Mobile Air Research Articles

Evaluation of collision detection and avoidance methods for urban air mobility through simulation

AbstractUrban Air Mobility is a new concept of regional aviation that has been growing in popularity as a solution to the issue of ever-increasing ground traffic. Electric vehicles with vertical take-off and landing capabilities are developed by numerous market companies as a result of the push toward environmentally sustainable aviation. The next stage in this development process would be to define the concept of operation of these conceptual aircraft and then to integrate them with the existing airspace once they are airborne. In addition to coordinating with conventional air traffic and other Urban Air Mobility vehicles, collision avoidance with uncooperative airspace users has to be addressed. Birds and drones of all sizes pose a serious risk to these low-flying aircraft. Innovative collision detection and avoidance techniques need to be employed due to the non-cooperative nature of these airspace users and different performance characteristics of Urban Air Mobility vehicles compared to classical fixed-wing aircraft. The aim of this study is to evaluate the concept of one such system by means of fast-time simulations. This system builds, similarly to the Airborne Collision Avoidance System, on safety envelopes and rule-based collision avoidance to prevent collisions with non-cooperative airspace members. The system is designed to work with all aircraft configurations used for Urban Air Mobility operations. To assess its influence on safety and capacity, different scenarios are modeled by varying parameters, such as intruder type, location, flight path. The parameters assessed are differences in flight time and closest point of approach with and without the collision avoidance system in place. Moreover, the influence of different configurations of Urban Air Mobility aircraft on these parameters is analyzed. The results show that the separation between the ownship and intruder is increased substantially which leads to safe operations at bearable delay costs.

An integrated supply chain network design for advanced air mobility aircraft manufacturing using stochastic optimization

An integrated supply chain network design for advanced air mobility aircraft manufacturing using stochastic optimization

Evaluation of the advanced air mobility potential for organ transplantation in Austria and Germany

Solid organ transplantation continues to be the only or most efficient therapeutic solution for several end-stage diseases. The success of such transplantation is largely dependent on the swift transportation of organs from donors to recipients, as Cold Ischemia Time (CIT) plays a critical role in determining the recipient’s medical outcome. This study explores the potential of Advanced Air Mobility (AAM) in the context of organ transplantation in Austria and Germany. AAM, in the healthcare sector, is associated with potential overall process time savings via air transportation, thereby reducing CIT. However, the application of AAM for organ transplantation has not yet been implemented in Europe. This study employs a Monte Carlo simulation to derive the trip length distributions for organ transplantation in Austria and Germany. By utilizing data from Eurotransplant (2018–2021) and ÖBIG (2017–2021), it was found that 48% of organ transports within Germany, and 80% of organ transports within Austria, fall within a trip length of less than 150 km. This distance is within the capabilities of today’s AAM technology. Anticipated time benefits of up to 30 min compared to ground-based transport can be expected. Furthermore, the optimization of the organ transport process, facilitated by AAM, promises greater potential for CIT reduction.

Commuter choice of UAM-friendly neighborhoods

Urban Air Mobility (UAM) which provides swift intra- and intercity transportation services has the potential to induce shifts in individuals’ commuting and residential decisions. It is anticipated that, in residential areas, UAM services would enhance accessibility for residents. An UAM-friendly neighborhood represents a novel, integrated neighborhood concept that provides the infrastructure and travel environment required to facilitate UAM services, thereby promoting sustainable neighborhood development and improving accessibility. To gain a deeper understanding of commuters’ choice behavior in UAM-friendly neighborhoods, we designed a stated choice experiment. Using data collected in Beijing city, we estimated a mixed logit model with interaction effects to identify the choice preferences of different people while capturing the unobserved preference heterogeneity. We found that individuals generally prefer to reside in such neighborhoods where the access distance to UAM vertiports is within one kilometer, the parking fee is either low (5 yuan/day) or free, the commuting time by UAT is 15 min, and drone window-docking delivery services are available. Households with high incomes (>400,000 yuan/year) and those owning a car are likely to adopt these novel neighborhoods. There is a varying degree of heterogeneity observed regarding residential location and distance to UAM vertiports among individuals in different age groups. Results of the elasticity analysis indicate that UAT commuting cost has the greatest impact on the likelihood of residing in UAM-friendly neighborhoods.

