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NASA NTRS2009

Convective Weather Avoidance with Uncertain Weather Forecasts

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

Karahan, Sinan↗

NASA NTRS2013

Evaluation of Flight Deck-Based Interval Management Crew Procedure Feasibility

Air traffic demand is predicted to increase over the next 20 years, creating a need for new technologies and procedures to support this growth in a safe and efficient manner. The National Aeronautics and Space Administration's (NASA) Air Traffic Management Technology Demonstration - 1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The integration of these technologies will increase throughput, reduce delay, conserve fuel, and minimize environmental impacts. The ground-based tools include Traffic Management Advisor with Terminal Metering for precise time-based scheduling and Controller Managed Spacing decision support tools for better managing aircraft delay with speed control. The core airborne technology in ATD-1 is Flight deck-based Interval Management (FIM). FIM tools provide pilots with speed commands calculated using information from Automatic Dependent Surveillance - Broadcast. The precise merging and spacing enabled by FIM avionics and flight crew procedures will reduce excess spacing buffers and result in higher terminal throughput. This paper describes a human-in-the-loop experiment designed to assess the acceptability and feasibility of the ATD-1 procedures used in a voice communications environment. This experiment utilized the ATD-1 integrated system of ground-based and airborne technologies. Pilot participants flew a high-fidelity fixed base simulator equipped with an airborne spacing algorithm and a FIM crew interface. Experiment scenarios involved multiple air traffic flows into the Dallas-Fort Worth Terminal Radar Control airspace. Results indicate that the proposed procedures were feasible for use by flight crews in a voice communications environment. The delivery accuracy at the achieve-by point was within +/- five seconds and the delivery precision was less than five seconds. Furthermore, FIM speed commands occurred at a rate of less than one per minute, and pilots found the frequency of the speed commands to be acceptable at all times throughout the experiment scenarios.

Wilson, Sara R.↗

NASA NTRS2011

Evaluation of an Airborne Spacing Concept, On-Board Spacing Tool, and Pilot Interface

The number of commercial aircraft operations is predicted to increase in the next ten years, creating a need for improved operational efficiency. Two areas believed to offer significant increases in efficiency are optimized profile descents and dependent parallel runway operations. It is envisioned that during both of these types of operations, flight crews will precisely space their aircraft behind preceding aircraft at air traffic control assigned intervals to increase runway throughput and maximize the use of existing infrastructure. This paper describes a human-in-the-loop experiment designed to study the performance of an onboard spacing algorithm and pilots ratings of the usability and acceptability of an airborne spacing concept that supports dependent parallel arrivals. Pilot participants flew arrivals into the Dallas Fort-Worth terminal environment using one of three different simulators located at the National Aeronautics and Space Administration s (NASA) Langley Research Center. Scenarios were flown using Interval Management with Spacing (IM-S) and Required Time of Arrival (RTA) control methods during conditions of no error, error in the forecast wind, and offset (disturbance) to the arrival flow. Results indicate that pilots delivered their aircraft to the runway threshold within +/- 3.5 seconds of their assigned arrival time and reported that both the IM-S and RTA procedures were associated with low workload levels. In general, pilots found the IM-S concept, procedures, speeds, and interface acceptable; with 92% of pilots rating the procedures as complete and logical, 218 out of 240 responses agreeing that the IM-S speeds were acceptable, and 63% of pilots reporting that the displays were easy to understand and displayed in appropriate locations. The 22 (out of 240) responses, indicating that the commanded speeds were not acceptable and appropriate occurred during scenarios containing wind error and offset error. Concerns cited included the occurrence of multiple speed changes within a short time period, speed changes required within twenty miles of the runway, and an increase in airspeed followed shortly by a decrease in airspeed. Within this paper, appropriate design recommendations are provided, and the need for continued, iterative human-centered design is discussed.

