Results for “Conflict Management” — Page 8

NASA NTRS2016

Considerations in Managing the Fill Rate of the Grand Ethiopian Renaissance Dam Reservoir Using a System Dynamics Approach.

The purpose of this study is to evaluate simulated fill rate scenarios for the Grand Ethiopian Renaissance Dam while taking into account plausible climate change outcomes for the Nile River Basin. The region lacks a comprehensive equitable water resource management strategy, which creates regional security concerns and future possible conflicts. We employ climate estimates from 33 general circulation models within a system dynamics model as a step in moving toward a feasible regional water resource management strategy. We find that annual reservoir fill rates of 8-15% are capable of building hydroelectric capacity in Ethiopia while concurrently ensuring a minimum level of stream flow disruption into Egypt before 2039. Insofar as climate change estimates suggest a modest average increase in stream flow into the Aswan, climate changes through 2039 are unlikely to affect the fill rate policies. However, larger fill rates will have a more detrimental effect on stream flow into the Aswan, particularly beyond a policy of 15%. While this study demonstrates that a technical solution for reservoir fill rates is feasible, the corresponding policy challenge is political. Implementation of water resource management strategies in the Nile River Basin specifically and Africa generally will necessitate a national and regional willingness to cooperate.

system dynamics↗

NASA NTRS1999

A Simple Two Aircraft Conflict Resolution Algorithm

Conflict detection and resolution methods are crucial for distributed air-ground traffic management in which the crew in the cockpit, dispatchers in operation control centers and air traffic controllers in the ground-based air traffic management facilities share information and participate in the traffic flow and traffic control imctions.This paper describes a conflict detection and a conflict resolution method. The conflict detection method predicts the minimum separation and the time-to-go to the closest point of approach by assuming that both the aircraft will continue to fly at their current speeds along their current headings. The conflict resolution method described here is motivated by the proportional navigation algorithm. It generates speed and heading commands to rotate the line-of-sight either clockwise or counter-clockwise for conflict resolution. Once the aircraft achieve a positive range-rate and no further conflict is predicted, the algorithm generates heading commands to turn back the aircraft to their nominal trajectories. The speed commands are set to the optimal pre-resolution speeds. Six numerical examples are presented to demonstrate the conflict detection and resolution method.

Chatterji, Gano B.↗

NASA NTRS2003

Providing Effective Access to Shared Resources: A COIN Approach

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user's satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and 'aligned' with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the COllective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Airiau, Stephane↗

NASA NTRS2004

Providing Effective Access to Shared Resources: A COIN Approach

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user s satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and "aligned" with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the Collective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Airiau, Stephane↗

NASA NTRS2011

State-Based Implicit Coordination and Applications

In air traffic management, pairwise coordination is the ability to achieve separation requirements when conflicting aircraft simultaneously maneuver to solve a conflict. Resolution algorithms are implicitly coordinated if they provide coordinated resolution maneuvers to conflicting aircraft when only surveillance data, e.g., position and velocity vectors, is periodically broadcast by the aircraft. This paper proposes an abstract framework for reasoning about state-based implicit coordination. The framework consists of a formalized mathematical development that enables and simplifies the design and verification of implicitly coordinated state-based resolution algorithms. The use of the framework is illustrated with several examples of algorithms and formal proofs of their coordination properties. The work presented here supports the safety case for a distributed self-separation air traffic management concept where different aircraft may use different conflict resolution algorithms and be assured that separation will be maintained.

Narkawicz, Anthony J.↗

NASA NTRS2006

A Simple Two Aircraft Conflict Resolution Algorithm

Conflict detection and resolution methods are crucial for distributed air-ground traffic management in which the crew in, the cockpit, dispatchers in operation control centers sad and traffic controllers in the ground-based air traffic management facilities share information and participate in the traffic flow and traffic control functions. This paper describes a conflict detection, and a conflict resolution method. The conflict detection method predicts the minimum separation and the time-to-go to the closest point of approach by assuming that both the aircraft will continue to fly at their current speeds along their current headings. The conflict resolution method described here is motivated by the proportional navigation algorithm, which is often used for missile guidance during the terminal phase. It generates speed and heading commands to rotate the line-of-sight either clockwise or counter-clockwise for conflict resolution. Once the aircraft achieve a positive range-rate and no further conflict is predicted, the algorithm generates heading commands to turn back the aircraft to their nominal trajectories. The speed commands are set to the optimal pre-resolution speeds. Six numerical examples are presented to demonstrate the conflict detection, and the conflict resolution methods.

