Search NASA⌕ Search

SEARCH · Search NASA

Results for “collision avoidance”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

A TCAS-II Resolution Advisory Detection Algorithm

The Traffic Alert and Collision Avoidance System (TCAS) is a family of airborne systems designed to reduce the risk of mid-air collisions between aircraft. TCAS~II, the current generation of TCAS devices, provides resolution advisories that direct pilots to maintain or increase vertical separation when aircraft distance and time parameters are beyond designed system thresholds. This paper presents a mathematical model of the TCAS~II Resolution Advisory (RA) logic that assumes accurate aircraft state information. Based on this model, an algorithm for RA detection is also presented. This algorithm is analogous to a conflict detection algorithm, but instead of predicting loss of separation, it predicts resolution advisories. It has been formally verified that for a kinematic model of aircraft trajectories, this algorithm completely and correctly characterizes all encounter geometries between two aircraft that lead to a resolution advisory within a given lookahead time interval. The RA detection algorithm proposed in this paper is a fundamental component of a NASA sense and avoid concept for the integration of Unmanned Aircraft Systems in civil airspace.

Munoz, Cesar↗
NASA NTRSDate not supplied

Integration of Automation Systems Flight Test Overview

This short presentation outlines an upcoming flight test to be performed as part of the Advanced Air Mobility (AAM) project. Referred to as the Integration of Automated Systems (IAS) flight test series, the objectives are to evaluate NASA research concepts and technologies for complex operations through integrated automation and candidate operational concepts and scenarios. The primary objective is to test mature AAM technologies in a relevant environment. The two primary systems under test are the Flight Path Management (FPM) and Hazard Perception and Avoidance (HPA) technology. This presentation focuses on the HPA technology developed by the FAA known as the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr) since the audience consists of committee members currently working on developing the minimum requirements for this system. The second half of the presentation explains the primary objectives and describes the scenarios expected to be tested in flight.

automation↗
NASA NTRS2012

UAS Integration Into the NAS: An Examination of Baseline Compliance in the Current Airspace System

As a result of the FAA Modernization and Reform Act of 2012, Unmanned Aerial Systems (UAS) are expected to be integrated into the National Airspace System (NAS) by 2015. Several human factors challenges need to be addressed before UAS can safely and routinely fly in the NAS with manned aircraft. Perhaps the most significant challenge is for the UAS to be non-disruptive to the air traffic management system. Another human factors challenge is how to provide UAS pilots with intuitive traffic information in order to support situation awareness (SA) of their airspace environment as well as a see-and-avoid capability comparable to manned aircraft so that a UAS pilot could safely maneuver the aircraft to maintain separation and collision avoidance if necessary. A simulation experiment was conducted to examine baseline compliance of UAS operations in the current airspace system. Researchers also examined the effects of introducing a Cockpit Situation Display (CSD) into a UAS Ground Control Station (GCS) on UAS pilot performance, workload and situation awareness while flying in a positively controlled sector. Pilots were tasked with conducting a highway patrol police mission with a Medium Altitude Long Endurance (MALE) UAS in L.A. Center airspace with two mission objectives: 1) to reroute the UAS when issued new instructions from their commander, and 2) to communicate with Air Traffic Control (ATC) to negotiate flight plan changes and respond to vectoring and altitude change instructions. Objective aircraft separation data, workload ratings, SA data, and subjective ratings regarding UAS operations in the NAS were collected. Results indicate that UAS pilots were able to comply appropriately with ATC instructions. In addition, the introduction of the CSD improved pilot SA and reduced workload associated with UAS and ATC interactions.

Fern, Lisa↗
NASA NTRS2007

Algorithm Plans Collision-Free Path for Robotic Manipulator

An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps between the corresponding OBB and OBP models. For computational efficiency, the process is started at the coarsest resolution and stopped as soon as possible, preferably before reaching the finest resolution. At the coarsest resolution, there is a single OBB enclosing all relevant external objects and a single OBB enclosing the entire robot. At the next finer level of resolution, the coarsest-resolution OBB is divided into two OBBs, and so forth. If no collision is detected at the coarsest resolution, then there is no need for further computation to detect collisions. If a collision is detected at the coarsest resolution, then tests for collisions are performed at the next finer level of resolution. This process is continued to successively finer resolutions until either no more collisions are detected or the finest resolution is reached.

