et al., 2025;
Zhao et al., 2025). Compared to traditional ground transportation, eVTOLs can provide commuters with fast and flexible transportation options. As we discussed before, UAM can effectively reduce urban traffic congestion, save commuting time, and potentially reduce the use of ground vehicles. In addition, eVTOLs can utilize existing urban spaces (such as rooftop vertistops) for take-off and landing, thus reducing the need for expanding vertiports. In the literature, most studies investigating UAM planning and operational management problems often assume an urban commuting scenario (
Wang et al., 2022;
Chen et al., 2022). This is because commuting scenarios can effectively simulate most urban low-altitude use cases and provide a representative framework for analyzing demand patterns, traffic flow, and system capacity. In addition, since urban commuting networks are always highly complex because of the high volume of commuters during peak hours, policymakers can leverage this characteristic to identify critical issues and develop targeted regulatory frameworks.
However, high travel prices and operational costs may limit market penetration and mainstream adoption of UAM services. Moreover, the limited passenger capacity of eVTOLs makes it difficult to meet commuting demand. Currently, no large-scale UAM pilot operations have been conducted specifically for urban commuting applications. Nevertheless, it is expected that further advancements in technology, infrastructure, and regulatory frameworks will facilitate the deployment of UAM systems in urban commuting scenarios in the coming years.
6.2 Airport shuttle services
Airport shuttle services form another important UAM application scenario, which aims to establish fast transit connections between city centers and airports using VTOL aircraft (
Kotwicz Herniczek and German, 2022;
Lewis et al., 2021;
Brunelli et al., 2023b;
Adamidis et al., 2025). A NASA market study estimated that the total addressable market for airport shuttle and air-taxi routes in the US could reach about $500 billion under unconstrained conditions (
Hasan, 2019). Compared to the distributed nature of urban-suburban commuting networks, airport shuttle operations are generally more straightforward owing to their fixed route structures between a city’s limited major airports (usually 1-2) and designated urban vertiports (
Kim et al., 2025;
Jang et al., 2025;
Coppola et al., 2025). In addition, airports are typically located in suburban or more remote areas which naturally provide more available airspace and fewer obstacles for safe eVTOL operations.
In recent years, many eVTOL companies have conducted pilot operations and feasibility studies for airport shuttle services. For example, AutoFlight successfully demonstrated its eVTOL aircraft in a trial route connecting Shanghai’s Lujiazui financial district to Pudong International Airport, reducing the original travel time of 60–90 min by ground transportation to about 10 min (
AutoFight, 2024). Recently, EHang conducted an unmanned demonstration eVTOL flight in Qingyang, China, successfully completing a fully automated journey from the city center to the local airport (
CAACNEWS, 2025). The eVTOL aircraft executed all operational phases, including vertical takeoff/landing, cruise, and real-time obstacle avoidance, along a pre-programmed route. Joby Aviation has announced the construction of a dedicated vertiport at Dubai International Airport to provide shuttle services (
Joby Aviation, 2024). Archer Aviation plans to establish an air taxi network in New York using its Midnight aircraft to connect Manhattan with nearby airports, aiming to reduce travel times that typically take 1-2 h down to 5-15 min (
Archer Aviation, 2025).
Moreover, the operation system design and optimization for UAM airport shuttle services have attracted widespread attention. Case studies in megacities such as Beijing, Seoul, and Munich have demonstrated the technical and operational feasibility of UAM-based airport shuttle services (
Lv et al., 2024;
Choi and Park, 2022;
Hagspihl et al., 2025). A graphical illustration of the airport shuttle service adapted from Lv et al. (
2024) is shown in Fig. 15, in which eVTOL repositioning is considered to balance the supply and demand. In the near future, airport shuttle services will likely be the first commercially viable implementation of UAM systems, though the high cost of these services remains a concern that could limit market accessibility and widespread adoption.
