Multi-view representation learning for performance-based tactical conflict resolution in urban air mobility

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.

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).

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.

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.

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.

Ultrafast charging of energy-dense lithium-ion batteries for urban air mobility

In the near future, vertical take off and landing aircraft of the urban air mobility sector will be integrated into the civil airspace and they will be characterised by several levels of autonomous flying capabilities. Many countries worldwide are funding several researches to identify and develop enabling technologies to make urban air mobility as safe as modern aviation. One of the most critical aspect of those aeroplanes rely on the reduced fuselage dimensions and available space on board to welcome all those safety critical systems commonly used on commercial aviation. The air data system is one of the safety critical system that is equipped with several probes and vanes, protruding externally from the aircraft fuselage, and some of its functionalities are adequately redundant for general aviation and large aeroplanes. Even though an airworthiness standard applicable to urban air mobility is not ready yet, worldwide there are several efforts that will lead to type certification standards in next years. This work presents a brief survey of certified technologies available for sensing solutions feeding air data systems and solutions based on synthetic sensors certifiable in a couple of years. The survey relies on certified and certifiable innovative data sensing units for realistic urban air mobility applications. To this aim, a safety assessment analysis is presented in order to support the validity of the certifiable air data sensing solutions presented in this paper.

Urban air mobility (UAM) refers to a set of vehicles and operational concepts proposed to provide on-demand or scheduled air transportation services within a metropolitan area. This paper investigates potential operational constraints that could arise during the implementation or scale-up of a UAM system. Literature on helicopter passenger networks was reviewed to determine operational constraints experienced by prior services similar to UAM. A constraint analysis was applied to near-term UAM operations in Los Angeles, Boston, and Dallas to assess if the historical constraints persist, or if novel constraints have emerged. The three city cases represented geographically diverse implementation regions for UAM services. A notional door-to-door concept of operations was applied to 32 reference missions within the three city cases. The reference missions exhibited a variety of requirements in terms of flight distance, passenger volume, market type, population overflight, and air traffic congestion, among others. By reviewing ground and flight operations for each reference mission, eight operational constraints were identified that could limit UAM system growth potential or prohibit UAM services altogether. The three most stringent constraints concerned community acceptance of aircraft noise, takeoff and landing area availability, and air traffic control scalability.

Abstract. With technological innovation and advancements, especially in autonomy, battery and digitization, the future of air transport and mobility is transiting towards a broader spectrum of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM). UAM envisions safer, faster, and more sustainable air mobility for smarter cities and urban environments including passenger transport and goods delivery. Nevertheless, this concept is still considered extremely breakthrough and several technological and operational aspects are mostly undefined. In this context, a comprehensive approach to AAM/UAM may be to adapt cutting-edge technologies in developing sustainable framework and Human-Machine Interfaces (HMIs) in order to realize the challenges, benefits, and conditions of such transport system in advance for future safer, more reliable and globally approved operations. One of the technologies that can contribute to accelerate advancements through human centred simulating UAM processes and operations is XR (eXtended Reality). This paper presents the early steps of a multidisciplinary study performed under the framework of PNRR (Piano Nazionale di Ripresa e Resilienza) and MOST (Centro Nazionale Mobilità Sostenibile) project in analyzing the perspectives of XR based HMIs for UAM paradigm and potential AAM/UAM use case scenarios that can be simulated with XR in view of attaining efficient and effective future solutions. Furthermore, the work introduces the state-of-the-art overview on XR facilitated UAM applications and considers prospective potential use cases that can be developed through PNRR research study in demonstrating XR as an enabling technology in promising areas of the UAM framework.

This paper examines developments in urban air mobility (UAM), the configurations and flight mechanisms of different aerial vehicles. Despite the interest generated around UAM, there seems to be a gap in the literature concerning a systematic comparative analysis of different configurations, especially regarding their appropriateness for given applications, performance under fault conditions, and potential in even more foresightful but neglected designs. The other problems standing in the way of current UAM technologies are limited payload capacity, endurance, and energy efficiency, all of which work against successful commercialization. This study, therefore, considers a representation of 53 of the more prominent UAM aircraft, classified into a number of groups, paving a way for the in-depth study of important specifications such as range, speed, endurance, cargo capacity, number of passengers, and dimensions. Twelve general UAM configurations are identified, along with their advantages, disadvantages, and fault tolerance. Some underutilized designs are highlighted as worthy of more attention due to their potential. An attempt is made to link UAM configurations to specific applications, such as transportation, emergency response, and cargo delivery, in order to provide specific recommendations for each application. This work challenges standard design thinking, thus inciting designers to explore unusual avenues. The outcome is a useful analysis for researchers and engineers to look at UAM technologies in a different light while opening up possibilities for unconventional and creative designs.