Swieringa, Kurt↗

NASA NTRS1997

Probabilistic Analysis of Ground-Holding Strategies

The Ground-Holding Policy Problem (GHPP) has become a matter of great interest in recent years because of the high cost incurred by aircraft suffering from delays. Ground-holding keeps a flight on the ground at the departure airport if it is known it will be unable to land at the arrival airport. The GBPP is determining how many flights should be held on the ground before take-off and for how long, in order to minimize the cost of delays. When the uncertainty associated with airport landing capacity is considered, the GHPP becomes complicated. A decision support system that incorporates this uncertainty, solves the GHPP quickly, and gives good results would be of great help to air traffic management. The purpose of this thesis is to modify and analyze a probabilistic ground-holding algorithm by applying it to two common cases of capacity reduction. A graphical user interface was developed and sensitivity analysis was done on the algorithm, in order to see how it may be implemented in practice. The sensitivity analysis showed the algorithm was very sensitive to the number of probabilistic capacity scenarios used and to the cost ratio of air delay to ground delay. The algorithm was not particularly sensitive to the number of periods that the time horizon was divided into. In terms of cost savings, a ground-holding policy was the most beneficial when demand greatly exceeded airport capacity. When compared to other air traffic flow strategies, the ground-holding algorithm performed the best and was the most consistent under various situations. The algorithm can solve large problems quickly and efficiently on a personal computer.

Sheel, Minakshi↗

NASA NTRS1995

Mode Transitions in Glass Cockpit Aircraft: Results of a Field Study

One consequence of increased levels of automation in complex control systems is the presence of modes. A mode is a particular configuration of a control system that defines how human command inputs are interpreted. In complex systems, modes also often determine a specific allocation of control authority between the human and automated systems. Even in simple static devices (e.g., electronic watches, word processors), the presence of modes has been found to cause problems in either-the acquisition or production of skilled performance. Many of these problems arise due to the fact that the selection of a mode causes device behavior to be mediated by hidden internal state information. For these simple systems, many of these interaction problems can be solved by the design of appropriate feedback to communicate internal state information to the human operator. In complex dynamic systems, however, the design issues associated with modes seem to trancend the problem of merely communicating internal state information via displayed feedback. In complex supervisory control systems (e.g., aircraft, spacecraft, military command and control), a key function of modes is the selection of a particular configuration of control authority between the human operator and automated control systems. One mode may result in full manual control, another may result in a mix of manual and automatic control, while a third may result in full automatic control over the entire system. The human operator selects an appropriate mode as a function of current goals, operating conditions, and operating procedures. Thus, the operator is put in a position of essentially trying to control two coupled dynamic systems: the target system itself, and also a highly complex suite of automation controlling the target system. From a historical perspective, it should probably not come as a surprise that very little information is available to guide the design of mode-oriented control systems. The topic of function allocation (i.e., the proper division of control authority among human and computer) has a long history in human-machine systems research. Although this research has produced some relevant guidelines, a design approach capable of defining appropriate allocations of control function between the human and automation is not yet available. As a result, the function allocation decision itself has been allocated to the operator, to be performed in real-time, in the operation of mode-oriented control systems. A variety of documented aircraft accidents and incidents suggest that the real-time selection and monitoring of control modes is a weak link in the effective operation of complex supervisory control systems. Research in human-machine systems and human-computer interaction has barely scraped the surface of the problem of understanding how operators manage this task.The purpose of this paper is to present the results of a field study which examined how operators manage mode selection in a complex supervisory control system. Data on mode engagements using the Boeing B757/767 auto-flight system were collected during approach and descent into four major airports in the East Coast of the United States. Protocols documenting mode selection, automatic mode changes, pilot actions, quantitative records of flight-path variables, and verbal reports during and after mode engagements were collected by an observer from the jumpseat. Observations were conducted on two typical trips between three airports. Each trip was be replicated 11 times, which yielded a total of 22 trips and 66 legs on which data were collected. All data collected concerned the same flight numbers, and therefore, the same time of day, same type of aircraft, and identical operational environments (e.g., ATC facilities, weather patterns, traffic flow etc.)

Degani, Asaf↗

DOE OSTI2021

Optimal Operations Management of Mobility-on-Demand Systems

The emergence of the sharing economy in urban transportation networks has enabled new fast, convenient and accessible mobility services referred to as Mobilty-on-Demand systems (e.g., Uber, Lyft, DiDi). These platforms have flourished in the last decade around the globe and face many operational challenges in order to be competitive and provide good quality of service. A crucial step in the effective operation of these systems is to reduce customers' waiting time while properly selecting the optimal fleet size and pricing policy. In this paper, we jointly tackle three operational decisions: (i) fleet size, (ii) pricing, and (iii) rebalancing, in order to maximize the platform's profit or its customers' welfare. To accomplish this, we first devise an optimization framework which gives rise to a static policy. Then, we elaborate and propose dynamic policies that are more responsive to perturbations such as unexpected increases in demand. We test this framework in a simulation environment using three case studies and leveraging traffic flow and taxi data from Eastern Massachusetts, New York City, and Chicago. Our results show that solving the problem jointly could increase profits between 1% and up to 50%, depending on the benchmark. Moreover, we observe that the proposed fleet size yield utilization of the vehicles in the fleet is around 75% compared to private vehicle utilization of 5%.