Backes, Paul↗
NASA NTRS2014

Pilot Evaluation of a UAS Detect-and-Avoid System's Effectiveness in Remaining Well Clear

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. Regulators will establish minimum operating standards for DAA effectiveness, but different combinations of algorithms, displays and procedures could be used to meet those standards. The research presented in this paper indicates the effectiveness of the combined pilot-DAA system as a function of the DAA design requirements and provides data that may be used to model the behavior of pilots when employing such systems. Two simulations involving 21 professional unmanned aircraft system (UAS) pilots evaluated eight different DAA system designs in order to assess their ability to maintain the "well clear" separation standard, i.e., the state of maintaining a safe distance from other aircraft that would not normally cause the initiation of a collision avoidance maneuver by either aircraft. When the traffic display was integrated with the primary mission map directly in front of the pilot, there were fewer losses of well clear. Greater warning time provided to the pilot was strongly correlated with success in remaining well clear. Pilots' ability to separate from aircraft with cooperative and non-cooperative surveillance systems was nearly the same after accounting for the amount of alert time provided in each encounter, although the limited surveillance volume for the airborne-equipped aircraft meant alerts tended to occur later and therefore were more difficult to resolve.

detect-and-avoid↗
NASA NTRS2010

Stereoscopic Machine-Vision System Using Projected Circles

A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a template in processing terrain images. During operation on terrain, the images acquired by the left and right cameras are analyzed. The analysis includes (1) computation of the horizontal and vertical dimensions and the aspect ratios of rectangles that bound the circle images and (2) comparison of these aspect ratios with those of the template. Coordinates of distortions of the circles are used to identify and locate objects. If the analysis leads to identification of an object of significant size, then stereoscopicvision algorithms are used to estimate the distance to the object. The time taken in performing this analysis on a single pair of images acquired by the left and right cameras in this system is a fraction of the time taken in processing the many pairs of images acquired in a sweep of the laser stripe across the field of view in the prior system. The results of the analysis include data on sizes and shapes of, and distances and directions to, objects. Coordinates of objects are updated as the vehicle moves so that intelligent decisions regarding speed and direction can be made. The results of the analysis are utilized in a computational decision-making process that generates obstacle-avoidance data and feeds those data to the control system of the robotic vehicle.

Mackey, Jeffrey R.↗
NASA NTRS1996

Follow-the-Leader Control for the PIPS Prototype Hardware

This report describes the payload inspection and processing system (PIPS), an automated system programmed off-line for inspection of space shuttle payloads after integration and prior to launch. PIPS features a hyper-redundant 18-degree of freedom (DOF) serpentine truss manipulator capable of snake like motions to avoid obstacles. During the summer of 1995, the author worked on the same project, developing a follow-the-leader (FTL) algorithm in graphical simulation which ensures whole arm collision avoidance by forcing ensuing links to follow the same tip trajectory. The summer 1996 work was to control the prototype PIPS hardware in follow-the-leader mode. The project was successful in providing FTL control in hardware. The STS-82 payload mockup was used in the laboratory to demonstrate serpentine motions to avoid obstacles in a realistic environment.

Williams, Robert L. II↗
NASA NTRS1999

NASA Lewis Launch Collision Probability Model Developed and Analyzed

There are nearly 10,000 tracked objects orbiting the earth. These objects encompass manned objects, active and decommissioned satellites, spent rocket bodies, and debris. They range from a few centimeters across to the size of the MIR space station. Anytime a new satellite is launched, the launch vehicle with its payload attached passes through an area of space in which these objects orbit. Although the population density of these objects is low, there always is a small but finite probability of collision between the launch vehicle and one or more of these space objects. Even though the probability of collision is very low, for some payloads even this small risk is unacceptable. To mitigate the small risk of collision associated with launching at an arbitrary time within the daily launch window, NASA performs a prelaunch mission assurance Collision Avoidance Analysis (or COLA). For the COLA of the Cassini spacecraft, the NASA Lewis Research Center conducted an in-house development and analysis of a model for launch collision probability. The model allows a minimum clearance criteria to be used with the COLA analysis to ensure an acceptably low probability of collision. If, for any given liftoff time, the nominal launch vehicle trajectory would pass a space object with less than the minimum required clearance, launch would not be attempted at that time. The model assumes that the nominal positions of the orbiting objects and of the launch vehicle can be predicted as a function of time, and therefore, that any tracked object that comes within close proximity of the launch vehicle can be identified. For any such pair, these nominal positions can be used to calculate a nominal miss distance. The actual miss distances may differ substantially from the nominal miss distance, due, in part, to the statistical uncertainty of the knowledge of the objects positions. The model further assumes that these position uncertainties can be described with position covariance matrices. With these, and some additional simplifying assumptions, a closed-form solution for the probability of collision is obtained. This solution provides clear insights into how each of the independent parameters affects the probability of collision. It shows that for a given maximum probability of collision and prior knowledge of the objects position uncertainties and sizes, only knowledge of the nominal closest approach distance is required to make the launch/no launch decision. The model was completed and used for the mission assurance COLA analysis for the Cassini spacecraft, which was launched on a Titan IV/Centaur rocket on October 15, 1997. Although the model was specifically developed for the Cassini mission, it is clearly applicable for other launches as well. The effect of COLA closures on the launch window is shown. The bar represents the entire 140-min launch window on October 15, 1997; the blackened areas represent the loss of launch opportunities due to the potential for a collision with an orbiting object.