Millions of small Unmanned Aerial Systems (sUAS), or drones weighing less than 55 pounds, will fly in urban airspaces within a decade. This is in addition to goals for increased Urban Air Mobility (UAM): larger transportation UAS and piloted air vehicles, including air taxi service and innovative aviation designs to revolutionize transportation. A significant problem is the lack of current management systems for this extremely large volume of air traffic, composed of heterogeneous drone shapes, sizes, and onboard equipment capabilities, flying adjacent to larger UAM vehicles in spaces previously unoccupied by General Aviation (GA). Robust and resilient detection, identification, localization, and tracking of sUAS sharing UAM airspace is complicated by urban factors such as non-transmitting, non-cooperative drones. Exacerbating these challenges, current technological limitations and vulnerabilities in Global Positioning System (GPS), Automatic Dependent Surveillance-Broadcast (ADS-B), and Inertial Navigation Systems (INS) can pose safety and security threats. To streamline a vision of safe and secure sUAS-UAM shared airspace, we propose Drone Net, a UAS Traffic Management (UTM) network of multi-modal ground and flight instruments. Drone Net is an architecture fusing a network of passive visual and acoustic sensor nodes with active Radio Detection and Ranging (radar) and Light Detection and Ranging (lidar) sensing methods for UTM, designed for integration with existing Air Traffic Control (ATC) and future UAM systems. The purpose of the Drone Net system is to evaluate use of Electro-Optical/Infrared (EO/IR) and acoustic arrays networked within an urban UAS operating region such as uncontrolled Class-G and waiver-granted Class-D airspace. The Drone Net approach combines detection, tracking, and localization estimation from radar, ADS-B, and EO/IR such that the design is robust to sensor errors, sample loss, and spoofing or other types of attacks. The system experimental design allows for emulation of corrupted ADS-B, GPS, and INS data on our flight platform including capability to communicate with ground radar and EO/IR to recover from flight instrument major and minor malfunctions such that a Drone Net cooperative UAS can be engineered to be fail-safe and fail-secure. We hypothesize that the Drone Net network of rooftop sensors, shown below, provides this conceptualized fail-safe, fail-secure property based upon the combination of self-localization with backup and confirming data from the ground sensor network. Further, with ground-system sensor fusion as well as UTM flight plan and registration information fusion, the overall system can manage small UAS that are both compliant and non-compliant alongside GA and UAM more safely than a single mode like ADS-B alone. To test our hypothesis, we envision two experiments this year. First, a test to confirm that we can emulate ADS-B, GPS, and INS sensor data corruption, leading to recovery using backup flight (lidar, EO/IR) or ground (radar, EO/IR) data to safely land an ALTA6 or other test UAS. Second, a series of Sense-and-Avoid (SAA) experiments between our test UAS and a tethered aerial obstacle. In the future, we will use this experience with fail-safe, fail-secure methods and software to further test more advanced scenarios between multiple UAS. The network of Drone Net instruments in a local area as well as regional and more global cloud-based networks will allow for heterogeneous information fusion and algorithm development for multi-sensor drone detection, classification, and identification with more accuracy than a single database or sensor system. The latent power of the Drone Net project is in its open-design ground and flight sensor network with data sharing capability to improve data mining and machine learning over time for analysis and security applications. More concrete applications for Drone Net include UTM integration with ATC and UAM, but also airspace safety and security for campus and public venues in general. Herein, we will present our experimental design and current test data from Embry-Riddle Aeronautical University in collaboration with University of Colorado Boulder toward completing the open specification for ground and flight instruments. We would additionally like to invite others to participate in growing the network and the data available for UTM, UAM, and GA shared airspace research.