Learning an Urban Air Mobility Encounter Model from Expert Preferences

The proliferation of unmanned aerial vehicles (UAVs) has driven the emergence of urban air mobility (UAM) as a solution to alleviate the increasing demand for UAVs applications in various domains. The concept of UAM envisions a future where UAVs play a pivotal role in short-distance transportation, delivery services, surveillance, emergency rescue, and more. However, the rapid growth of UAVs poses significant challenges arising from the need to ensure the safe coexistence of UAVs with other manned/unmanned aerial vehicles. To ensure the safe integration of UAVs into low-altitude urban airspace and support high-density on-demand mobility, this research focuses on handling the safety-centric challenges related to UAV collision risk assessment, obstacle avoidance, and conflict resolution in complex urban environments.
\nOne of the main challenges is the intrusion of UAVs into airport runways. Airports serve as critical hubs for civil aircraft takeoff and landing operations. However, the increasing presence of UAVs has raised concerns about intruding into airports, leading to flight delays and temporary runway closures. To quantify the potential interference of UAVs on civil aircraft, a collision-course based trajectory planning model is proposed to evaluate the collision risk between manned civil aircraft and intruding UAVs. In this risk assessment model, the trajectory of the intruding UAV is formulated using a collision-course concept, taking into account the limited trajectory information available about intruding UAVs. The planned trajectory of the UAVs is then used to predict its relative position concerning civil aircraft. To account for the possible disturbances of the relative distance, a stochastic position prediction model based on Brownian motion is developed. The collision risk is assessed based on this stochastic kinematic model, providing a quantitative measure of the potential collisions. The proposed model is validated through extensive simulations involving different UAV initial positions, position updates, and different sizes of collision zone tests, as well as comparative tests with the Monte-Carlo algorithm, demonstrating its robustness in assessing the collision risk of the airport restricted area. To facilitate the application, the model is finally used to develop a platform to generate runway heatmaps, accounting for airport runway risk distributions. 
\nAnother safety-centric challenge is ensuring autonomous obstacle avoidance and conflict resolution of UAVs. To enable UAV autonomous safe operations in uncontrolled urban low-altitude airspace, a comprehensive collision-free path planning framework is developed to address the avoidance of both static obstacles and dynamic threats. Firstly, to handle static obstacles, a novel algorithm of 3D voxel jump point research is introduced to generate a global reference path for UAV navigation to avoid static obstacles, particularly for a free flight at different altitudes. Additionally, to optimize the reference path for specific mission requirements, techniques such as trajectory de-diagonalization, reconstruction, and smoothness are proposed to reduce the risk of static collisions, shorten the fly range, and enable UAVs to negotiate turns more efficiently. Secondly, real-time conflict resolution actions based on the Markov decision process are developed to avoid local dynamic threats encountered along the optimized desired path. This allows the host UAV to dynamically adjust its course to a resolution trajectory while maintaining its planned speed without hovering to avoid the potential collision with the approaching intruders. By avoiding near mid-air collisions (NMAC) and preventing the UAV from hovering, the proposed method ensures the timely completion of UAV missions. Simulation results demonstrate that the developed method successfully achieves UAV autonomous global path planning and local real-time conflict resolution in complex urban low-altitude environments, thereby avoiding both static obstacles and dynamic threats. 
\nMoreover, to bridge the research gap of UAV hard conflict resolution in mitigating NMAC risks arising from local dynamic threats, a novel situational NMAC risk assessment approach is developed by integrating the conditional random field (CRF) algorithm with safety metrics and conflict resolution performance to facilitate UAV tiered aerial passage operations. To improve UAV operating environments in urban airspace, a concept of tiered aerial passages is first designed to provide a practical urban airspace planning scheme that addresses UAV heterogeneity and optimizes the utilization of urban airspace. For UAV tiered aerial passage operations, a situational NMAC risk assessment module coupled with a conflict resolution decision-making module is formulated, enabling the host UAV to evaluate and respond to real-time conflicts, ensuring avoidance of potential collisions. To assess NMAC risks, a general risk assessment model is proposed based on the CRF algorithm, considering UAV safety metrics and resolution performance. Then the overtaking, approaching head-on, and converging UAV encounters are analyzed, and situational risk potential scores are created using the Gaussian kernel function in the CRF algorithm, considering advisory, caution, and warning risk alert levels. To resolve conflict, acceptable, tolerable, and unacceptable scenarios are proposed to enhance the flexibility and personalization of the resolution decision-making. The proposed scheme is validated by simulating geometric encounter situations and comparative tests with the previous hard resolution technique. The results indicate that the proposed method outperforms UAV NMAC risk assessment and conflict resolution. Even in the most dangerous unacceptable resolution decision-making scenarios across three conflict encounters, the proposed algorithm achieves NMAC rates of 0.036, 0.070, and 0.043, which are lower than the corresponding NMAC rates associated with the hard resolution approach. Together with the acceptable and tolerable scenarios, the proposed negotiation resolution effectively tailors different risk requirements to accommodate diverse UAV missions. 
\nWith a primary focus on ensuring the safety of the UAM architecture, this research endeavors to assess UAV NMAC risks and efficiently manage potential conflicts. The proposed work are thoroughly validated to demonstrate their effectiveness in real-world scenarios. As a result, this study significantly contributes to the establishment of a robust UAM architecture, facilitating the realization of safe and reliable UAM.