6.3 Emergency rescue and medical services
Helicopters have long served as a vital asset in emergency rescue and medical services due to their ability to perform vertical take-offs and landings in confined spaces (
Taylor et al., 2010). Compared with traditional ground ambulances and other vehicles, they can provide rapid response and access to remote or difficult-to-reach locations, thus reducing the “golden hour” for medical intervention. To this day, helicopters remain widely used in time-sensitive medical transport scenarios. However, despite their proven utility, helicopters have several drawbacks that limit their large-scale adoption in more scenarios. As we introduced in Section 2.2, the high operational cost, considerable noise pollution, and relatively large size present significant barriers to applications in urban areas. These inherent limitations of helicopters highlight the need for alternative solutions to improve the efficiency, accessibility, and sustainability of emergency rescue and medical services.
Fortunately, eVTOL aircraft are widely viewed as a perfect alternative that offer advantages such as significantly lower noise levels, reduced downwash, smaller landing footprint, and lower operational costs (
Espejo-Díaz et al., 2023b;
Goyal and Cohen, 2022;
Ziakkas and Natakusuma, 2025). More importantly, the development of the broader AAM and UAM systems can support eVTOL operations with intelligent ATM and well-coordinated ground infrastructure. Additionally, potential for autonomous operation further enhances its capability to handle complex and hazardous emergency scenarios, such as firefighting and disaster relief. Figure 16 shows AutoFlight’s specialized firefighting eVTOL aircraft.
From the perspective of low-altitude airspace management, the integration of emergency rescue and medical services into UAM systems will inevitably introduce additional complexity in planning and operations. For instance, although dedicated corridors for emergency services would ensure priority access, the unpredictable nature of demand may lead to inefficient resource allocation. On the other hand, real-time coordination increases safety risks and places demands on ATM systems to ensure secure operations. Therefore, innovative strategies are essential for the successful integration of emergency eVTOL missions into UAM frameworks.
6.4 Aerial tourism and sightseeing
Another potential application scenario where eVTOLs can serve as an alternative to traditional helicopters is in providing mobility for tourism and sightseeing (
Suo et al., 2024). Over the past decades, many tourist destinations have offered helicopter cruise services to enhance visitors’ experiences. For example, Tokyo provides dozens of aerial sightseeing options, allowing passengers to enjoy breathtaking views of landmarks like Tokyo Tower and Mount Fuji from above. Similarly, renowned tourist cities such as New York, Shanghai, and London have also developed helicopter sightseeing services. However, these services are very expensive, often ranging from $200 to $1000 per seat depending on route duration and exclusivity.
In this context, eVTOLs offer a promising and potentially more scalable solution for providing large-scale aerial sightseeing services. In China, the development of low-altitude aerial tourism and sightseeing has been incorporated to a strategic level within the national civil aviation development plan (
ChinaDaily, 2025). Over 20 provinces and municipalities have released ambitious targets and policies to accelerate real-world deployment.
7 Challenges and open questions
As an emerging transportation mode, UAM faces widespread skepticism and numerous challenges since its introduction in 2016. Surprisingly, recent years have witnessed remarkable progress in UAM development. Many eVTOL models have already obtained low-altitude airworthiness certifications. Pilot operations have been conducted in many cities worldwide, which continuously validate the feasibility and practicability of UAM and eVTOL aircraft. It is predicted that the first commercial UAM operations may commence as early as late 2025. However, the long-term large-scale deployment of UAM systems still face some research challenges that must be resolved before achieving widespread adoption.
