Results for “avoidance” — Page 44

NASA NTRS2011

Climate, Health, Agricultural and Economic Impacts of Tighter Vehicle-Emission Standards

Non-CO2 air pollutants from motor vehicles have traditionally been controlled to protect air quality and health, but also affect climate. We use global composition climate modelling to examine the integrated impacts of adopting stringent European on-road vehicle-emission standards for these pollutants in 2015 in many developing countries. Relative to no extra controls, the tight standards lead to annual benefits in 2030 and beyond of 120,000-280,000 avoided premature air pollution-related deaths, 6.1-19.7 million metric tons of avoided ozone-related yield losses of major food crops, $US0.6-2.4 trillion avoided health damage and $US1.1-4.3 billion avoided agricultural damage, and mitigation of 0.20 (+0.14/-0.17) C of Northern Hemisphere extratropical warming during 2040-2070. Tighter vehicle-emission standards are thus extremely likely to mitigate short-term climate change in most cases, in addition to providing large improvements in human health and food security. These standards will not reduce CO2 emissions, however, which is required to mitigate long-term climate change.

Shindell, Drew↗

NASA NTRS2016

UAS-NAS Project Demo - Mini HITL Week 2 Stats

The UAS-NAS Project demo will showcase recent research efforts to ensure the interoperability between proposed UAS detect and avoid (DAA) human machine interface requirements (developed within RTCA SC-228) and existing collision avoidance displays. Attendees will be able to view the current state of the art of the DAA pilot traffic, alerting and guidance displays integrated with Traffic advisory and Collision Avoidance (TCAS) II in the UAS-NAS Project's research UAS ground control station (developed in partnership with the Air Force Research Laboratory). In addition, attendees will have the opportunity to interact with the research UAS ground control station and "fly" encounters, using the DAA and TCAS II displays to avoid simulated aircraft. The display of the advisories will be hosted on a laptop with an external 30" monitor, running the Vigilant Spirit system. DAA advisories will be generated by the JADEM software tool, connected to the system via the LVC Gateway. A repeater of the primary flight display will be shown on a 55" monitor mounted on a stand at the back of the booth to show the pilot interaction to the passersby.

UAS↗

NASA NTRS2016

AIAA Aviation UAS DAA Demonstration-Mini HITL Week 2 Stats

The UAS-NAS Project demo will showcase recent research efforts to ensure the interoperability between proposed UAS detect and avoid (DAA) human machine interface requirements (developed within RTCA SC-228) and existing collision avoidance displays. Attendees will be able to view the current state of the art of the DAA pilot traffic, alerting and guidance displays integrated with Traffic advisory and Collision Avoidance (TCAS) II in the UAS-NAS Project's research UAS ground control station (developed in partnership with the Air Force Research Laboratory). In addition, attendees will have the opportunity to interact with the research UAS ground control station and "fly" encounters, using the DAA and TCAS II displays to avoid simulated aircraft. The display of the advisories will be hosted on a laptop with an external 30" monitor, running the Vigilant Spririt system. DAA advisories will be generated by the JADEM software tool, connected to the system via the LVC Gateway. A repeater of the primary flight display will be shown on a 55" tv/monitor mounted on a stand at the back of the booth to show the pilot interaction to the passersby.

UAS↗

NASA NTRS2016

UAS in the NAS Flight Test Series 4 Overview

Flight Test Series 4 (FT4) provides the researchers with an opportunity to expand on the data collected during the first flight tests. Following Flight Test Series 3, additional scripted encounters with different aircraft performance and sensors will be conducted. FT4 is presently planned for Spring of 2016 to ensure collection of data to support the validation of the final RTCA Phase 1 DAA (Detect and Avoid) Minimum Operational Performance Standards (MOPS). There are three research objectives associated with this goal: Evaluate the performance of the DAA system against cooperative and non-cooperative aircraft encounters Evaluate UAS (Unmanned Aircraft Systems) pilot performance in response to DAA maneuver guidance and alerting with live intruder encounters Evaluate TCAS/DAA (Traffic Alert and Collision Avoidance System/Detect and Avoid) interoperability. This flight test series will focus on only the Scripted Encounters configuration, supporting the collection of data to validate the interoperability of DAA and collision avoidance algorithms.