Urban air mobility is gaining interest as the need for On Demand Mobility in today's congested traffic is becoming high in metropolitan areas. Urban Air Mobility (UAM) is envisioned as a concept to transport passengers and cargo safely and efficiently using innovative aircraft in the urban areas. It is expected to improve mobility for the general public, decongest road traffic, reduce transport time and reduce the strain on existing public transport networks. There exist several challenges to Urban Air Mobility (UAM) such as integration of procedures with airspace and the airport, noise levels that are acceptable to the general public, public safety, public acceptance, vehicle certification, and more. Most of the research in the United States and European skies (DLR - German Aerospace Center) related to urban areas has focused on small UAS (Unmanned Aircraft Systems) flights (NASA's UTM (UAS Traffic Management) research) and their integration with the airspace and building safe operations in densely populated areas. Previous studies on UAM have focused on fast time simulations of the routes that are separated via a separation service and network of routes. Similarly, research in Europe has focused on the approach profile for these innovative aircraft, vertiports and battery life among others. UAM as a part of the On-Demand Mobility effort has provided some guidelines for operations as shown below: Does not require additional ATC (Air Traffic Control) infrastructure; Does not impose additional workload on ATC; Does not restrict operations of traditional airspace users; Will meet appropriate safety thresholds and requirements; Will prioritize operational scalability; Will allow flexibility where possible and structure where necessary. This paper explores potential routes and procedures in a Human-In-The-Loop (HITL) experiment that could be applied in the near-term to allow integration of UAM flights into the airspace as well as a large airport. The airspace that was explored was Dallas Fort Worth (DFW) airspace managed by the DFW East Tower in South Flow only. In addition, Dallas Love Field (DAL) and Addison (ADS) airspace were also part of the testbed. The initial set of routes investigated in this study were published helicopter routes in the DFW area. Figure 1 shows class B airspace in DFW area and the origin/destination city pairs where UAM flights flew along with helicopter routes shown in blue. The research focused on exploring procedures for integrating UAM flights into Class Bravo and Class Delta airspace. Three different communication procedures, evaluated with three different levels of UAM traffic, are shown in Table 1. The current day routes were evaluated with current day communication procedures were explored as the first condition. The current day routes were also evaluated in the second condition with reduced communications, which was assumed due to the presence of a Letter Of Agreement (LOA). The purpose of the LOA was to reduce the verbiage associated with pilots getting clearance to Class B airspace from the controllers, pre-assigning beacons codes to the UAM flights, separate routes by assigning altitudes and speeds to flights going in any one direction. Flights were expected to automatically change frequency when exiting Class B airspace, thus transition points for entry and exit points were also specified in the LOA.