7.1 Role of UAM in modern transportation system
In the literature, many research works and reports have positioned UAM as a viable solution for alleviating ground traffic congestion. Consequently, it seems reasonable to investigate the UAM infrastructure planning and operational management problems based on the commuting or daily mobility scenarios (
Rimjha et al., 2021;
Willey and Salmon, 2021;
Waltz et al., 2024). Theoretically, it is no doubt that traffic congestion can be mitigated if some travel demand can be shifted to the urban airspace. However, given the limited payload capacity of eVTOLs and the constraints of low-altitude airspace management, whether such a shift can genuinely alleviate ground congestion remains questionable. In addition, the construction of high-capacity vertiports in dense urban cores also poses difficulties, including available land, high real estate costs, zoning restrictions, and potential community opposition due to noise and visual impact. More importantly, high ticket prices of UAM service will inevitably restrict its accessibility to only the wealthiest commuters, rather than serving as a practical congestion-relief solution for the public. Notably, despite the rapid development of many eVTOL companies worldwide, no trial operations have been conducted specifically targeting daily commuting scenarios. Although many studies have modeled hypothetical commuting scenarios at various scales to test the performance of UAM systems, quantitative analyses aiming to evaluate UAM’s potential for traffic congestion mitigation remain limited and inconclusive. Therefore, future research should prioritize the demonstration of the actual impact of UAM operations on ground traffic through carefully designed pilot programs that integrate real-world operational data with advanced traffic simulation models.
7.2 Business model of UAM service
UAM business models can be broadly categorized into three main types with different operational frameworks (
Pons-Prats et al., 2022). The first model positions UAM as a public transit service, conceptually similar to metro and bus systems, which provides scheduled operations along fixed aerial routes with eVTOL aircraft serving major transportation hubs at relatively affordable fares. The second model positions UAM as a point-to-point on-demand solution through app-based booking systems that provide flexible routing and immediate availability. The third model positions UAM as an exclusive premium service that only caters specifically to high-income passengers who require customized and time-sensitive transportation with luxury amenities and maximum privacy. Table 4 presents a comparative analysis of the three UAM business models.
Current research on UAM business models remains relatively underdeveloped. How to design reliable, scalable, and economically viable models that account for regulatory frameworks, infrastructure requirements, and passenger needs remains a pressing issue for both academia and industry.
7.3 UAM and transport divide
The transport divide (also known as transport exclusion, transport disadvantage, transport deprivation, transportation divide, and mobility divide) refers to the systemic disparities in mobility access and quality between different socioeconomic groups within urban populations (
Kemp and Stephani, 2015;
UN-HABITAT, 2010). This divide can lead to reduced access to essential services, limited economic opportunities, and social isolation for disadvantaged groups. For instance, residents in low-income suburban areas with infrequent or unreliable public transit may struggle to reach job centers located in the city center, which limits their employment prospects compared to those living in well-connected neighborhoods. Similarly, an elderly individual living in a rural area with no suitable transportation options might find it extremely difficult and costly to travel to a specialist appointment at a hospital located several miles away.
As a high-cost and technology-driven solution, UAM risks exacerbating the transport divide by predominantly serving high-income passengers and urban centers and leaving low-income populations and rural areas with limited or even no low-altitude air mobility benefits. Without effective equity measures such as public subsidy, this could lead to a two-tiered mobility system, where privileged groups gain time-saving aerial access while marginalized communities remain constrained to increasingly underfunded ground transportation systems. Hence, future research should focus on exploring the impacts of UAM on different socioeconomic groups and geographical areas to identify and mitigate factors that may lead to transport divide.
8 Conclusions and future research directions
The rapid development of UAM in recent years has far exceeded our expectations. Just over a decade ago, low-altitude air travel was merely an interesting idea found in science fiction movies. Since the concept of UAM was first proposed in 2016, the utilization of low-altitude airspace for urban transportation has attracted considerable attention in both academia and industry. People believe that UAM will become the next transformative urban transportation solution since the emergence of steam-powered public buses in 1833 and the subway system in 1863. From prototype testing to regulatory advancements and pilot programs, the past five years have seen UAM evolve from an initial concept to a reality. In this paper, we conducted a comprehensive review for UAM-related research topics from 2020 to 2025, including infrastructure planning, UAM operations management, and various societal issues. In addition to research papers, we also consider government and institutional reports as well as news articles from mainstream media. Compared to other reviews that focus on analyzing specific research methods, this paper aims to provide a more comprehensive review from a systems engineering perspective, examining the research problems involved in the entire UAM system. Unquestionably, UAM is becoming a popular research topic. While current studies often draw on principles from ground transportation modes or rely on various assumptions, it can be predicted that this research field will be significantly expanded with the anticipated launch of commercial UAM operations. Through the current research progress summarized in this review, we can glean some insights into promising directions for future UAM research.
