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Statistical Engineering in Air Traffic Management Research

NASA is working to develop an integrated set of advanced technologies to enable efficient arrival operations in high-density terminal airspace for the Next Generation Air Transportation System. This integrated arrival solution is being validated and verified in laboratories and transitioned to a field prototype for an operational demonstration at a major U.S. airport. Within NASA, this is a collaborative effort between Ames and Langley Research Centers involving a multi-year iterative experimentation process. Designing and analyzing a series of sequential batch computer simulations and human-in-the-loop experiments across multiple facilities and simulation environments involves a number of statistical challenges. Experiments conducted in separate laboratories typically have different limitations and constraints, and can take different approaches with respect to the fundamental principles of statistical design of experiments. This often makes it difficult to compare results from multiple experiments and incorporate findings into the next experiment in the series. A statistical engineering approach is being employed within this project to support risk-informed decision making and maximize the knowledge gained within the available resources. This presentation describes a statistical engineering case study from NASA, highlights statistical challenges, and discusses areas where existing statistical methodology is adapted and extended.

Wilson, Sara R.↗

Optimal Eco-Driving Control of Connected and Autonomous Vehicles Through Signalized Intersections

This article focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized intersections on the road is considered. The eco-driving problem is formulated as a data-driven chance-constrained robust optimization problem. Effective red-light duration (ERD) is defined as a random variable, and describes the feasible passing time through the signalized intersections. Usually, the true probability distribution for ERD is unknown. Consequently, a data-driven approach is adopted to formulate chance constraints based on empirical sample data. This incorporates robustness into the eco-driving control problem with respect to uncertain signal timing. Dynamic programming (DP) is employed to solve the optimization problem. The simulation results demonstrate that the proposed method can generate optimal speed reference trajectories with 40% less vehicle fuel consumption, while maintaining the arrival time at a similar level compared to a modified intelligent driver model (IDM). The proposed control approach significantly improves the controller's robustness in the face of uncertain signal timing, without requiring to know the distribution of the random variable a priori.

33 ADVANCED PROPULSION SYSTEMS↗

Offline Arterial Signal Timing Optimization for Closely Spaced Intersections

The stop-and-go driving behavior at a busy arterial causes a significant amount of fuel waste and emissions that could be reduced. For closely spaced intersections, the traditional bottom-up signal timing approach could fail under high volumes when the queues reach the upstream intersections. A well-coordinated arterial should manage the queue length to prevent the control from failing. Traditionally, coordination among signalized intersections for an arterial means finding the good offsets for each intersection. The control of the intersections along an arterial can also be coordinated by optimizing splits. Splits impact the capacity of an intersection. Similar to the highway, the capacity drop could cause growing queues. This work is based on the Virtual Phase-Link (VPL) model, a street traffic model designed for online traffic model predictive control, to obtain a top-down offline arterial signal timing. The VPL-based model can guarantee capacity consistency in intersections along an arterial. We, therefore, adopted the VPL-based model and developed an offline signal timing optimization approach. The proposed timing derived from the VPL-based offline signal timing optimization showed very good results in simulation. We also collected field experiment data, which demonstrated overall energy reductions and speed improvements on some sections of the study arterial.

47 OTHER INSTRUMENTATION↗

Situation Awareness Implications of Adaptive Automation of Air Traffic Controller Information Processing Functions