ABSTRACTA state-of-the-art review of all the developments, standards and regulations associated with the use of major unmanned aircraft systems under development is presented. Requirements and constraints are identified by evaluating technologies specific to urban air mobility, considering equivalent levels of safety required by current and future civil aviation standards. Strategies, technologies and lessons learnt from remotely piloted aviation and novel unmanned traffic management systems are taken as the starting point to assess operational scenarios for autonomous urban air mobility.

Urban Air Mobility (UAM) systems offer a three-dimensional transportation alternative by using low-altitude airspace, with the potential to reduce travel times and improve access to mobility in regions underserved by current transportation systems. To support efficient design and operation of UAM systems, we develop an integrated optimization framework in response to three interrelated challenges: (i) land use, aeronautical feasibility, community acceptance and other factors that restrict the number of potential locations for vertiports, (ii) bidirectional demand–supply interaction that needs to be considered, as the level of service influences demand for UAM and operators adjust the level of service in response to demand, and (iii) strong interactions between strategic decisions on the distribution of ground infrastructure, tactical decisions on eVTOL fleet size and operational decisions on dispatching and repositioning. Analyzing the decisions in isolation can lead to poor estimates of the overall system performance. The framework consists of (1) a knock-off criteria analysis model for the identification of a realistic set of candidate locations for vertiports, (2) integer programming models in which strategic, tactical and operational decision levels are modeled, and (3) pre-processing techniques to generate near-optimal solutions for real-world instances. By applying the framework in a large-scale real-world setting in the Île-de-France region, we demonstrate complex interactions between strategic, tactical, and operational decision levels and customer demand, revealing various trade-offs between operator profit and traveler generalized travel costs. • Provide realistic candidate vertiports in the Île-de-France region using knock-off criteria screening. • Integrate vertiport location selection with eVTOL fleet sizing and operations and demand interaction. • Identify non-linear trade-offs between operator profit and user generalized travel costs. • Conclusions on the economic viability of UAM operations. • Identification of UAM network structures with distinct vertiport roles.

The scalability of the current air traffic control system, the availability of aviation ground infrastructure, and the acceptability of aircraft noise to local communities have been identified as three key operational constraints that may limit the implementation or growth of Urban Air Mobility (UAM) systems.This paper identifies the primary mechanisms through which each constraint emerges to limit the number of UAM operations in an area (i.e. the scale of the service).Technical, ecosystem, or operational factors that influence each of the mechanisms are also identified.Interdependencies between the constraints are shown.Potential approaches to reduce constraint severity through adjustments to the mechanisms are introduced.Finally, an effort is made to characterize the severity of each operational constraint as a function of the density of UAM operations in a region of interest.To this end, a measure of severity is proposed for each constraint.This measure is used to notionally display how the severity of the constraint responds to UAM scaling, and to identify scenarios where efforts to relieve the constraint are most effective.The overall purpose of this paper is to provide an abstraction of the workings of the key UAM operational constraints so that researchers, developers, and practitioners may guide their efforts to mitigation pathways that are most likely to increase achievable UAM system scale.U 2 American Institute of Aeronautics and Astronautics perceive to degrade their quality of life and enjoyment of their property.Local governments may use zoning or building codes to limit or prohibit aviation infrastructure development or operations.Finally, congressional representatives may compel the FAA to change ATC procedures to reduce noise, as was the case in the Los Angeles Residential Helicopter Noise Relief Act of 2013 [4].While community acceptance of UAM activities may be influenced by numerous factors including privacy, viewshed, pollution, safety, and equity, aircraft noise has dominated recent public discourse and action and represents a key constraint for UAM operations.However, the successful implementation of helicopter-based UAM operations in São Paulo, as well as the large private and charter helicopter operations in Moscow and Mumbai, indicate that local values and expectations significantly influence the actual severity of this constraint.U.S. and European communities may exhibit increased sensitivity to aircraft noise compared to other potential UAM markets.These three operating constraints are of keen interest to researchers, potential operators, and transportation planners as they dictate if a UAM system may serve a few hundred customers per day or tens of thousands of customers per day.The contribution of this research is significant because it will support the estimation of achievable UAM system scale based upon local factors and the ecosystem of the city in which it is implemented.Furthermore, this work may support the evaluation of how potential design and operating decisions may increase system scale.

