Designing for safety: The free flight air traffic management concept

Technology, Policy and Managemen

BlueSky ATC Simulator Project: An Open Data and Open Source Approach

To advance ATM research as a science, ATM research results should be made more comparable. A possible way to do this is to share tools and data. This paper presents a project that investigates the feasibility of a fully open-source and open-data approach to air traffic simulation. Here, the first of the two main challenges is to achieve a high fidelity, without using proprietary data, e.g. for aircraft performance. The second challenge is to increase the adoption by the community by keeping the program easy to use, easy to modify, multi-platform, downloadable for free and running stand-alone on relatively simple systems. The approach chosen by the project is to investigate this feasibility by trying to start the development. The paper describes the many hurdles to be overcome when using a fully open-data and open-source policy in this area.Control & Simulatio

Integrating pyModeS and OpenSky Historical Database

A large quantity of Mode S data is being gathered by the OpenSky receiver network every day. Information regarding common flight states, such as position, ground speed, and the vertical rate is broadcast by ADS-B and has already been decoded and made available for researchers via the OpenSky historical database. However, there is still a large amount of Mode S communication data that has not yet been fully explored. Specifically, the information contained in Enhanced Mode S Surveillance downlink messages can be utilized to better support ATM research. The challenge of decoding such information lies in the implicit inference process for Mode S Comm-B messages. This paper presents a new open library, pymodes-opensky, which connects the existing open-source pyModeS decoder to the raw Mode S messages from the OpenSky historical database through the Impala shell. It also presents a convenient workflow that can be used to obtain additional information regarding airspeeds, flight intentions, and meteorological conditions of a given flight from the OpenSky database. An analysis based on a global dataset from OpenSky is conducted, and the associated Mode S interrogation statistics in different regions are shown.Control & SimulationControl & Operation

Analyzing Aircraft Surveillance Signal Quality at the 1090 Megahertz Radio Frequency

Due to the increasing demands for real-time air traffic monitoring, the 1090 megahertz radio frequency has become the most utilized communication channel for aircraft surveillance purposes. Several services are using the radio frequency at the same time, which are Mode A/C communications and Mode S communications. These different types of communications are not coordinated, meaning that the quality of a communication channel can deteriorate with the increasing number of aircraft in the airspace. This deterioration may further worsen with the increasing number of aircraft that comply with the Automatic Dependent Surveillance-Broadcast requirement, which is implemented based on Mode S Extended Squitter. In this paper, we conduct experiments to determine the quality of 1090 megahertz radio frequency by analyzing the low-level signals using an open-source software-defined radio. First, we implement the demodulation of Mode A/C and Mode S signals from the raw in-phase and quadrature signals with a high sampling rate. Then, several methods are employed to study the occupancy of the communication channel and the garbling severity of the signals, as well as the error rate in ADS-B signals. All results show that the radio frequency is experiencing high communication load during day time air traffic operations. The results also suggest a need for a major redesign of the aircraft surveillance system in the future due to the current inefficient utilization of this radio frequency.Virtual/online event due to COVID-19Control & SimulationControl & Operation

Aerial Robotics: State-based Conflict Detection and Resolution (Detect and Avoid) in High Traffic Densities and Complexities

Purpose of Review A lot of research into decentralised, state-based conflict detection and resolution, or detect and avoid algorithms has been executed. This paper explains the essential properties of state-based conflict detection and reviews the work in the context of applications for not only manned but also unmanned aerial vehicles, where this might be applied relatively soon. Recent Findings Lately, based on several reviews of a variety of published algorithms, a selection has been implemented and simulated in extremely high traffic densities for comparison. Summary The modified voltage potential has been surprisingly efficient, even compared with more complex algorithms or adaptations, as is apparent from looking at macroscopic metrics like domino effect, efficiency and safety. This indicates that to this date, it is so far the most suitable algorithm for the detect and avoid role for unmanned aerial vehicles in urban airspaces, or other areas where a high density is expected.Control & OperationsControl & Simulatio

Drone Delivery: Urban airspace traffic density estimation

The concept of autonomous drone delivery in urban areas has gained a favorable amount of media attention over the past few years. Companies such as Amazon, Uber and Matternet are investigating the use of drones to transport parcels in order to solve the disaggregate delivery (last-mile) problem. This solution could potentially reduce vehicular congestion in cities by replacing traditional transport modes used in last-mile delivery, such as trucks, vans and bikes, with a fleet of autonomous drones flying in an urban airspace. To realize this concept, the design of an urban airspace for drones is necessary. However, the design of an urban airspace for drones will depend on critical design metrics such as drone traffic densities, traffic distribution patterns, distance between origin-destination, and the number of distribution centers. For this study, we first tackle the first metric, drone traffic density. This metric will provide an indication for the required urban airspace capacity and its expected demand. This paper therefore establishes a framework for determining the traffic density of delivery drones for a typical urban city airspace in Europe. In addition, the paper presents a cost-analysis study for fast-food delivery via drones relative to electric bikes.Control & SimulationControl & Operation

The Effect of Intent on Conflict Detection and Resolution at High Traffic Densities

The use of drones for applications such as package delivery, in an urban setting, would result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Such densities not only make automated conflict detection and resolution a necessity, but it will also force a reevaluation of aspects such as centralised vs. distributed, coordination vs. priority, or state vs. intent. This paper investigates the use of intent in tactical conflict detection and resolution at high traffic densities in unmanned aviation. Experimental results show that combining both current state and future intent information improved overall safety. Adding intent enables the detection, in advance, of conflicts resulting from future changes of state. A conflict resolution maneuver is optimal for safety when all aircraft deviate only minimally from their current state to solve the conflict. Consequently, they could deviate from the broadcast intent information. Therefore, state projection into the future must still be kept to prevent very short-term conflicts when intruders do not follow their original intent.Virtual/online event due to COVID-19Control & SimulationControl & Operation

Drone Delivery: Nature of Traffic Conflicts in Constrained Urban Airspace Environments

Drone-based delivery is likely to reduce energy and greenhouse gas emissions associated with the transport of small express packages, fast-food meals and medicines, especially when deployed in large-scale in urban areas. However, it is an enormous challenge to facilitate such high traffic densities in constrained urban environments. A recent study applied the principles of traffic alignment and segmentation to the constrained urban airspace of Manhattan, New York, in an effort to mitigate conflict probability. In that study, two novel airspace concepts were proposed, namely, the two-way and one-way concept. Both concepts employed a heading-altitude rule to vertically segmented traffic with respect to their travel directions. In addition, the one-way concept also featured horizontal constraints to promote unidirectional traffic flow. These concepts bear resemblance to that of road-based traffic. Further, both concepts featured transition altitudes to accommodate turning flights that need to decelerate to safely perform turns at intersections. The comparative study showed the one-way airspace configuration to be more effective than the two-way concept in terms of safety. In the pursuit of demonstrating our understanding of the intricate differences between the two-way and one-way airspace configurations, this paper aims to explore and analyse salient conflict properties. By using fast-time simulation experiments, the different types of conflicts are captured and analysed for multiple traffic demand levels. Our results suggest that conflicts are largely caused by flights climbing or descending to their respective altitude layers. For both concepts, the merging conflicts consisted of in-trail and crossing conflicts, while the two-way also contained a high proportion of head-on conflicts. Our study therefore sheds light on the different categories of conflicts that could help guide future research in airspace design in constrained urban areas.Control & SimulationControl & Operation

Derivation of Trajectory Predictor Input Distributions from Observed Data

Control & Simulatio