Wollenstein-Betech, Salomón↗

NASA NTRSDate not supplied

Applying Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗

NASA NTRSDate not supplied

Machine Learning Tools for Runway Configuration Decision Support

Runway Configuration Management↗

NASA NTRS2012

Flow Analysis Tool White Paper

Faster networks are continually being built to accommodate larger data transfers. While it is intuitive to think that implementing faster networks will result in higher throughput rates, this is often not the case. There are many elements involved in data transfer, many of which are beyond the scope of the network itself. Although networks may get bigger and support faster technologies, the presence of other legacy components, such as older application software or kernel parameters, can often cause bottlenecks. Engineers must be able to identify when data flows are reaching a bottleneck that is not imposed by the network and then troubleshoot it using the tools available to them. The current best practice is to collect as much information as possible on the network traffic flows so that analysis is quick and easy. Unfortunately, no single method of collecting this information can sufficiently capture the whole endto- end picture. This becomes even more of a hurdle when large, multi-user systems are involved. In order to capture all the necessary information, multiple data sources are required. This paper presents a method for developing a flow analysis tool to effectively collect network flow data from multiple sources and provide that information to engineers in a clear, concise way for analysis. The purpose of this method is to collect enough information to quickly (and automatically) identify poorly performing flows along with the cause of the problem. The method involves the development of a set of database tables that can be populated with flow data from multiple sources, along with an easyto- use, web-based front-end interface to help network engineers access, organize, analyze, and manage all the information.

Boscia, Nichole K.↗

NASA NTRSDate not supplied

An Impedance-Based Complexity Metric for Unmanned Aircraft System Traffic Scenario Classification

This paper introduces an impedance-based metric to capture the complexity of a given unmanned aircraft system traffic scenario. The metric accounts for both the number of aircraft and the traffic flow pattern. The work presented here extends an earlier approach that introduced another scenario complexity metric based on the number of potential conflicts weighted by the conflict resolution cost associated. Complexity measurements for randomly-generated scenarios were produced through high-fidelity fast-time simulations and treated as baseline. Then the impedance based metric was evaluated, for the same scenarios, without the need for an actual flight simulation and a conflict resolution method. The results show that the impedance-based metric has a strong correlation to the baseline data and performs marginally better than the weighted conflict-based complexity metric introduced in the earlier work. The metric computation generates impedance maps which are useful for identifying high complexity regions in a scenario, where flight plan changes might be necessitated. This metric can therefore be used, in conjunction with other complexity metrics, to inform adequate traffic management strategies and classify a traffic scenario as acceptable, unacceptable or acceptable with changes made to flight plans that pass through the high complexity regions. The metric can also be used as a guidance metric for strategic conflict management methods.

Complexity↗

DOE OSTI2024

Study of eVTOL Charging Impact on Airport Electrical Grids

Growth in commercial air traffic has increased the aviation industry's contribution to global emissions. Aircraft electrification can reduce greenhouse gas emissions along with being efficient and reliable. Advanced air mobility introduces the idea of an advanced and more efficient air transportation system. Electric and hybrid aircraft designs, such as electric vertical takeoff and landing (eVTOL), are being considered for a number of applications, such as urban air mobility, cargo delivery, and medical emergencies. Although the electrification of aircraft provides environmental benefits, their charging needs will place significant demand on the electrical grid. This work presents a grid impact study and infrastructure upgrade requirements analysis of eVTOL charging on a realistic distribution grid through power flow simulation analysis. The case study results show that the eVTOL charging can lead to power quality issues, such as undervoltage and equipment capacity overloading. Grid infrastructure, such as lines and transformers, would need to be upgraded, and voltage management strategies would need to be deployed to accommodate eVTOL charging at an existing airport.