Urban Air Mobility (UAM) is a system for passenger and air cargo transportation within an urban area. It includes small package delivery and other urban unmanned aerial systems (UAS) and supports a mix of onboard piloted, ground-piloted and increasingly autonomous operations. UAM is developing rapidly due to advances in technology. Several aerospace and vehicle manufacturers are developing automated aerial vehicle and piloted aerial vehicle prototypes, and pilot projects are underway in Dubai and planned for Dallas and Los Angeles in the early 2020s. The UAM market is broad and includes potential applications such as air taxi, personal commuting, air ambulance, and law enforcement. Due to the recent emergence of this technology, there has been little research into the potentially significant weather impacts on safety, cost, and efficiency of UAM operations and vehicles.Conducted as part of a comprehensive UAM market assessment, this research identifies potential key weather barriers to UAM due to a variety of weather conditions and public perception of flying in adverse weather. To characterize challenging weather conditions, a comprehensive seasonal and diurnal climatology was generated based on historical observations across anticipated UAM operational altitudes (surface – 5000 ft AGL) at ten focus urban areas in the United States. Weather related societal barriers to UAM were evaluated through a large general population survey where respondents were asked about their views regarding flying in a UAM vehicle amid various adverse weather conditions. Regional variability in weather conditions and potential barriers were also evaluated and will be described.

Nowadays, there is an increase in the demand for optimized services in urban environments. However, ground transportation in big urban centers has been facing challenges for many years (e.g., resilience and congestion) and new paradigms have been proposed, such as the Urban Air Mobility (UAM) concept. UAM aims to enhance the urban transportation system using manned and unmanned aerial vehicles (i.e., Electric Vertical Takeoff and Landing - eVTOL - vehicles). Although UAM offers many benefits (e.g., cost reduction and increase in transportation capacity), many challenges need to be faced to enable safe and efficient operations. Furthermore, trajectory planning is challenging in the National Airspace System (NAS) and UAM operations due to several factors. Finally, new initiatives concerning UAM trajectory planning can be accelerated with the support of an automatic what-if platform capable of evaluating trajectories feasibility and efficiency. This research aims to propose a simulation platform for enabling trajectory evaluation in UAM operations. This platform, named Trajectory-Based Urban Air Mobility Simulator (TUS), focuses on simulating trajectories in the urban aerial environment. TUS enables users to test new UAM algorithms (e.g., flow management strategies, real-time evaluation of maneuvers effectiveness, airspace configurations) and simulate both manned and unmanned vehicles. Furthermore, TUS operation relies on a set of inputs and evaluates the trajectories generated from efficiency and safety perspectives. This process is performed using a Discrete Event Simulation (DES) approach. The experiments performed showed that TUS can perform a realistic evaluation of UAM trajectories and can be effortlessly used to simulate hundreds of scenarios.