flight test↗

NASA NTRS2017

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

Human-in-the-loop Evaluation↗

NASA NTRS2017

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

Traffic flow management↗

NASA NTRS2014

Investigating the Impacts of a Separation Standard for UAS Operations in Enroute and Transition Airspace

Unmanned aircraft systems will be required to equip with a detect and avoid system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. To comply with regulations in today’s operations manned aircraft must “see and avoid” other aircraft and use subjective judgment to determine whether those aircraft are well clear. For a detect-and- avoid (DAA) system to satisfy the requirement to stay well clear, a quantitative definition of well clear needs to be defined and evaluated. Definitions for the boundary of well clear have been proposed by the Unmanned Aircraft System (UAS) Executive Committee Science and Research Panel (SaRP) and the Radio Technical Commission for Aeronautics (RTCA) Special Committee 228 on Detect and Avoid Systems. This study investigates the interoperability implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the national airspace system. The first analysis in the study focuses on the effect of variations in well clear definition parameters on the rate of losses of well clear per flight hour. The second analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The third analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All three analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results from the three analyses presented in this study inform the safety case, requirements development, and the operational environment for the DAA minimum operational performance standards.

UAS Seperation Standard↗

NASA NTRSDate not supplied

The Challenger tragedy was caused by an Apollo mistake, terminating risk analysis

NASA’s view of risk changed between early Apollo and the Space Shuttle. Risk was a known serious problem at the beginning of Apollo and the risk estimates were disturbingly high. To avoid public concern, risk analysis was discontinued. Risk analysis was avoided in Shuttle, leading to an unnecessarily risky design. The immediate cause of the Challenger tragedy was the mistaken decision to launch in cold weather. The fundamental cause was the high risk of the Shuttle design. Before Challenger, management thought and testified that the probability of an accident was 1 in 100,000. After Challenger, Probabilistic Risk Analysis (PRA) found a roughly 1 in 100 chance of a Shuttle failure. The recent Orion design uses the safer Apollo approach, with a hardened capsule, launch abort escape, and the crew placed above the rocket tanks and engines. During Apollo it was estimated that, “assuming all elements from propulsion to rendezvous and life support were done as well or better than ever before, that 30 astronauts would be lost before 3 were returned safely to the Earth.” The chance of astronaut survival was only 10%. After the Apollo 1 tragedy, the awareness of risk led to an intense focus on achieving safety. “The only possible explanation for the astonishing success – no losses in space and on time – was that every participant at every level in every area far exceeded the norm of human capabilities.” During Apollo, a NASA PRA found that the chance of success was “less than 5 percent.” The NASA Administrator felt that “the numbers could do irreparable harm,” and discontinued numerical risk assessment. This led to decreasing understanding of risk. The head of Apollo reliability and safety decided, “Statistics don’t count for anything,” and that risk is reduced by “attention taken in design.” The great and initially unexpected success of Apollo appeared to validate the neglect of PRA. Continuing to neglect the mathematical estimation of risk led Shuttle into a high risk design that produced tragic results. The initial design of the Shuttle emphasized increasing capability and reducing cost without analysis or even mention of risk. A retired NASA official stated, “some NASA people began to confuse desire with reality. … One result was to assess risk in terms of what was thought acceptable without regard for verifying the assessment. … Note that under such circumstances real risk management is shut out.” Not computing risk led to removing launch abort, removing crew escape, selecting less reliable Solid Rocket Boosters, placing the crew compartment next to the rocket boosters, and accepting more stressed shielding tile designs. Accepting these specific risks directly caused the shuttle disasters. The Challenger tragedy is frequently taught as a case of management failure. The focus is on the Challenger launch decision hours before, which is a dramatic example of bad management. However, the true cause of the Challenger disaster occurred decades earlier in the Apollo era. When the easily predictable failures occurred, failure investigations focused on how they might have been avoided. The Shuttle was cancelled after the space station was completed because of its high risk. The ultimate cause of the Shuttle tragedies was the choice by the Apollo-era NASA administrator to avoid a negative public reaction to realistic risk analysis.