Wind of Change: Investigating Information Visualizations for Passengers and Residents' Perception of Automated Urban Air Mobility

Wind of Change: Investigating Information Visualizations for Passengers and Residents' Perception of Automated Urban Air Mobility

Application of Mind Map and TRIZ to an Advanced Air Mobility System for Post-Disaster Response

In this article, an Advanced Air Mobility (AAM) platform focused on search and rescue applications is discussed and analyzed from a systems thinking perspective. By applying two systems thinking tools, namely Mind Map and TRIZ, the strong interactions within the constituent parts that make up the system’s whole are examined with the aim of providing a comprehensive roadmap for a proposed Advanced Air Mobility Post-Disaster Response (AAMPDR) system. Furthermore, two problems are discussed to demonstrate the application of the TRIZ technique. The first is in regards to a clause in the AGL rule that could present operational risks to the AAM’s airframe, while the second relates to a potential conflict ensuing from the advent of the 5G C-band and its effect on the AAM altimetry. The resulting solutions to resolve these conflicts using this same technique are also discussed, firstly by taking into account the mean sea/water level as a reference for vertical height within the provisions of the Federal Aviation Regulation requirements, and secondly by applying segmentation of the mission profile as well as a multi-stage frequency designation for each segment depending on a threshold vertical distance. Finally, this study demonstrated that Mind Map and TRIZ can be effective techniques in the early stages of conceptual model development for an AAM system applied to post–disaster response. Furthermore, that the contradictions tool of TRIZ can also be utilized in resolving those potential conflicts identified in relation to the system of interest. To this end, this paper proposes the amendment of the current Part 107 rule to include the term Above Mean Sea (or Water) Level (AMS/WL), a critical yet missing piece of the system requirements that engineers should take into account in future AAM system designs.

Urban Air Mobility (UAM) in Türkiye: Evaluating Existing Aviation Laws and International Practices

Urban Air Mobility (UAM) has emerged as a solution to transport challenges such as traffic congestion, environmental impacts, and lack of adequate public transport systems in urban areas. As the interest in UAM objects such as electric vertical take-off and landing aircraft (eVTOL) is increasing, it is important to understand whether the current regulations are sufficient to address the sui generis difficulties of this brand new technology. This article examines the adequacy of Türkiye's current legal framework to ensure the safe, effective, and sustainable integration of UAM. This article analyses Türkiye's existing aviation legislation, in particular the Turkish Civil Aviation Law and the instructions issued by the Directorate General of Civil Aviation (DGCA) and examines their applicability to UAM. The article discusses various regulatory gaps such as the lack of standards specifically designed for UAM, inadequate safety, environmental and operational regulations, and unclear guidelines on airspace integration. The article also discusses various UAM regulations prepared by the International Civil Aviation Organisation (ICAO), the European Union Aviation Safety Agency (EASA), and the approaches of pioneer countries in this area, such as the US, Germany, and Japan. Through a comparative analysis, it demonstrates the key lessons learnt from these international practices and presents suggestions for improving Türkiye's regulatory environment. The study emphasises the need for targeted reforms, introduction of specific standards, and a new regulative framework to foster the successful integration of UAM. The findings aim to contribute to the establishment of a solid legal framework to ensure that Türkiye is prepared for the future of UAM.

Dual-Frequency Multi-Constellation Global Navigation Satellite System/Inertial Measurements Unit Tight Hybridization for Urban Air Mobility Applications

A global navigation satellite system (GNSS) for remotely piloted aircraft systems (RPASs) positioning is essential, thanks to the worldwide availability and continuity of this technology in the provision of positioning services. This makes the GNSS technology a critical element as malfunctions impacting on the determination of the position, velocity and timing (PVT) solution could determine safety issues. Such an aspect is particularly challenging in urban air mobility (UAM) scenarios, where low satellite visibility, multipath, radio frequency interference and cyber threats can dangerously affect the PVT solution. So, to meet integrity requirements, GNSS receiver measurements are augmented/fused with other aircraft sensors that can supply position and/or velocity information on the aircraft without relying on any other satellite and/or ground infrastructures. In this framework, in this paper, the algorithms of a hybrid navigation unit (HNU) for UAM applications are detailed, implementing a tightly coupled sensor fusion between a dual-frequency multi-constellation GNSS receiver, an inertial measurements unit and the barometric altitude from an air data computer. The implemented navigation algorithm is integrated with autonomous fault detection and exclusion of GPS/Galileo/BeiDou satellites and the estimation of navigation solution integrity/accuracy (i.e., protection level and figures of merit). In-flight tests were performed to validate the HNU functionalities demonstrating its effectiveness in UAM scenarios even in the presence of cyber threats. In detail, the navigation solution, compared with a real-time kinematic GPS receiver used as the reference centimetre-level position sensor, demonstrated good accuracy, with position errors below 15 m horizontally and 10 m vertically under nominal conditions (i.e., urban scenarios characterized by satellite low visibility and multipath). It continued to provide a valid navigation solution even in the presence of off-nominal events, such as spoofing attacks. The cyber threats were correctly detected and excluded by the system through the indication of the valid/not valid satellite measurements. However, the results indicate a need for fine-tuning the EKF to improve the estimation of figures of merit and protection levels associated to the navigation solution during the cyber-attacks. In contrast, solution accuracy and integrity indicators are well estimated in nominal conditions.