Chatterji, Gano B.↗

DOE OSTI2022

Integration of Microgrids, DER Aggregators, and DERMS with ADMS

Distributed energy resource (DER) management and control is disjointed, siloed, and at times conflicting. Behind-the-meter (BTM) assets can provide significant flexibility but are poorly integrated with the grid. Centralized control methods alone are not scalable. The objective is to develop and demonstrate an architecture that: provides reliable, resilient, and secure grid services; enables scalable, near-real-time management of utility- and small-scale DERs; supports transactive control, aggregation, and direct control of DERs; and incorporates existing utility management systems.

ADMS↗

NASA NTRS2010

Conflict Resolution Automation and Pilot Situation Awareness

This study compared pilot situation awareness across three traffic management concepts. The Concepts varied in terms of the allocation of traffic avoidance responsibility between the pilot on the flight deck, the air traffic controllers, and a conflict resolution automation system. In Concept 1, the flight deck was equipped with conflict resolution tools that enable them to fully handle the responsibility of weather avoidance and maintaining separation between ownship and surrounding traffic. In Concept 2, pilots were not responsible for traffic separation, but were provided tools for weather and traffic avoidance. In Concept 3, flight deck tools allowed pilots to deviate for weather, but conflict detection tools were disabled. In this concept pilots were dependent on ground based automation for conflict detection and resolution. Situation awareness of the pilots was measured using online probes. Results showed that individual situation awareness was highest in Concept 1, where the pilots were most engaged, and lowest in Concept 3, where automation was heavily used. These findings suggest that for conflict resolution tasks, situation awareness is improved when pilots remain in the decision-making loop.

Dao, Arik-Quang V.↗

NASA NTRS2009

Complexity Science Applications to Dynamic Trajectory Management: Research Strategies

The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.

Sawhill, Bruce↗

NASA NTRS2014

A Novel Application of TMA to Converging Runway Operations in a Simulated NextGen Environment

In 2013, the Airspace Operations Laboratory at NASA Ames Research Center conducted a human-in-the-loop simulation that examined the feasibility of applying a number of Next Generation Air Transportation System (NextGen) solutions to complex arrival operations in and around the New York metroplex. The delivery of arrivals to Newark Liberty International Airport (EWR) was the focus of this simulation, which involved extending the Terminal Sequencing and Spacing (TSS) scheduling capability to precisely schedule arrivals to intersecting runways 22 Left and 11. An important enabler for the concept was the availability of a dependent runway scheduler that was able to coordinate arrival times between aircraft landing on intersecting runways. At the time of the study, there was no functionality within the TSS scheduler to automatically create the dependent runway schedules. Instead, a Traffic Management Coordinator (TMC) manually created a de-conflicted schedule, which allowed for the concept to be tested as well as provided valuable insight into the tool requirements for a dependent runway scheduler. Throughout the course of preparations for the simulation, the individual serving as the TMC developed a number of strategies and procedures for manually adjusting the Scheduled Time of Arrival (STA) of the EWR arrivals in order to ensure that adequate spacing was provided between runway 22L and 11 arrival pairs. This paper describes the strategies and procedures that were developed and details how they were successfully applied during the simulation. Results will also be presented that shed additional light on exactly how the schedules were manipulated and their impact on delivery performance and safety. Ideas for additional TSS enhancements and next steps, based on participant feedback, will also be presented.

Homola, Jeffrey↗

NASA NTRSDate not supplied

Parametric Study of Federated Conflict Resolution for UAM Operations

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗

NASA NTRSDate not supplied

Parametric Study of Federated Conflict Resolution for UAM Operations using DOE Analysis

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗

NASA NTRSDate not supplied

Intent Modeling and Intent Conflict Probability Calculation for Operations in Upper Class E Airspace

This work presents probabilistic intent models for two typical vehicles in ETM operational environment. Several methods, including analytical methods for approximated solutions and a numerical method for exact solution, are presented and applied to compute the intent conflict probability for ETM operations. A comparison of these methods will be conducted in the final paper. Furthermore, simulations will be performed to verify the probabilistic intent model and verify the results of intent conflict probability from different methods.