Bollenbacher, Gary↗
NASA NTRS1990

Teleautonomous guidance for mobile robots

Teleautonomous guidance (TG), a technique for the remote guidance of fast mobile robots, has been developed and implemented. With TG, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This type of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. TG allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. TG is based on the virtual force field (VFF) method, which was developed earlier for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data (such as that produced by ultrasonic sensors) and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles.

Borenstein, J.↗
NASA NTRS2012

Varying Levels of Automation on UAS Operator Responses to Traffic Resolution Advisories in Civil Airspace

Continuing demand for the use of Unmanned Aircraft Systems (UAS) has put increasing pressure on operations in civil airspace. The need to fly UAS in the National Airspace System (NAS) in order to perform missions vital to national security and defense, emergency management, and science is increasing at a rapid pace. In order to ensure safe operations in the NAS, operators of unmanned aircraft, like those of manned aircraft, may be required to maintain separation assurance and avoid loss of separation with other aircraft while performing their mission tasks. This experiment investigated the effects of varying levels of automation on UAS operator performance and workload while responding to conflict resolution instructions provided by the Tactical Collision Avoidance System II (TCAS II) during a UAS mission in high-density airspace. The purpose of this study was not to investigate the safety of using TCAS II on UAS, but rather to examine the effect of automation on the ability of operators to respond to traffic collision alerts. Six licensed pilots were recruited to act as UAS operators for this study. Operators were instructed to follow a specified mission flight path, while maintaining radio contact with Air Traffic Control and responding to TCAS II resolution advisories. Operators flew four, 45 minute, experimental missions with four different levels of automation: Manual, Knobs, Management by Exception, and Fully Automated. All missions included TCAS II Resolution Advisories (RAs) that required operator attention and rerouting. Operator compliance and reaction time to RAs was measured, and post-run NASA-TLX ratings were collected to measure workload. Results showed significantly higher compliance rates, faster responses to TCAS II alerts, as well as less preemptive operator actions when higher levels of automation are implemented. Physical and Temporal ratings of workload were significantly higher in the Manual condition than in the Management by Exception and Fully Automated conditions.

Kenny, Caitlin↗
NASA NTRSDate not supplied

Hazard Perception & Avoidance (HPA), Assured Vehicle Automation 1 Simulation (AVA-1h) Results Outbrief

In late 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This HITL was the lab’s second Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The goals were to assess detect and avoid technology for manned, electric vertical takeoff and landing (eVTOL) aircraft. This simulation tested Resolution Advisory (RA) responses and return-to-course (RTC) maneuvers for the second version of the Airborne Collision Avoidance System’s (ACAS) rotary-wing (Xr) variant. This was conducted at the center's Vertical Motion Simulator (VMS), on a motion-based platform, and was configured to fly eVTOL aircraft while maneuvering for intruding traffic. Variables for this study included ACAS Xr modes (i.e., TA/RA and DAA) and phases of flight (i.e., Cruise, Hover, and Approach). The data collected included response times, losses of well clear, and pilots' noncompliances to alerts and guidance as well as subjective ratings like acceptability and perceived workload. Additional details and future anticipations are also discussed.

ACAS Xr↗
DOE OSTI2022

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2011

Engineering and Technology Challenges for Active Debris Removal

After more than fifty years of space activities, the near-Earth environment is polluted with man-made orbital debris. The collision between Cosmos 2251 and the operational Iridium 33 in 2009 signaled a potential collision cascade effect, also known as the "Kessler Syndrome", in the environment. Various modelling studies have suggested that the commonly-adopted mitigation measures will not be sufficient to stabilize the future debris population. Active debris removal must be considered to remediate the environment. This paper summarizes the key issues associated with debris removal and describes the technology and engineering challenges to move forward. Fifty-four years after the launch of Sputnik 1, satellites have become an integral part of human society. Unfortunately, the ongoing space activities have left behind an undesirable byproduct orbital debris. This environment problem is threatening the current and future space activities. On average, two Shuttle window panels are replaced after every mission due to damage by micrometeoroid or orbital debris impacts. More than 100 collision avoidance maneuvers were conducted by satellite operators in 2010 to reduce the impact risks of their satellites with respect to objects in the U.S. Space Surveillance Network (SSN) catalog. Of the four known accident collisions between objects in the SSN catalog, the last one, collision between Cosmos 2251 and the operational Iridium 33 in 2009, was the most significant. It was the first ever accidental catastrophic destruction of an operational satellite by another satellite. It also signaled the potential collision cascade effect in the environment, commonly known as the "Kessler Syndrome," predicted by Kessler and Cour-Palais in 1978 [1]. Figure 1 shows the historical increase of objects in the SSN catalog. The majority of the catalog objects are 10 cm and larger. As of April 2011, the total objects tracked by the SSN sensors were more than 22,000. However, approximately 6000 of them had yet to be fully processed and entered into the catalog. This population had been dominated by fragmentation debris throughout history. Before the anti-satellite test (ASAT) conducted by China in 2007, the fragmentation debris were almost all explosion fragments. After the ASAT test and the collision between Iridium 33 and Cosmos 2251, the ratio of collision fragments to explosion fragments was about one-to-one. It is expected that accidental collision fragments will further dominate the environment in the future.