The goal of this research was to define a measure of situation awareness (SA) in an air traffic control (ATC) task and to assess the influence of adaptive automation (AA) of various information processing functions on controller perception, comprehension and projection. The measure was also to serve as a basis for defining and developing an approach to triggering dynamic control allocations, as part of AA, based on controller SA. To achieve these objectives, an enhanced version of an ATC simulation (Multitask (copyright)) was developed for use in two human factors experiments. The simulation captured the basic functions of Terminal Radar Approach Control (TRACON) and was capable of presenting to operators four different modes of control, including information acquisition, information analysis, decision making and action implementation automation, as well as a completely manual control mode. The SA measure that was developed as part of the research was based on the Situation Awareness Global Assessment Technique (SAGAT), previous goal-directed task analyses of enroute control and TRACON, and a separate cognitive task analysis on the ATC simulation. The results of the analysis on Multitask were used as a basis for formulating SA queries as part of the SAGAT-based approach to measuring controller SA, which was used in the experiments. A total of 16 subjects were recruited for both experiments. Half the subjects were used in Experiment #1, which focused on assessing the sensitivity and reliability of the SA measurement approach in the ATC simulation. Comparisons were made of manual versus automated control. The remaining subjects were used in the second experiment, which was intended to more completely describe the SA implications of AA applied to specific controller information processing functions, and to describe how the measure could ultimately serve as a trigger of dynamic function allocations in the application of AA to ATC. Comparisons were made of the sensitivity of the SA measure to automation manipulations impacting both higher-order information processing functions, such as information analysis and decision making, versus lower-order functions, including information acquisition and action implementation. All subjects were exposed to all forms of AA of the ATC task and the manual control condition. The approach to AA used in both experiments was to match operator workload, assessed using a secondary task, to dynamic control allocations in the primary task. In total, the subjects in each experiment participated in 10 trials with each lasting between 45 minutes and 1 hour. In both experiments, ATC performance was measured in terms of aircraft cleared, conflicting, and collided. Secondary task (gauge monitoring) performance was assessed in terms of a hit-to-signal ratio. As part of the SA measure, three simulation freezes were conducted during each trial to administer queries on Level 1, 2, and 3 SA.

Kaber, David B.↗

Control of Future Air Traffic Systems via Complexity Bound Management

The complexity of the present system for managing air traffic has led to "discreteness" in approaches to creating new concepts: new concepts are created as point designs, based on experience, expertise, and creativity of the proposer. Discrete point designs may be highly successful but they are difficult to substantiate in the face of equally strong substantiation of competing concepts, as well as the state of the art in concept evaluation via simulations. Hybrid concepts may present a compromise - the golden middle. Yet a hybrid of sometimes in principle incompatible concepts forms another point design that faces the challenge of substantiation and validation. We are faced with the need to re-design the air transportation system ab initio. This is a daunting task, especially considering the problem of transitioning from the present system to any fundamentally new system. However, design from scratch is also an opportunity to reconsider approaches to new concept development. In this position paper we propose an approach, Optimized Parametric Functional Design, for systematic development of concepts for management and control of airspace systems, based on optimization formulations in terms of required system functions and states. This reasoning framework, realizable in the context of ab initio system design, offers an approach to deriving substantiated airspace management and control concepts. With growing computational power, we hope that the approach will also yield a methodology for actual dynamic control of airspace

Alexandrov, Natalia↗

Precision Arrival Scheduling for Tactical Reconfiguration

This research adapts the concept of precision arrival scheduling to accommodate reconfiguration operations between two sets of fixed arrival routes modeled for Chicago O'Hare International Airport (ORD). Integrated fixed path routing from en-route to runways was modeled for ORD's top two peak traffic configurations, as well as transition routing between the two configurations. A first-come-first-served multi-point scheduler was adapted to the reconfiguration problem by prioritizing the rescheduling of aircraft within the terminal airspace at the time of reconfiguration notification. Arrival rescheduling was then tested for a range of arrival rates and reconfiguration notification lead-times in fasttime simulation. Reconfigurations with lead-times as short as 10 minutes at a nominal static configuration arrival rate (~25 arrivals per quarter hour) could be accommodated with little impact to throughput. However, as lead-time shortened below 25 minutes, individual aircraft efficiency quickly degraded due to extra flight time at lower altitude and speed. In general, first-come-first-served arrival scheduling on fixed routing for this sample reconfiguration problem is promising if at least 10-15 minutes lead-time is given before the reconfiguration is in effect.