Machine Learning-Based Environment-Aware GNSS Integrity Monitoring for Urban Air Mobility

The increasing deployment of unmanned aerial vehicles (UAVs) in urban air mobility (UAM) necessitates robust Global Navigation Satellite System (GNSS) integrity monitoring that can adapt to the complexities of urban environments. The traditional integrity monitoring approaches struggle with the unique challenges posed by urban settings, such as frequent signal blockages, multipath reflections, and Non-Line-of-Sight (NLoS) receptions. This study introduces a novel machine learning-based GNSS integrity monitoring framework that incorporates environment recognition to create environment-specific error models. Using a comprehensive Hardware-in-the-Loop (HIL) simulation setup, extensive data were generated for suburban, urban, and urban canyon environments to train and validate the models. The proposed Natural Gradient Boosting Protection Level (NGB-PL) method, leveraging the uncertainty prediction capabilities of the NGB algorithm, demonstrated superior performance in estimating protection levels compared to the classical methods. The results indicated that environment-specific models significantly enhanced both accuracy and system availability, particularly in challenging urban scenarios. The integration of environment recognition into the integrity monitoring framework allows the dynamic adaptation to varying environmental conditions, thus substantially improving the reliability and safety of UAV operations in urban air mobility applications. This research offers a novel protection level (PL) estimation method and a framework tailored to GNSS integrity monitoring for UAM, which enhances the availability with narrower PL bound gaps without yielding higher integrity risks.

Urban Aviation: The Future Aerospace Transportation System for Intercity and Intracity Mobility

This review discusses the challenges of integrating emerging transportation technologies into existing urban environments, considering their impact on equity, sustainability, and urban design. The aim is to provide readers with strategic insights and policy recommendations for incorporating aerospace innovations into transportation systems. This narrative review draws on a wide range of publications, including books, journal articles, and industry reports, to examine the multifaceted aspects of urban aviation. The review explores the scales of aerospace transport, detailing the technologies enabling urban aviation, the necessary urban adaptations to support such a system, and the social and regulatory challenges of integrating urban air mobility into existing transportation networks. The research suggests that for urban air mobility to be successfully integrated into existing transportation systems, further research is needed on the social and regulatory implications, particularly regarding equitable access, sustainable practices, and community engagement.

Future Low-Cost Urban Air Quality Monitoring Networks: Insights from the EU’s AirHeritage Project

The last decade has seen a significant growth in the adoption of low-cost air quality monitoring systems (LCAQMSs), mostly driven by the need to overcome the spatial density limitations of traditional regulatory grade networks. However, urban air quality monitoring scenarios have proved extremely challenging for their operative deployment. In fact, these scenarios need pervasive, accurate, personalized monitoring solutions along with powerful data management technologies and targeted communications tools; otherwise, these scenarios can lead to a lack of stakeholder trust, awareness, and, consequently, environmental inequalities. The AirHeritage project, funded by the EU’s Urban Innovative Action (UIA) program, addressed these issues by integrating intelligent LCAQMSs with conventional monitoring systems and engaging the local community in multi-year measurement strategies. Its implementation allowed us to explore the benefits and limitations of citizen science approaches, the logistic and functional impacts of IoT infrastructures and calibration methodologies, and the integration of AI and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements and reporting. Similar research or operative projects have been implemented in the recent past, often focusing on a limited set of the involved challenges. Unfortunately, detailed reports as well as recorded and/or cured data are often not publicly available, thus limiting the development of the field. This work openly reports on the lessons learned and experiences from the AirHeritage project, including device accuracy variance, field recording assessments, and high-resolution mapping outcomes, aiming to guide future implementations in similar contexts and support repeatability as well as further research by delivering an open datalake. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, citizens, public authorities, and agencies, about effective strategies for deploying and utilizing LCAQMSs to enhance air quality monitoring and public awareness on this challenging urban environment issue.