With new aviation market entrants such as Urban Air Mobility (UAM) vehicles, the role aviation will take in seamless, end-to-end multimodal transportation is evolving. Travelers will likely be able to request on-demand, point-to-point transportation through air taxis in the not-to-distant future. Previous multimodal research efforts have focused on surface urban mobility, where multiple modes of ground transportation compete with and complement each other, ignoring the growing role that aviation will play going forward. Existing public transportation data exchange models, tailored for their respective systems, likewise, have not yet accounted for this looming transportation transformation nor for widespread multimodal end-to-end, seamless transporting. To date, the FAA has succeeded in establishing a robust data exchange architecture to support traditional air transportation, but to facilitate this evolution of the public airspace system with respect to UAM and other emerging air vehicle systems, new and revised data exchange models are necessary. Existing data exchange models in need of revision include the International Civil Aviation Organization's (ICAO) Flight Information Exchange Model (FIXM) and the General Transit Feed Specification (GTFS) [2], [3]. New data exchange models in need of creation include the Passenger Information Exchange Model (PIXM), the Operation Information Exchange Model (OIXM), and Vehicle Information Exchange Model (VIXM) [1]. The research here explored these data models, identifying and defining preliminary conceptual data elements necessary to support seamless, end-to-end mobility. The conceptual model herein proposed is holistic and considers all modes of transportation – walk, car, bus, rail, boat, air, etc. - and looks to incorporate the most promising transportation data exchange models from among these transportation systems.A realistic multimodal travel scenario subject to disruptive events (such as severe weather) was developed for the purpose of identifying the necessary exchange of data to reduce the impact of the disruptive events on the traveler. This work helped inform the next steps in the project, the definition of multimodal data exchange models and the development of a corresponding multimodal transportation conceptual data model. The scenario includes Urban Air Mobility (UAM) vehicles that are intended to serve as short haul providers operating in a congested urban metro environment to bypass surface traffic congestion. New aviation market entrants, such as UAM, will likely not operate entirely within a traditional gate to gate model and are eventually likely to use a model similar to on-demand surface transportation such as ride share. Uber Elevate has already been proposing this type of application for their future air taxis [4]. Accommodating these new aviation market entrants will require further extensions to the FIXM (a second package for Unmanned Aircraft System (UAS) is already planned by the FIXM committee), adoption and enhancement of existing industry data exchange models, and entirely new data models. GTFS is the industry-leading and international de facto public transportation data exchange standard and has an extension called "flex" for supporting on-demand mobility, though has been limited to surface applications thus far [3], [5]. Alongside FIXM and GTFS, new models are necessary to facilitate seamless, end-to-end mobility. Proposed models include the Vehicle Information Exchange Model (VIXM), the Passenger Information Exchange Model (PIXM), and the Operator Information Exchange Model (OIXM) [1].This paper serves as an initial exploration of a data exchange model for future of transportation. The authors envision a future where a traveler can easily plan, dynamically re-plan, and track the real-time progress of a multimodal trip from the convenience of a smartphone application. The authors include a description of a future smartphone application to help illustrate the concept (Section 5). Section 6 provides a brief history of multimodal data exchange initiatives. Section 7 includes a brief discussion of next steps and recommendations for continued research.

The introduction of unmanned aircraft systems into various domains of civil aviation led to the necessity to develop suitable integration concepts to coordinate flight movements of manned and unmanned aircraft especially regarding surface operations at civil airports. These remotely piloted or automatic / autonomous unmanned aircraft do not have the same capabilities as manned aircraft. However, to achieve a wide commercial success, they will have to use the same infrastructure. Air traffic control has to maintain a safe, orderly and expeditious flow of air traffic, considering this new mixed traffic constellation. In order to do so, new operational procedures were defined. Within the scope of the SESAR 2020 project `Surface Management Operations' (SuMO), a procedural concept for ground movements of unmanned aircraft together with manned aircraft has been developed and evaluated in gaming sessions. This concept introduces so-called segmented standard taxi routes as a first and easy solution to enable mixed traffic while maintaining the same level of safety and very low system requirements for unmanned aircraft systems. In 2017, this concept was successfully validated in a dedicated workshop with operational experts, air traffic controller, remote and conventional pilots. The results of this evaluation have been published at the 37th Digital Avionics Systems Conference in September 2018. Based on this success, a fast-time simulation has been conducted in the beginning of 2019 to investigate quantitatively the operational performance of this solution in terms of the key performance areas capacity, efficiency and environmental impact. According to project objectives, the simulation scenarios were set up using as example the international airport of Stuttgart. Towing operations were used as a baseline scenario for RPAS ground movements. Selected performance parameters were then compared with those being calculated for the application of the segmented standard taxi route procedure in the solution scenario. The share of remotely piloted aircraft systems varied between 0% and 50% of the whole traffic. This paper provides a detailed description of the setup of this fast-time simulation, conducted simulation runs, defined metrics and results. In addition, these results are correlated with the recently published outcomes of the validation workshop of 2017. The paper closes with a summary and an outlook.