As we discussed before, infrastructure planning, particularly the design and placement of vertiports, forms the foundation of UAM operations. Therefore, it is essential to integrate the location solution with the unique operational characteristics of UAM. First, the location of emergency landing sites determines the reliability and operational resilience of UAM networks, which is influenced by factors such as demand distribution, route planning, and geographic constraints. How to effectively allocate these sites to ensure operational safety while avoiding resource inefficiency requires a carefully designed optimization framework that balances safety, accessibility, and cost considerations. Second, the deployment of vertiports and other supporting infrastructure is a multi-stage problem that must address both immediate operational needs and long-term network scalability. Each stage may have different objectives and practical considerations that need to be carefully balanced over time. Finally, the selection of vertiport locations should be integrated with first- and last-mile ground transportation networks. If the roads connecting the vertiports become congested, the efficiency of UAM services could be compromised and the operating capacity of the vertiport will rapidly reach its bottleneck. The integration of vertiports and other public transportation modes may alleviate the traffic congestion on first- and last-mile ground transportation networks. Nevertheless, the associated location selection is a multidimensional problem that needs further exploration to develop effective and scalable solutions in future research.
From the perspective of operations management, if the UAM market aligns with predicted trends, the future of low-altitude airspace is expected to become highly congested. In addition to conventional issues such as ATM and vertiport operations, it is also critical to prioritize safety considerations. Although some research works have focused on collision avoidance and emergency response issues, most existing studies still fail to address the systemic challenges emerging during large-scale UAM operations. For example, the emergency route re-planning for a large fleet of eVTOLs raises the question of centralized versus decentralized control. The former can produce better solutions but also demands high response speed. The latter has relatively lower computational burden but may result in managerial issues and reduce the operational efficiency. Another noteworthy aspect is the pricing of UAM services, which directly influences UAM’s role in the urban transportation system. Government subsidies and policy incentives can be formulated to accelerate market penetration by bridging the gap between early-stage high costs and mass-market affordability. For instance, in the early stages of EV adoption, many governments worldwide implemented tax credits, purchase rebates, and reduced registration fees to make EVs more financially attractive (
Li et al., 2023;
Shang et al., 2024). Additionally, investments in supporting infrastructure, such as charging networks, can help mitigate drivers’ range anxiety and improve consumer confidence (
Feng et al., 2024). These strategies offer valuable insights for UAM during its early adoption phase, and similar measures could be used to reduce barriers to mass-market penetration.
From the perspective of social acceptance, a notable area for research concerns the low-altitude aerophobia for both potential passengers and ground-level communities. Although aerophobia in commercial aviation has been well-studied, UAM-related aerophobia introduces several unique characteristics. If not adequately addressed, any incident involving UAM operations could trigger widespread social panic. Another important research direction is to develop effective mechanisms to avoid potential social inequalities. If UAM and eVTOL services only serve as exclusive transportation options for a small segment of society, the vision of a truly transformative and equitable urban mobility solution will lose its significance. Some of the potential research directions are summarized in Fig. 17.
In summary, the development and deployment of UAM systems is a multifaced and complex progress that involves multiple stakeholders and should be investigated from a systems engineering perspective. In this paper, we conducted a comprehensive review of key research issues related to UAM, offering insights from different sectors to highlight current progress and perspectives. We hope the findings presented in this paper can help researchers in this field better understand this field and identify pathways for future investigation.
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