Mamba-VNPS: A Visual Navigation and Positioning System with State-Selection Space

This study was designed to address the challenges of autonomous navigation facing UAVs in urban air mobility environments without GPS. Unlike traditional localization methods that rely heavily on GPS and pre-mapped routes, Mamba-VNPS leverages a self-supervised learning framework and advanced feature extraction techniques to achieve robust real-time localization without external signal dependence. The results show that Mamba-VNPS significantly outperforms traditional methods across multiple aspects, including localization error. These innovations provide a scalable and effective solution for UAV navigation, enhancing operational efficiency in complex spaces. This study highlights the urgent need for adaptive positioning systems in urban air mobility (UAM) and provides a methodology for future research on autonomous navigation technologies in both aerial and ground applications.

Fast-Time Simulations to Study the Capacity of a Traffic Network Aimed at Urban Air Mobility

This article investigates viable solutions to implement an Urban Air Mobility network in Milan, Italy, and analyzes its influence on the airspace capacity. The network comprises eight vertiports for passenger transport among two main airports in the area and the city using electric vertical take-off and landing aircraft (eVTOLs). A Fast-Time Simulation (FTS) model with the software AirTOp (Air Traffic Optimization) allowed the evaluation of the ideal capacity of the network by varying two configurations, which differ from each other in terms of the number of Final Approach and Takeoff areas (FATOs). The results show how it is possible to reach high hourly capacities (in the order of one hundred), thus allowing the use of the service for about 4% of the total passengers passing through the two airports during the reference day chosen for this study. However, the results are ideal due to the strong idealism of the system, which overlooks several factors, and they should be considered as the maximum limit that can be obtained. Despite this, the method presented in this article can also be adapted for other urban areas with high population densities. In addition, the use of a simulation tool of this type allows, in addition to a numerical analysis, a qualitative analysis of the network behavior in terms of traffic, thus highlighting the criticalities of the proposed systems.

Wireless Connectivity and Localization for Advanced Air Mobility Services

Wireless Connectivity and Localization for Advanced Air Mobility Services

Acoustic imaging of geometrically shielded sound sources using tailored Green's functions.

In light of the growing market of urban air mobility, it is crucial to accurately detect the stationary or moving noise sources within the complex scattering environments caused by aircraft structures such as airframes and engines. This study combines conventional and wavelet-based beamforming techniques with an acoustic scattering prediction method to develop an acoustic imaging approach that considers scattering effects. Tailored Green's function is numerically evaluated and used to compute the steering vectors and the specific delayed time used in those beamforming methods. By examining common scenarios where a scatterer is positioned between the source plane and the array plane, it is observed that beamforming in a scattering environment differs from that in free space, leading to improved resolution alongside scattering-induced side lobes. The effectiveness of the developed method is validated through numerical simulations and experimental studies, confirming its improved ability to localize both stationary and rotating sound sources in a shielded environment. This advancement offers effective techniques for acoustic measurement and fault monitoring in the presence of structural scatterers.

Investigating the Need for Urban Air Mobility in Tehran City

The increase in urbanization has led to the creation of dense population in urban areas, along with economic development and the increase in vehicles, which has led to an increase in demand and consequently an increase in many challenges regarding mobility and infrastructure. Solving these challenges or reducing the effects of these challenges can have significant effects on people's daily lives. Various solutions have always been proposed to solve these challenges, some of which have been successful and some of which have not. In the city of Tehran, too, challenges have arisen due to the rapid growth of urbanization, population, and vehicles, and solutions have been proposed to solve these challenges or improve the conditions, but due to the current conditions in Tehran, these solutions have not been able to appear as successful as they should be. In this paper, by examining the conditions of Tehran in terms of noise pollution, energy and fuel consumption, air pollution, traffic conditions, public and road transportation, it is proved that Tehran needs a new mode of transportation. According to today's needs of Tehran, this new mode of transportation can be an urban air mobility (UAM) that can be used in areas such as passenger and goods transportation. The presence of this mode of transportation in the transportation system of Tehran, in addition to improving the level of transportation of this city, helps to improve and even solve the challenges of today's transportation in Tehran, such as the high noise pollution of this city.