advanced air mobility (AAM)↗

NASA NTRS2010

Spinoff 2010

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

Source record↗

NASA NTRS1990

National plan to enhance aviation safety through human factors improvements

The purpose of this section of the plan is to establish a development and implementation strategy plan for improving safety and efficiency in the Air Traffic Control (ATC) system. These improvements will be achieved through the proper applications of human factors considerations to the present and future systems. The program will have four basic goals: (1) prepare for the future system through proper hiring and training; (2) develop a controller work station team concept (managing human errors); (3) understand and address the human factors implications of negative system results; and (4) define the proper division of responsibilities and interactions between the human and the machine in ATC systems. This plan addresses six program elements which together address the overall purpose. The six program elements are: (1) determine principles of human-centered automation that will enhance aviation safety and the efficiency of the air traffic controller; (2) provide new and/or enhanced methods and techniques to measure, assess, and improve human performance in the ATC environment; (3) determine system needs and methods for information transfer between and within controller teams and between controller teams and the cockpit; (4) determine how new controller work station technology can optimally be applied and integrated to enhance safety and efficiency; (5) assess training needs and develop improved techniques and strategies for selection, training, and evaluation of controllers; and (6) develop standards, methods, and procedures for the certification and validation of human engineering in the design, testing, and implementation of any hardware or software system element which affects information flow to or from the human.

Foushee, Clay↗

NASA NTRS2013

Flight Deck Surface Trajectory-based Operations (STBO): Results of Piloted Simulations and Implications for Concepts of Operation (ConOps)

The results offour piloted medium-fidelity simulations investigating flight deck surface trajectory-based operations (STBO) will be reviewed. In these flight deck STBO simulations, commercial transport pilots were given taxi clearances with time and/or speed components and required to taxi to the departing runway or an intermediate traffic intersection. Under a variety of concept of operations (ConOps) and flight deck information conditions, pilots' ability to taxi in compliance with the required time of arrival (RTA) at the designated airport location was measured. ConOps and flight deck information conditions explored included: Availability of taxi clearance speed and elapsed time information; Intermediate RTAs at intermediate time constraint points (e.g., intersection traffic flow points); STBO taxi clearances via ATC voice speed commands or datal ink; and, Availability of flight deck display algorithms to reduce STBO RTA error. Flight Deck Implications. Pilot RTA conformance for STBO clearances, in the form of ATC taxi clearances with associated speed requirements, was found to be relatively poor, unless the pilot is required to follow a precise speed and acceleration/deceleration profile. However, following such a precise speed profile results in inordinate head-down tracking of current ground speed, leading to potentially unsafe operations. Mitigating these results, and providing good taxi RTA performance without the associated safety issues, is a flight deck avionics or electronic flight bag (EFB) solution. Such a solution enables pilots to meet the taxi route RTA without moment-by-moment tracking of ground speed. An avionics or EFB "error-nulling" algorithm allows the pilot to view the STBO information when the pilot determines it is necessary and when workload alloys, thus enabling the pilot to spread his/her attention appropriately and strategically on aircraft separation airport navigation, and the many other flight deck tasks concurrently required. Surface Traffic Management (STM) System Implications. The data indicate a number of implications regarding specific parameters for ATC/STM algorithm development. Pilots have a tendency to arrive at RTA points early with slow required speeds, on time for moderate speeds, and late with faster required speeds. This implies that ATC/STM algorithms should operate with middle-range speeds, similar to that of non-STBO taxi performance. Route length has a related effect: Long taxi routes increase the earliness with slow speeds and the lateness with faster speeds. This is likely due to the" open-loop" nature of the task in which the speed error compounds over a longer time with longer routes. Results showed that this may be mitigated by imposing a small number oftime constraint points each with their own RTAs effectively tuming a long route into a series of shorter routes - and thus improving RTA performance. STBO ConOps Implications. Most important is the impact that these data have for NextGen STM system ConOps development. The results of these experiments imply that it is not reasonable to expect pilots to taxi under a "Full STBO" ConOps in which pilots are expected to be at a predictable (x,y) airport location for every time (t). An STBO ConOps with a small number of intermediate time constraint points and the departing runway, however, is feasible, but only with flight deck equipage enabling the use of a display similar to the "error-nulling algorithm/display" tested.