Harry W. Jones↗

NASA NTRS2021

Development of Near-term Urban Air Mobility Routes and Airspace Integration

Growing interest in Urban Air Mobility (UAM) has been demonstrated by a great deal of investment in related research made by industry, government, and academia. Based on this research effort along with considerations of the maturing concept for UAM airspace integration, a cognitive walkthrough exercise and a human-in-the-loop simulation were conducted with controller subject matter experts (SMEs) to evaluate Dallas-Fort Worth (DFW) current day helicopter routes for near-term use as UAM routes. One of the outcomes of this work is a set of heuristics that should be applied when designing UAM routes in the future. The following heuristics were identified as critical to UAM route design: the proximity of routes to surrounding airports (including approach and departure paths of traditional commercial traffic), the configuration of surrounding airports, avoiding congested or heavily populated areas, avoiding route segments that would go through several sectors, avoiding route segments that would go in and out of Class B airspace, creating routes outside of Class B airspace when able, using routes with two-way, altitude-separated traffic when able, minimizing the length of the route, avoiding commonly placed Temporary Flight Restrictions, and creating Non-Movement Areas or UNICOM Areas. This paper describes each of these identified heuristics and relevant examples based on a human-in-the-loop study conducted using the DFW area airspace.

Urban Air Mobility↗

NASA NTRSDate not supplied

Lunar Excavator Mission Operations using Dynamic Movement Primitives

To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One of these tests is a circular trajectory around the lander while avoiding miscellaneous surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. Here, we introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. After making key changes to the obstacle avoidance formulation, our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.

Space Robotics and Automation↗

NASA NTRSDate not supplied

Advanced Air Mobility Operations & Automation Part II Technical Lecture

The Airborne Collision Avoidance System X (ACAS X) is a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant – referred to as ACAS XR – is designed to accommodate existing helicopter platforms as well as in-development, electric vertical takeoff and landing concepts, which are critical to the emerging concept of operations referred to as Advanced Air Mobility. The fundamental role of ACAS XR is to provide Detect and Avoid (DAA) and/or Collision Avoidance (CA) protection against airborne traffic. DAA alerting and guidance in the context of ACAS XR is caution-level and “suggestive,” and is to be used by the pilot if, and when, they decide to maneuver against an identified threat to DAA “well clear.” The CA alerting, by contrast, is warning-level and “directive,” with the pilot required to comply with the associated guidance to prevent a predicted Near Midair Collision (NMAC). The CA alerts generated by ACAS XR are referred to as Resolution Advisories (RAs) consistent with previous CA systems. Unlike earlier CA systems, ACAS XR issues RAs in the horizontal and vertical dimensions as well as multi-axis RAs (referred to as “Blended” RAs). According to the Minimal Operational Performance Standards of DAA systems for Unmanned Aircraft Systems, maneuvers to comply with RAs may be automated, whereas maneuvers based on DAA alerting assume a manual response. The current presentation discusses two human-in-the-loop simulations that presented rotorcraft pilots with ACAS XR alerts and guidance in eVTOL simulators with varying levels of automation. It also presents overviews of these studies as well as how they assisted live flight tests, which will occur throughout 2023.

