According to a 2013 AUVSI report, delays in integrating Unmanned Aerial Systems (UAS) into the National Airspace System (NAS) could cost more than $10 billions a year for the United States alone. Worldwide regulatory bodies are under pressure by the UAS industry to accelerate the regulation process, but safety remains their main objective. One condition for the safe introduction of UAS in the NAS is for them to be equipped with a collision avoidance system. Though the existing Airborne Collision Avoidance System II (ACAS II) could have been an option, the transformations of air traffic management engaged through NextGen (US) and SESAR (Europe) led to the definition of a new ACAS based on new logics, namely ACAS X. Its definition contains in particular two variations : ACAS Xa, for large aircraft, and ACAS Xu, for unmanned aircraft. As noted in a 2014 RTCA annual report, divide in technological knowledge between those experienced in ACAS II and those involved in the development of ACAS X is a concern. To help preventing this divide we believe it is essential to keep the community updated with the latest evolutions of the ACAS X standards. As work on Minimum Operational Performance Standards (MOPS) for ACAS Xu just started, it is of interest to know which parts of the MOPS are already decided, which remain flexible for the industries to make the difference and which are open research problems. Being a member of the ACAS X family, ACAS Xu lays on the same foundations as the well defined ACAS Xa standard. This work proposes an introduction to the ACAS Xa/Xu common basis, as it is unlikely to change, including the general architecture and Collision Avoidance (CA) logics. It is followed by a presentation of concepts specific to ACAS Xu such as the tailored threat logic, horizontal CA logic, CA coordination and automatic responses. For the flexible part, we believe it mainly concerns the surveillance sources. Instead of a precise standard, the regulation is likely to ask for requirements on the sensors capabilities. A state of the art of recent works allows proposing minimum sensor performances and focusing on an essential set of sensors. This work is concluded by presenting future challenges that need to be addressed to build a safe ACAS Xu baseline and to extend it to smaller and lower altitude UAS.

/pdf/an-introduction-to-acas-xu-and-the-challenges-ahead-4fylk0z2do.pdf

An introduction to ACAS Xu and the challenges ahead

The capability to avoid other air traffic is a fundamental component of the layered conflict management system to ensure safe and efficient operations in the National Airspace System. The evaluation of systems designed to mitigate the risk of midair collisions of manned aircraft are based on large-scale modeling and simulation efforts and a quantitative volume defined as a near midair collision (NMAC). Since midair collisions are difficult to observe in simulation and are inherently rare events, basing evaluations on NMAC enables a more robust statistical analysis. However, an NMAC and its underlying assumptions for assessing close encounters with manned aircraft do not adequately consider the different characteristics of smaller UASonly encounters. The primary contribution of this paper is to explore quantitative criteria to use when simulating two or more smaller UASs in sufficiently close proximity that a midair collision might reasonably occur and without any mitigations to reduce the likelihood of a midair collision. The criteria assumes a historically motivated upper bound for the collision likelihood and subsequently identify the smallest possible NMAC analogs. We also demonstrate the NMAC analogs can be used to support modeling and simulation activities.

/pdf/a-quantitatively-derived-nmac-analog-for-smaller-unmanned-322b1jx5or.pdf

A Quantitatively Derived NMAC Analog for Smaller Unmanned Aircraft Systems Based on Unmitigated Collision Risk

We autonomously direct a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or "drone" to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, are varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

/pdf/in-flight-positional-and-energy-use-data-set-of-a-dji-2atem0x9c2.pdf

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery

A procedure for calibrating the spinning ultrasonic wind sensors

A high-quality estimate of wind fields can potentially improve the safety and performance of Unmanned Aerial Vehicles (UAVs) operating in dense urban areas. Computational Fluid Dynamics (CFD) simulations can help provide a wind field estimate, but their accuracy depends on the knowledge of the distribution of the inlet boundary conditions. This paper provides a real-time methodology using a Particle Filter (PF) that utilizes wind measurements from a UAV to solve the inverse problem of predicting the inlet conditions as the UAV traverses the flow field. A Gaussian Process Regression (GPR) approach is used as a surrogate function to maintain the real-time nature of the proposed methodology. Real-world experiments with a UAV at an urban test-site prove the efficacy of the proposed method. The flight test shows that the 95% confidence interval for the difference between the mean estimated inlet conditions and mean ground truth measurements closely bound zero, with the difference in mean angles being between –3.7° and 1.3° and the difference in mean magnitudes being between –0.2 m/s and 0.0 m/s.Video : https://youtu.be/U4XdYgSJRZM