Foyle, David C.↗

NASA NTRS2010

Proceedings of the Second NASA Formal Methods Symposium

This publication contains the proceedings of the Second NASA Formal Methods Symposium sponsored by the National Aeronautics and Space Administration and held in Washington D.C. April 13-15, 2010. Topics covered include: Decision Engines for Software Analysis using Satisfiability Modulo Theories Solvers; Verification and Validation of Flight-Critical Systems; Formal Methods at Intel -- An Overview; Automatic Review of Abstract State Machines by Meta Property Verification; Hardware-independent Proofs of Numerical Programs; Slice-based Formal Specification Measures -- Mapping Coupling and Cohesion Measures to Formal Z; How Formal Methods Impels Discovery: A Short History of an Air Traffic Management Project; A Machine-Checked Proof of A State-Space Construction Algorithm; Automated Assume-Guarantee Reasoning for Omega-Regular Systems and Specifications; Modeling Regular Replacement for String Constraint Solving; Using Integer Clocks to Verify the Timing-Sync Sensor Network Protocol; Can Regulatory Bodies Expect Efficient Help from Formal Methods?; Synthesis of Greedy Algorithms Using Dominance Relations; A New Method for Incremental Testing of Finite State Machines; Verification of Faulty Message Passing Systems with Continuous State Space in PVS; Phase Two Feasibility Study for Software Safety Requirements Analysis Using Model Checking; A Prototype Embedding of Bluespec System Verilog in the PVS Theorem Prover; SimCheck: An Expressive Type System for Simulink; Coverage Metrics for Requirements-Based Testing: Evaluation of Effectiveness; Software Model Checking of ARINC-653 Flight Code with MCP; Evaluation of a Guideline by Formal Modelling of Cruise Control System in Event-B; Formal Verification of Large Software Systems; Symbolic Computation of Strongly Connected Components Using Saturation; Towards the Formal Verification of a Distributed Real-Time Automotive System; Slicing AADL Specifications for Model Checking; Model Checking with Edge-valued Decision Diagrams; and Data-flow based Model Analysis.

Munoz, Cesar↗

NASA NTRS2014

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Horio, Brant M.↗

NASA NTRS2013

NextGen Flight Deck Surface Trajectory-Based Operations (STBO): Contingency Holds

The purpose of this pilot-in-the-loop taxi simulation was to investigate a NextGen Surface Trajectory-Based Operations (STBO) concept called "contingency holds." The contingency-hold concept parses a taxi route into segments, allowing an air traffic control (ATC) surface traffic management (STM) system to hold an aircraft when necessary for safety. Under nominal conditions, if the intersection or active runway crossing is clear, the hold is removed, allowing the aircraft to continue taxiing without slowing, thus improving taxi efficiency, while minimizing the excessive brake use, fuel burn, and emissions associated with stop-and-go taxi. However, when a potential traffic conflict exists, the hold remains in place as a fail-safe mechanism. In this departure operations simulation, the taxi clearance included a required time of arrival (RTA) to a specified intersection. The flight deck was equipped with speed-guidance avionics to aid the pilot in safely meeting the RTA. On two trials, the contingency hold was not released, and pilots were required to stop. On two trials the contingency hold was released 15 sec prior to the RTA, and on two trials the contingency hold was released 30 sec prior to the RTA. When the hold remained in place, all pilots complied with the hold. Results also showed that when the hold was released at 15-sec or 30-sec prior to the RTA, the 30-sec release allowed pilots to maintain nominal taxi speed, thus supporting continuous traffic flow; whereas, the 15-sec release did not. The contingency-hold concept, with at least a 30-sec release, allows pilots to improve taxiing efficiency by reducing braking, slowing, and stopping, but still maintains safety in that no pilots "busted" the clearance holds. Overall, the evidence suggests that the contingency-hold concept is a viable concept for optimizing efficiency while maintaining safety.

NextGen↗

DOE OSTI2025

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. About one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States happen at traffic intersections . Effective management of these intersections is important to ensure safety and efficiency of all users - vehicles, pedestrians, cyclists, and vulnerable road users (VRUs). With advancements in sensor perception technologies such as radar, light detection and ranging (lidar), and cameras, traffic intersections are developing into dynamic and data-rich environments. By using these data to create a real-time digital twin, we can enable real-time data-driven decision making and a range of applications such as sharing perception information to connected vehicles (CVs) and connected autonomous vehicles (CAVs), safety affirmative signaling, and curb optimizing to improve efficiency and enhance safety.This paper presents an overview of the concept and examines the challenges involved in implementing an infrastructure-based cooperative perception engine at a traffic intersection. In addition to outlining the physical components, this study also addresses important challenges involved in a multi-sensor system. We present results from deploying the National Renewable Energy Laboratory's (NREL's) Infrastructure Perception and Control (IPC) mobile trailer at a traffic intersection in the city of Colorado Springs, Colorado, USA that employed multiple radars and lidars to capture the data. This study provides necessary practical learning for the Cooperative Driving Automation (CDA) and traffic engineering communities for next-generation infrastructure-based cooperative perception that promises improvements in signal control for optimized traffic flow, among other applications, and documents findings for ongoing research and development efforts in other areas.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