Operational intent↗

NASA NTRS2020

Massachusetts Water Resources: Assessing Flood Events Resulting from North American Beaver Reintroduction with NASA Earth Observations to Inform Biodiversity and Infrastructure Management

North American beavers (Castor canadensis) are returning to Massachusetts after overhunting decimated their populations in the 1700s. Current regulations have allowed this species to recolonize, resulting in increasingly prevalent human-beaver conflicts. These ecosystem engineers can quickly change their environment through the creation of dams, leading to floods that can adversely affect human infrastructures, such as basements, roads, or septic systems. Conversely, beaver dams can positively influence their environment, modifying the physical and chemical properties of streams and providing crucial habitats to a variety of wildlife. The 2020 Spring Boston NASA DEVELOP team collaborated with the Massachusetts Audubon Society to support their efforts in monitoring beaver impacts and managing human-beaver conflicts. The project-utilized data from Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager to map the spectral signature created from beaver-induced flooding. The team created a tool called Beaver-Flood Event Detector (B-FED) in Google Earth Engine using imagery from 1985 to 2019. Ancillary datasets were incorporated into B-FED that allow the tool to highlight flood events in wetland areas and in situ observations of beaver presence. Beaver observations in or near flooded areas indicated likelihood that the flood was beaver induced. Time series and animations were also produced to display key regions of landscape change across Massachusetts. B-FED will allow the partner to identify and assess potential ecosystem changes and infrastructural impacts from beavers across Massachusetts and inform future management practices.

Water Resources↗

NASA NTRS2020

Massachusetts Water Resources: Assessing Flood Events Resulting from North American Beaver Reintroduction with NASA Earth Observations to Inform Biodiversity and Infrastructure Management

North American beavers (Castor canadensis) are returning to Massachusetts after overhunting decimated their populations in the 1700s. Current regulations have allowed this species to recolonize, resulting in increasingly prevalent human-beaver conflicts. These ecosystem engineers can quickly change their environment through the creation of dams, leading to floods that can adversely affect human infrastructures, such as basements, roads, or septic systems. Conversely, beaver dams can positively influence their environment, modifying the physical and chemical properties of streams and providing crucial habitats to a variety of wildlife. The 2020 Spring Boston NASA DEVELOP team collaborated with the Massachusetts Audubon Society to support their efforts in monitoring beaver impacts and managing human-beaver conflicts. The project-utilized data from Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager to map the spectral signature created from beaver-induced flooding. The team created a tool called Beaver-Flood Event Detector (B-FED) in Google Earth Engine using imagery from 1985 to 2019. Ancillary datasets were incorporated into B-FED that allow the tool to highlight flood events in wetland areas and in situ observations of beaver presence. Beaver observations in or near flooded areas indicated likelihood that the flood was beaver induced. Time series and animations were also produced to display key regions of landscape change across Massachusetts. B-FED will allow the partner to identify and assess potential ecosystem changes and infrastructural impacts from beavers across Massachusetts and inform future management practices

Water Resources↗

NASA NTRS2009

Analysis of Automated Aircraft Conflict Resolution and Weather Avoidance

This paper describes an analysis of using trajectory-based automation to resolve both aircraft and weather constraints for near-term air traffic management decision making. The auto resolution algorithm developed and tested at NASA-Ames to resolve aircraft to aircraft conflicts has been modified to mitigate convective weather constraints. Modifications include adding information about the size of a gap between weather constraints to the routing solution. Routes that traverse gaps that are smaller than a specific size are not used. An evaluation of the performance of the modified autoresolver to resolve both conflicts with aircraft and weather was performed. Integration with the Center-TRACON Traffic Management System was completed to evaluate the effect of weather routing on schedule delays.

Love, John F.↗

NASA NTRS1990

A conflict analysis of 4D descent strategies in a metered, multiple-arrival route environment

A conflict analysis was performed on multiple arrival traffic at a typical metered airport. The Flow Management Evaluation Model (FMEM) was used to simulate arrival operations using Denver Stapleton's arrival route structure. Sensitivities of conflict performance to three different 4-D descent strategies (clear-idle Mach/Constant AirSpeed (CAS), constant descent angle Mach/CAS and energy optimal) were examined for three traffic mixes represented by those found at Denver Stapleton, John F. Kennedy and typical en route metering (ERM) airports. The Monte Carlo technique was used to generate simulation entry point times. Analysis results indicate that the clean-idle descent strategy offers the best compromise in overall performance. Performance measures primarily include susceptibility to conflict and conflict severity. Fuel usage performance is extrapolated from previous descent strategy studies.

Izumi, K. H.↗

DOE OSTI2022

Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (50 m) and wind conditions are known at facility scale (3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio 1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

17 WIND ENERGY↗