Liou, Jer-Chyi↗
NASA NTRS1991

Advanced mechanisms for robotics

An overview of applied research and development at the Goddard Space Flight Center (GSFC) on mechanisms and collision avoidance skin for robots is presented. The work on robot end effectors is outlined, followed by a brief discussion of robot-friendly payload latching mechanisms and compliant joints. This is followed by discussions of the collision avoidance/management skin and the GSFC research on magnetorestrictive direct drive motors. A new project, the artificial muscle, is introduced. Each of the devices is described sufficiently to permit a basic understanding of its purpose, capabilities, and operating fundamentals. The implications for commercialization are discussed.

Vranish, John M.↗
NASA NTRS1992

Advanced mechanisms for robotics

An overview of applied research and development at NASA-Goddard (GSFC) on mechanisms and the collision avoidance skin for robots is presented. First the work on robot end effectors is outlined, followed by a brief discussion on robot-friendly payload latching mechanisms and compliant joints. This, in turn, is followed by the collision avoidance/management skin and the GSFC research on magnetostrictive direct drive motors. Finally, a new project, the artificial muscle, is introduced. Each of the devices is described in sufficient detail to permit a basic understanding of its purpose, fundamental principles of operation, and capabilities. In addition, the development status of each is reported along with descriptions of breadboards and prototypes and their test results. In each case, the implications of the research for commercialization is discussed. The chronology of the presentation will give a clear idea of both the evolution of the R&D in recent years and its likely direction in the future.

Vranish, John M.↗
NASA NTRSDate not supplied

Assured Vehicle Automation 1 Sim - Results Outbrief

In early 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This part-task HITL began the lab’s Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The results of that sim guided the objectives of the current study, which were to examine pilots’ use of the Airborne Collision Avoidance System (ACAS) rotorcraft variant (Xr) v2 in multiple phases of flight with two separate Xr Modes, fully leverage Xr v2 features (e.g., use radar altimeter data to inform low altitude Resolution Advisory [RA] behavior, utilize the ability to designate “terminal-area intruders,” and display airspeed-based Detect and Avoid [DAA] guidance), emulate a “Traffic Advisory” (TA), and present Xr in a higher-fidelity environment. Therefore, this study was conducted in the Vertical Motion Simulator, and the variables included Phase of Flight (En-route, Hover, and Approach) as well as ACAS Xr Mode (TA/RA and DAA). The data collected included response times, losses of well clear, and maneuver sizes and durations as well as subjective ratings like acceptability and usability. Additional details and future anticipations are also discussed.

air taxis↗
NASA NTRS2015

Appendix A: NAS-Wide Encounter Rate Evaluation Using Historical Radar Data and the Airspace Concept Evaluation System (ACES)

Regulations that establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions. Those requirements will apply to detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the National Airspace System (NAS) and are determined according to their contribution to the overall level of safety required to operate in the airspace. Several key gaps must be addressed in order to link equipment requirements to an airspace level of safety. Foremost among these is the calculation of the relative effectiveness of a particular system to mitigate violations of a separation standard with other aircraft, which is known as the systems risk ratio. The risk ratio is calculated as the probability of mid-air collision with a DAA system divided by the probability of mid-air collision without a DAA system. The risk ratio of a DAA system, in combination with the risk ratios of other collision avoidance mitigations, will determine the overall safety of the airspace measured in terms of the number of mid-air collisions per flight hour. Defining the required risk ratio that the DAA system needs to ensure the safety of the airspace requires an evaluation of the current airspace and a simulated evaluation that incorporates UAS aerodynamic performance and the mission characteristics of future UAS operations that are projected to be conducted in areas that interact with current operations. These evaluations will produce the frequency of encounters that currently exist in the airspace and those that could be generated with the introduction of UAS. Together, the frequency of encounters, an evaluation of unmitigated risk of collision, and a desired level of safety of the airspace will yield a required risk ratio of the DAA system. This study will focus on evaluating the encounter rates between aircraft based on historical radar data and encounter rates that could occur based on simulated UAS missions.

Unmanned Aircraft Systems↗