air taxis↗

NASA NTRSDate not supplied

A HIRF-Map Certification Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in airspace similar to Transport Category Rotorcraft, requiring them to meet stringent requirements for High-Intensity Radiated Fields (HIRF) certification. The environment is notably severe, particularly compared to fixed-wing aircraft, due to operations at lower altitudes. This potentially exposes the vehicles to high-power transmitters on the ground, leading to significant challenges. High-level HIRF exposure can result in avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF pose significant barriers concerning size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel HIRF protection approach, aiming to reduce costs by certifying vehicles to a "vehicle tolerance level" lower than that required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources. This distance is calculated based on the vehicle's tolerance level and transmitter characteristics, such as transmit power, antenna beamwidth, and direction. Tailored flight maps are developed to identify transmitters and avoidance zones within an operating area or along a flight path, enabling restricted vehicle operations. Vehicles with higher tolerance levels could have smaller HIRF avoidance zones, allowing them to operate closer to transmitters. Transmitter data are sourced from government databases, such as those of the Federal Communications Commission (FCC) and the National Oceanic and Atmospheric Administration (NOAA). A map tool is developed using Matlab to calculate and visualize HIRF avoidance zones based on available databases. The tool determines stand-off distances based on input vehicle tolerance levels, displaying results on various base maps depicting HIRF-restricted areas. Illustrations cover various FCC transmitters, including AM/FM/TV transmitters, satellite earth stations, and NOAA weather radars. The HIRF zones of smaller transmitters, such as land-mobile radios, pagers, microwave links, and cellular towers, are also illustrated. An example of flight planning around transmitters is provided. For now, airports and government-owned lands are excluded due to limited access to sensitive transmitter data. Despite this approach, a minimum HIRF tolerance level for vehicles may still be necessary to cover mobile devices, cellular base stations, transmitters on other AAM vehicles, and other small power devices not included in the FCC databases. The paper discusses findings and areas for improving existing databases and suggests an approach for better access to sanitized data in more restricted government databases. This method significantly deviates from the standard approach and introduces slightly higher flight-planning complexity. However, the potential cost savings are considerable. Future AAM/UAM/UAS aeronautical charts could potentially incorporate these new HIRF avoidance zones. Keywords—HIRF; Map; AAM; UAM; UAS; Advanced Air Mobility; Urban Air Mobility; Unmanned Aerial Systems; Certification.

HIRF↗

NASA NTRS2024

Computing Proximity to Threat Along Uncertain Trajectory to Support Urban Air Mobility

Many airspace threats affect the selection of a flight route, such as terrain, physical obstacles, adverse weather, and special-use airspace, among others. Threat avoidance during Urban Air Mobility (UAM) and Low Altitude Mobility (LAM) flights is especially challenging due to their lower cruising altitudes. These operations may be exposed to buildings, towers, trees, terrain undulations, etc., along much of their flight route. Moreover, these low-altitude flights in urban environments are expected to encounter very busy airspace, increasing the workload associated with threat avoidance. The Proximity to Threat (PtT) function aims to support onboard or remote pilots by computing the risk from geospatial threats in the airspace along an aircraft’s flight path. The threats are both static entities and dynamic airspace restrictions that have been modeled and stored in geo-referenced mapping databases. The flight path may be specified by waypoints, airways, or similar discrete route elements or by a time series of closely spaced position and altitude points. Flight path uncertainty can also be taken into account by assuming both the position and altitude to be sampled from two normal distributions, each being specified by a mean and variance. PtT uses this additional information to verify that the flight path remains clear of threats along a wider path or if a position is reached earlier or later than anticipated, assuring the pilot or operator that there will be an available safety margin even if the aircraft deviates due to one or more occurrences of unexpected wind gusts, mechanical failures, airspeed changes, collision avoidance maneuvers, etc. The client can specify an uncertainty confidence level to bound the set of trajectories evaluated for threats so that the confidence level corresponds to the client’s risk tolerance under the expected conditions. PtT can be used as a pre-flight planning tool to determine a safe route through known threats and in-flight to avoid emerging or changing threats. In this report, we present the PtT function, discuss how the trajectory uncertainty is incorporated into the PtT function, and describe the use of this PtT function in a representative scenario.

urban air mobility↗

DOE OSTI2023

The Mitigation Hierarchy

The mitigation hierarchy is a widely used framework to inform conservation decisions. The hierarchy offers a structured set of steps for how projects can lessen negative impacts or lead to an increase in biodiversity. In its simplest form, the mitigation hierarchy includes three stages: (1) avoid creating impacts from the outset, (2) minimize the impacts that cannot be avoided, and (3) compensate for or offset the impacts that cannot be minimized. Proper application of the hierarchy should decrease impacts of the project over time, such that most of the impact is alleviated through avoidance, leaving a modest amount remaining to minimize, and only a residual to compensate. In practice, avoidance should be prioritized and can be a cost-effective means of mitigation. Whereas compensation should be considered the lowest priority and should only be applied in situations in which the previous mitigation steps were unable to fully alleviate undesirable impacts.