airport reconfiguration↗

Obtaining Public Opinion about sUAS Activity in an Urban Environment

The Unmanned Aircraft Systems (UAS) Traffic Management (UTM) research project has been developing and testing concept ideas for enabling small UAS (sUAS) operations in low altitude airspace (ground to 400 feet). To do this, a series of flight test demonstrations were organized over five years at seven test sites. Technology Capability Level-4 (TCL4), the most complex flight tests, were conducted in Texas, USA, during August 2019. This testing resulted in over 400 data collection flights using eight live rotorcraft, with nine flight crews flying pre-planned scenarios in the urban downtown and waterfront areas of Corpus Christi, Texas. Test scenarios were designed to include a variety of elements, including live and simulated vehicles, and personnel in many different roles, including flight crews and mission personnel. One group of people who did not have a role in the flight tests but will be affected by UAS operations as they become more ubiquitous, are the general public. What do the public think about sUAS operations in urban areas? In order to obtain a reference point that noted the public's view of the operations in the TCL4 demonstration, a short survey was developed and offered to members of the public who wished to comment on the sUAS activities they saw in their city during two weeks in August, 2019.Forty five people completed the online public opinion survey. Participants volunteered to take it, creating a self-selected sample. The survey included eleven questions that asked participants about their level of comfort and concerns with UAS activity; their knowledge of UAS operations; and, whether a traffic management system like UTM would increase their confidence in urban UAS activity. The general public in Corpus Christi showed a good level of knowledge of sUAS regulations, with almost half of their responses to the knowledge portion of the survey being correct. They expressed a moderate level of concern (x = 4.7 out of 7) at urban sUAS activity and, of those who cited a concern, the majority reported this was about privacy (54%), which are all responses in line with those reported in earlier research on public opinion. Views on UTM were mixed, with respondents indicating they thought the introduction of UTM will improve safety somewhat (5.2 out of 7) but it will also increase their concern a little (4.6 out of 7). This would indicate there needs to be more information and educational material about the UTM concept made available to the public with the aim to reduce public concerns about the system.

Caterina Grossi↗

Dynamically-allocated multi-queue buffers for VLSI communication switches

Several buffer structures are discussed and compared in terms of implementation complexity, interswitch handshaking requirements, and their ability to deal with variations in traffic patterns and message lengths. A new design of buffers is presented that provide non-FIFO message handling and efficient storage allocation for variable size packets using linked lists managed by a simple on-chip controller. The new buffer design is evaluated by comparing it to several alternative designs in the context of a multistage interconnection network. The present modeling and simulations show that the new buffer outperforms alternative buffers and can thus be used to improve the performance of a wide variety of systems currently using less efficient buffers.

Tamir, Yuval↗

The System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO)

NASA's Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to leverage Unmanned Aerial Systems (UAS) and UAS Traffic Management (UTM) to improve asset coordination and overall emergency response. One application of STEReO is wildfire response, which is the focus of this research. In order to implement the operations described in the STEReO project, these additions must have tangible benefits and proven safety. To this end, the System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO) project constructs a simulation model, developed through the Python modeling and resiliency analysis package fmdtools. The model describes wildfire response operations, including current operational concepts and emerging concepts utilizing UAS as described in STEReO. While previous simulation models focus primarily on fire propagation with some models including emergency response intervention, SMART-STEReO evaluates the system performance and resilience benefits gained by the addition of UAS and UTM. Due to the novelty and complexity of the model, initial model verification and validation efforts are conducted and a detailed description of the model is provided. Preliminary results from experimental analysis on the SMARt-STEReO model indicate that when compared to current operations, the addition of UAS in wildfire operations results in improved response efforts, in terms of fewer acres burned, as well as improved system resilience in response to a given fault.

Sequoia Andrade↗

Streaming Instability with Multiple Dust Species – II. Turbulence and Dust–Gas Dynamics at Non-Linear Saturation

The streaming instability is a fundamental process that can drive dust–gas dynamics and ultimately planetesimal formation inprotoplanetary discs. As a linear instability, it has been shown that its growth with a distribution of dust sizes can be classifiedinto two distinct regimes, fast- and slow-growth, depending on the dust-size distribution and the total dust-to-gas density ratio. Using numerical simulations of an unstratified disc, we bring three cases in different regimes into non-linear saturation. Wefind that the saturation states of the two fast-growth cases are similar to its single-species counterparts. The one with maximumdimensionless stopping timeτs,max=0.1 and=2 drives turbulent vertical dust–gas vortices, while the other withτs,max=2and=0.2 leads to radial traffic jams and filamentary structures of dust particles. The dust density distribution for the former isflat in low densities, while the one for the latter has a low-end cut-off. By contrast, the one slow-growth case results in a virtuallyquiescent state. Moreover, we find that in the fast-growth regime, significant dust segregation by size occurs, with large particlesmoving towards dense regions while small particles remain in the diffuse regions, and the mean radial drift of each dust speciesis appreciably altered from the (initial) drag-force equilibrium. The former effect may skew the spectral index derived frommultiwavelength observations and change the initial size distribution of a pebble cloud for planetesimal formation. The latteralong with turbulent diffusion may influence the radial transport and mixing of solid materials in young protoplanetary discs.