Urban Air Mobility Passengers’ Profiling: Evidence from Milan Airports, Italy

Urban air mobility (UAM) is expected to offer new travel options for passengers to and from airports in the near future, despite uncertainties associated with regulatory issues, environmental concerns, and societal impacts. This paper analyzes the socioeconomic and behavioral factors that could influence users’ modal choices (including UAM services) for accessing and egressing airports. Using revealed and stated preference data collected at Milan airports (Italy), mixed logit and hybrid choice modeling specifications are estimated and compared with profile potential UAM passengers. Our findings suggest that the level of service, socioeconomic factors, and trip-related variables explain passengers’ choices better than latent traits such as fear of flying, propensity for technological advances, and expectations about the safety of UAM services. In other words, the additional complexity of hybrid choice modeling is not justified by the slight gain in likelihood compared with the estimated mixed logit model. The results also indicate that high-income individuals traveling for business purposes are the most likely demand segment to use UAM services, at least initially. Moreover, highly educated individuals and employees who have their travel expenses reimbursed for work trips are less likely to choose UAM services for airport access or egress, preferring traditional ground taxis.

An estimation method for vision-based autonomous landing system for fixed wing aircraft

In this paper, we propose a vision-based estimation method for autonomous landing of fixed-wing aircraft for Advanced Air Mobility. The concept of autonomous flight with minimal human intervention has gained significant interest with a particular focus on autonomous landing. The goal is to overcome the limitations of existing instrument landing systems and reduce reliance on GNSS during aircraft landing. The proposed system leverages the following techniques for high-performance and real-time operations in various real-world environments and during all stages of landing. A deep learning segmentation model was directly learned, created, and used for robust runway recognition performance against environmental changes around the runway. Algorithms were designed to adapt to different flight stages considering the varying information offered by image data when the aircraft is in mid-air and on the ground. The relative lateral position from the aircraft to the runway was estimated using bird’s-eye-view conversion and inverse projection techniques instead of conventional perspective-n-point methods for reducing the recognition error occurring from the conversion between 2D image and 3D world. Finally, the mixed-precision technique was used for the segmentation model to improve inference speed and ensure real-time operation in real-world deployment. Estimation stability and reliability were improved by using a Kalman Filter to cope with sensor uncertainties caused by the real-world flight environment. Consequently, we show that the average error in the lateral position estimation by the proposed method is comparable to the accuracy of a single GNSS and demonstrate successful autonomous landing of our test aircraft with a set of flight tests.

The Overview of Vertical Take-Off and Landing Technology

Vertical takeoff and landing (VTOL) technology is garnering significant attention in the aviation industry due to its distinct benefits and wide range of potential applications. A long runway is not necessary when using VTOL technology, which allows aircraft to take off and land vertically straight from the ground. Air mobility in cities, military activities, and emergency response are just a few of the areas where this technology is beneficial. This essay will provide an overview of the development, application, and future of vertical takeoff and landing technology. The technologys operating principles, advantages and limitations will also be explored. Overall, VTOL technology offers a tremendous leap in aircraft technology, with numerous possible uses. Even though there are still difficulties, more research and development will probably result in improvements and broader use.

U-Space Contingency Management Based on Enhanced Mission Description

Loss of communication, low battery, or bad weather conditions (like high-speed wind) are currently managed by performing a return to launch (RTL) point maneuver. However, the execution of this procedure can pose a safety threat since it has not been considered within the mission planning process. This work proposes an advanced management of contingency events based on the integration of a new U-space service that enhances mission description. The proposed new service, deeply linked to demand capacity balance and strategic deconfliction services, assigns alternative safe landing spots by analyzing the planned mission. Two potential solutions are characterized (distinguished primarily by the number of contingency vertiports assigned): contingency management based on the assignment of a single alternative vertiport to each mission (static) or the allocation of a set of different contingency vertiports that are valid during certain time intervals. It is proven that this enhanced mission planning could ensure that U-space volumes operate in an ultra-safe system conditions while facing these unforeseen events, highlighting its importance in high-risk scenarios like urban air mobility deployments.