The purpose of this study is to explore how trust in and the service quality of urban air mobility (UAM) relate to the user acceptance of UAM. We hypothesized that trust directly influences the attitude and intention to use UAM, while service quality factors affect its perceived usefulness and ease of use. A survey data of 450 respondents were analysed by using a partial least squares structural equation model. The results show that trust positively influences the intention to use UAM, and safety perception contributes the most to UAM’s trustworthiness. In addition, transport service quality factors (i.e., time-saving, availability, flight comfort, and perceived cost) significantly explained the perceived usefulness and/or ease of use. Path coefficients of the structural model indicate that trust has a greater impact on the user's attitude toward UAM than perceived usefulness. The results of this study contribute to increasing the early user adoption of UAM.

Urban air mobility: A comprehensive review and comparative analysis with autonomous and electric ground transportation for informing future research

Urban Air Mobility (UAM) or Advanced Air Mobility (AAM) is a concept aerial transportation mode being designed for intracity transport of passengers and cargo utilizing autonomous electric vehicles capable of Vertical Take-Off and Landing (VTOL) from dense and congested areas. Airport ground access trips could be among the early adopters of UAM because of the high customer willingness to pay, and substantial time-savings for long-distance or significantly congested access trips. This study aims to estimate demand for UAM in the airport ground access segment of Los Angeles International Airport (LAX). Travel behavior is derived from the airport passenger survey 2019 provided by Los Angeles World Airports (LAWA). A mixed logit model captures the mode-choice behavior that is later modified to include UAM. Total daily originating passenger trips are estimated from the T-100 database. The calibrated model is then applied to calculate the UAM demand. Utilizing the developed UAM demand estimation framework, a feasibility analysis is performed through a series of sensitivity analyses with respect to UAM passenger cost per mile (CPM) and UAM network size (number of vertiports). Furthermore, the Also, UAM demand in specific high-demand corridors (according to the ground access traffic) is analyzed. UAM could capture an estimated 3.6% market share in airport access trips to/from LAX at $2.00 UAM cost per passenger mile, assuming 2.4 passengers per flight (additional to $15 base cost per passenger and $20 landing cost per flight).