biodiversity↗

DOE OSTI2023

La Jerarquia de Mitigacion (Spanish)

The mitigation hierarchy is a widely used framework to inform conservation decisions. The hierarchy offers a structured set of steps for how projects can lessen negative impacts or lead to an increase in biodiversity. In its simplest form, the mitigation hierarchy includes three stages: (1) avoid creating impacts from the outset, (2) minimize the impacts that cannot be avoided, and (3) compensate for or offset the impacts that cannot be minimized. Proper application of the hierarchy should decrease impacts of the project over time, such that most of the impact is alleviated through avoidance, leaving a modest amount remaining to minimize, and only a residual to compensate. In practice, avoidance should be prioritized and can be a cost-effective means of mitigation. Whereas compensation should be considered the lowest priority and should only be applied in situations in which the previous mitigation steps were unable to fully alleviate undesirable impacts. This is the Spanish translation of NREL/FS-5000-85363, "The Mitigation Hierarchy."

biodiversity↗

NASA NTRS2019

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: ACAS Xu Engineering Analysis Results

This presentation provides an overview of the results from a two-part engineering analysis conducted as part of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. Part one of this analysis examined how to present resolution advisories (RAs) issued by Airborne Collision Avoidance System (ACAS) Xu, which can be in the vertical dimension, the horizontal dimension, or both (i.e., "blended"). The study varied the appearance of the alerting and the verbiage used in the aural alerts. Results revealed high acceptability ratings for the appearance of the RA guidance. Part two of the analysis assessed pilot acceptability of varying levels of automation in the collision avoidance (CA) task. Pilots experienced conditions in which ACAS Xu RAs were executed either manually or automatically (i.e., auto-Collision Avoidance). In some conditions the return to a previously filed course was also executed automatically (auto-Return to Course). Results indicated that improvements are needed to how the state of the automation is presented. Implications of these findings are also discussed.

Detect and Avoid↗

NASA NTRS2020

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due to the complex stochastic environment in which the system operates.As a result, safety validation is not only concerned about whether a failure can occur, but also discovering which failures are most likely to occur. This article presents adaptive stress testing (AST), a framework for finding the most likely path to a failure event in simulation. We consider a general black box setting for partially observable and continuous-valued systems operating in an environment with stochastic disturbances. We formulate the problem as a Markov decision process and use reinforcement learning to optimize it. The approach is simulation-based and does not require internal knowledge of the system, making it suitable for black-box testing of large systems. We present different formulations depending on whether the state is fully observable or partially observable. In the latter case, we present a modified Monte Carlo tree search algorithm that only requires access to the pseudorandom number generator of the simulator to overcome partial observability. We also present an extension of the framework, called differential adaptive stress testing (DAST), that can find failures that occur in one system but not in another. This type of differential analysis is useful in applications such as regression testing, where we are concerned with finding areas of relative weakness compared to a baseline. We demonstrate the effectiveness of the approach on an aircraft collision avoidance application, where a prototype aircraft collision avoidance system is stress tested to find the most likely scenarios of near mid-air collision.

Verification and Validation↗

NASA NTRSDate not supplied

DAA Use Case for Auto Cargo m:N Operations

A detect and avoid use-case was developed to highlight detect and avoid issues associated with m:N operations in the auto cargo domain. This work is being done in conjunction with industry partners and developed for the Operational Scenario and Environmental Description (OSED) for RTCA SC-228. The detect and avoid function is critical, required technology for unmanned aircraft to operation in the national airspace. RTCA SC-228 has published MOPS (phase 1 & 2) detailing the requirements and methods of compliance. This work will help address additional operational aspects of how/when DAA will be employed by unmanned systems. Specifically, this work focuses on “auto cargo” operations. Auto cargo, in this context, refers to regularly scheduled cargo-size aircraft that are flown remotely. The Remote Pilot In Command (RPIC), in this case, is responsible for multiple aircraft, flown simultaneously. The use-case details the use of DAA in this context, the potential issues and gaps that exist.

multi-vehicle control↗