Wind and the City: Utilizing UAV-Based In-Situ Measurements for Estimating Urban Wind Fields

Collision Avoidance System Effectiveness on Low Performance Unmanned Aircraft

This paper details a series of flight tests performed on an 11-foot wingspan UAV. Flight test objectives included calculation of the aerodynamic angles (angle of attack and sideslip angle), calculation of in-flight horizontal wind velocity, and characterization of aircraft dynamic modes. Important flight variables included rotation rates as measured by MEMS rate gyros, velocities relative to the ground as measured by GPS, and airspeed as measured by an airborne sonic anemometer. The aerodynamic angles were calculated using a vector analysis of the aircraft's orientation and velocity as determined from the rate gyros and GPS, respectively. These results were then compared to those calculated from the onboard sonic anemometer. Similarly, wind speeds were calculated by subtracting groundspeed as measured by the GPS from airspeed as measured by the airborne sonic anemometer. These results were then compared to windspeeds measured from a second, grounded sonic anemometer. Finally, the short period, roll, and Dutch roll modes were excited by appropriate flight maneuvers and compared to theoretical/empirical predictions. Trendwise, the rate gyro/GPS aerodynamic angles agreed with the sonic anemometer during straight and level passes. The calculations would be improved by better Euler angle estimates and better knowledge of ambient wind. The average wind velocity vector obtained from the onboard instrumentation was higher than the one measured from the ground station. The aerodynamic influence of the aircraft at the location of the sonic anemometer and measurement errors of the Euler angles might be the possible causes. The dynamic mode flight results matched the theoretical/empirical predictions, though they were significantly affected by atmospheric turbulence.

http://enu.kz/repository/2010/AIAA-2010-4572.pdf

UAV Flight Testing with an Airborne Sonic Anemometer, IMU and GPS

This paper describes Monte Carlo simulation results for validating airport surveillance requirements. A fast-time ATC simulator was used to assess the effect on airport efficiency and aircraft safety as surveillance parameters were varied. The results were used to identify the minimum surveillance performance needed to meet operational efficiency and safety requirements.

Airport surveillance requirements validation using Monte Carlo simulation

The effectiveness of an airborne collision avoidance system is influenced by the manner in which pilots respond to the system’s advisories. Current pilot response models used in collision avoidance...

Bayesian Network Model of Pilot Response to Collision Avoidance System Resolution Advisories

Introduction: Engineering students benefit from understanding the role of technical communication in the professional workplace. This article examines the communication coefficient (CC), a new method for grading student technical communication intended to help students better understand this role. Its goal is to encourage students to treat their communication with the same importance that it has in the professional workplace. About the case: The core philosophy of the CC method is that audiences perceive technical work more positively when it is communicated well and more negatively when it is not. The method captures this philosophy mathematically: students’ grades result from multiplying the points earned for technical content by a number—the coefficient—representing how well they communicated that content. Situating the case: The CC method is rooted in established principles, such as holistic grading and the separate yet simultaneous consideration of content and communication. It is novel in how it combines these principles into a grading technique. Approach: The CC method was employed in three undergraduate engineering classes at the United States Military Academy during the spring 2020 semester. Student and instructor feedback were collected to gauge the pros and cons of the method and whether it is worth fielding on a larger scale. Discussion: The CC method was found to encourage better student communication, although mixed student and instructor opinion suggest that changes to the method and the way that it is messaged are necessary. Conclusion: The CC method warrants further study and consideration of its usefulness in other departments and institutions.

Edward H. Londner

Papers

Collision Avoidance System Effectiveness on Low Performance Unmanned Aircraft

UAV Flight Testing with an Airborne Sonic Anemometer, IMU and GPS

Airport surveillance requirements validation using Monte Carlo simulation

Bayesian Network Model of Pilot Response to Collision Avoidance System Resolution Advisories

The Communication Coefficient Method: A New Faculty Grading Tool Designed to Help Engineering Students Improve Their Technical Communication