국토교통부와 산업통상부는 2019년 9월 “신개념 항공교통수단으로 활용될 미래형 ‘개인용 비행체(PAV: Personal Air Vehicle)’의 개발 및 교통산업 활성화를 위한 민관 합동 발전전략협의체(이하 ‘협의체’라 한다)를 구축 운영한다.”고 밝힌바 있다. 이 협의체는 항공, 자동차, 배터리, 전기 전자, 교통서비스, 정비 인프라 등 다양한 분야의 산업전문가, 학자 및 연구자가 ‘개인용 비행체(PAV)’ 산업 발전을 위해 공동의 노력을 기울임과 동시에 향후 핵심기술의 개발 및 국제공동개발 지원, 산업 생태계 조성 및 전문인력 양성, 성능 및 품질 향상지원 및 국제표준, 민군 협력 등 ‘개인용 비행체(PAV)’의 보급 등 관련 서비스산업 등의 활성화 방안에 대한 검토를 수행하게 된다. 현대자동차는 2020년 1월 7일 개최된 ‘국제전자제품박람회2020(CES 2020: Consumer Electronics Show 2020)’에서 ‘개인용 비행체(PAV)’의 컨셉트 모델 ‘S-A1’을 공개하면서, 이와 함께 현대자동차가 구상하는 ‘도심항공모빌리티(UAM: Urban Air Mobility)’ 체계를 함께 공개한 바 있다. ‘도심항공모빌리티(UAM)’은 ‘개인용 비행체(PAV)’를 이용하여 이용자들이 도심지 내에서 지상의 교통정체에서 자유롭게 이동할 수 있도록 하고, ‘모빌리티 환승거점(HUB)’를 기반으로 착륙 이후에는 도심지내 주요 시설로 바로 이동할 수 있는 미래 모빌리티 생태계를 구축하고 2028년 그 상용화를 목표로 하고 있다. 이와 같이 정부(국토교통부, 산업통상자원부)나 기업(현대자동차 등)에서 발표한 전략을 살펴보면 미래의 도심지내 교통수단은 지상에는 ‘자율주행자동차’가 달리고, 공중에는 ‘개인용 비행체(PAV)’가 날아다니는 모습을 향후 10년 이내에 현실화될 것이 기대된다 할 것이다. 다만, ‘도심항공모빌리티(UAM)’ 체계가 ‘개인용 비행체(PAV)’를 기반으로 한다는 점에서 항공, 전자, 전기, 통신, 정비 등 관련 기술이나 환승거점(HUB) 등과 같은 시설의 구축이 매우 중요하다 할 것이지만, 최우선시 되어야 하는 것은 이러한 ‘개인용 비행체(PAV)’가 자유롭게 이동할 수 있는 공간을 어떻게 확보할 것인지에 대한 검토라 할 것이다. ‘자율주행자동차’의 경우에는 기존 도로 위에서 이동하면 될 것이지만 ‘개인용 비행체(PAV)’는 지상이 아닌 공중을 비행한다는 점에서 기존 도로의 이용이 어렵기 때문이다. 만약 이 에 대한 부분이 우선 해결되지 못한다면 향후 ‘도심항공모빌리티(UAM)’ 체계의 상용화는 어려울 것이다. 이에 본 논문은 ‘도심항공모빌리티(UAM)’ 체계의 구축 및 그 상용화를 위한 핵심장치인 ‘개인용 비행체(PAV)’의 상용화를 위해 구축되어야 할 시설 및 도심지내 그 이동 공간 에 대한 검토를 통해 ‘개인용 비행체(PAV)’의 도심지내 운영에 관한 법적쟁점을 제시하고 그 개선방안에 관한 법적 검토를 수행하고자 한다.The Ministry of Land, Infrastructure and Transport and the Ministry of Industry and Trade said in September 2019 that they are going to establish and to operate ‘a Joint Government-Private Development Strategy Consultative Body’ for developing the future model of ‘Private Air Vehicle’ and for revitalizing the transportation industry, a new concept of air transport. The consultative body will promote joint efforts by industry experts, scholars and researchers in various fields, including aviation, automotive, battery, electric and electronic, transportation services, maintenance and infrastructure, while also promoting review of personal aviation (PAV) services such as development of core technologies and international joint development support for industrial ecosystems, support for improvement of performance and quality, and cooperation among civil forces. Hyundai Motor Co., Ltd. unveiled the concept model ‘S-A1’ of the ‘Private Air Vehicle (PAV)’ at the ‘CES 2020 Consumer Electronics Show 2020’ held on January 7, 2020, along with the unveiling of Hyundai Motor s ‘UAM: Urban Air Mobility’ system. Using ‘Private Air Mobility (UAM)’, ‘Private Airplane Mobility (PAV)’ aims to establish a future mobility ecosystem that allows users to move freely from ground-to-ground traffic jams within urban centers and directly to major facilities in urban areas after landing on the basis of ‘Mobility Transfer Point (HUB)’. If we look at the strategies announced by the government (the Ministry of Land, Transport, Trade, Industry and Energy) and companies (the Ministry of Trade, Industry and Energy) and Hyundai Motor (Hyundai Motor), we will expect that the future transportation in the city will be a self-driving car on the ground and a personal airplane (PAV) flying in the air within the next 10 years. However, the implementation of related technologies, such as aviation, electronics, electricity, communications, maintenance, and other facilities such as transit points(HUB) will be critical in that the ‘UAM’ system is based on ‘Personal Air Mobility’(PAV), but the top priority should be to review how to ensure that these Private Flights (PAVs) can move freely. In the case of self-driving cars, they can move on existing roads, but the use of existing roads is difficult in that ‘PAVs’ fly in the air, not on the ground. If this is not resolved in advance, the commercialization of the ‘urban air mobility’ system will be difficult in the future. Therefore, this paper focuses on the legal issues concerning the operation of ‘Private Air Vehicle (PAV)’ in city areas through a review of the facilities to be built for the commercialization of ‘Private Air Mobility(UAM)’ system and its moving space in urban areas, and intends to conduct a legal review of the improvement measures.

Accurate prediction of drone motion within structured urban air corridors is essential for ensuring safe and efficient operations in Urban Air Mobility (UAM) systems. Although real-world Remote Identification (Remote ID) regulations require drones to broadcast critical flight information such as velocity, access to large-scale, high-quality broadcast data remains limited. To address this, this study leverages a Digital Twin (DT) framework to augment Remote ID spatio-temporal broadcasts, emulating the sensing environment of dense urban airspace. Using Remote ID data, we propose BiDGCNLLM, a hybrid prediction framework that integrates a Bidirectional Graph Convolutional Network (BiGCN) with Dynamic Edge Weighting and a reprogrammed Large Language Model (LLM, Qwen2.5–0.5B) to capture spatial dependencies and temporal patterns in drone speed trajectories. The model forecasts near-future speed variations in surrounding drones, supporting proactive conflict avoidance in constrained air corridors. Results from the AirSUMO co-simulation platform and a DT replica of the Cranfield University campus show that BiDGCNLLM outperforms state-of-the-art time series models in short-term velocity prediction. Compared to Transformer-LSTM, BiDGCNLLM marginally improves the R2 by 11.59%. This study introduces the integration of LLMs into dynamic graph-based drone prediction. It shows the potential of Remote ID broadcasts to enable scalable, real-time airspace safety solutions in UAM.

This paper presents a method of tightly coupling carrier-phase-differential GNSS (CDGNSS) with terrestrial radionavigation system (TRNS) signals and data to build a robust positioning, velocity, and timing (PVT) solution for urban air mobility (UAM). UAM will require precise and robust PVT solutions that are resilient to interference and jamming. CDGNSS offers absolute positioning with high availability and sub-decimeter accuracy but cannot serve as the sole source of PVT for UAM because of its vulnerability to interference: a single potent GNSS jammer could deny UAM service across an entire city were GNSS the sole means UAM navigation. TRNS signals are stronger than those of GNSS and offer additional frequency diversity. Their multipath errors, although larger than for GNSS at street level due to the low elevation angles with which TRNS signals propagate from terrestrial transmitters, are manageably small at altitudes where UAM vehicles will operate. Thus, TRNS offers an attractive backup to GNSS for UAM. This paper explores two techniques for fusion of TRNS and CDGNSS: loosely- and tightly-coupled. The loosely-coupled technique fuses information from the two sensing modalities at the level of full PVT solutions. The tightly-coupled technique explored here fuses GNSS carrier phase and pseudorange measurements with TRNS pseudorange, Doppler, and calibrated pressure sensor measurements, together with inertial sensor measurements, to produce a unified PVT solution. Innovations-based measurement exclusion is applied to reduce the impact of GNSS and TRNS multipath errors and of pressure anomalies due, e.g., to ground effect at take-off and landing. Both loosely- and tightly-coupled techniques are tested on an aerial vehicle platform in an environment where both GNSS and TRNS signals are available. Error growth of the tightly-coupled technique during extended intervals of GNSS denial is studied to determine whether UAM service could continue uninterrupted when only inertial and TRNS measurements remain available.