Chao-chin Yang↗

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗

Obtaining Public Opinion About sUAS Activity in an Urban Environment

The Unmanned Aircraft Systems (UAS) Traffic Management (UTM) research project has been developing and testing concept ideas for enabling small UAS (sUAS) operations in low altitude airspace (ground to 400 feet). To do this, a series of flight test demonstrations were organized over five years at seven test sites. Technology Capability Level-4 (TCL4), the most complex flight tests, were conducted in Texas, USA, during August 2019. This testing resulted in over 400 data collection flights using eight live rotorcraft, with nine flight crews flying pre-planned scenarios in the urban downtown and waterfront areas of Corpus Christi, Texas. Test scenarios were designed to include a variety of elements, including live and simulated vehicles, and personnel in many different roles, including flight crews and mission personnel. One group of people who did not have a role in the flight tests but will be affected by UAS operations as they become more ubiquitous, are the general public. What do the public think about sUAS operations in urban areas? In order to obtain a reference point that noted the public’s view of the operations in the TCL4 demonstration, a short survey was developed and offered to members of the public who wished to comment on the sUAS activities they saw in their city during two weeks in August, 2019. Forty five people completed the online public opinion survey. Participants volunteered to take it, creating a self-selected sample. The survey included eleven questions that asked participants about their level of comfort and concerns with UAS activity; their knowledge of UAS operations; and, whether a traffic management system like UTM would increase their confidence in urban UAS activity. The general public in Corpus Christi showed a good level of knowledge of sUAS regulations, with almost half of their responses to the knowledge portion of the survey being correct. They expressed a moderate level of concern (x = 4.7 out of 7) at urban sUAS activity and, of those who cited a concern, the majority reported this was about privacy (54%), which are all responses in line with those reported in earlier research on public opinion. Views on UTM were mixed, with respondents indicating they thought the introduction of UTM will improve safety somewhat (5.2 out of 7) but it will also increase their concern a little (4.6 out of 7). This would indicate there needs to be more information and educational material about the UTM concept made available to the public with the aim to reduce public concerns about the system.

UTM↗

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗

The Impact of Integrated Maneuver Guidance Information on UAS Pilots Performing the Detect and Avoid Task

The integrated human-in-the-loop (iHITL) simulation examined the effect of four different Detect-and-Avoid (DAA) display concepts on unmanned aircraft system (UAS) pilots' ability to maintain safe separation. The displays varied in the type and amount of guidance they provided to pilots. The study's background and methodology are discussed, followed by the 'measured response' data (i.e., pilots' end-to-end response time in reacting to traffic alerts on their DAA display). Results indicate that display type had a significant impact on how long pilot's spent interacting with the interface (i.e., edit times).

detect and avoid↗

A Queuing Theory Approach to Pilot-Controller Coordination for m:N Operations

In recent years, attention and interest by industry and researchers has grown in a control paradigm for remotely piloted aircraft termed “m:N operations.” In an m:N operation, a team of m remote pilots in command (RIPCs) collaboratively manage the flights of N aircraft. A consequence of an m:N concept of operations is that the RPICs will have to switch attention from one aircraft to another and from one task to another. Previous research in m:N operations has focused on the workload experienced by an RPIC and their level of situation awareness on their flights. Researchers have found that RPIC workload and situation awareness are generally sensitive to increasing N, although NASA’s Multi-Vehicle (m:N) Working Group has suggested that the driver of workload/situation awareness is the number of exceptions requiring human intervention as opposed to the value of N itself. In any case, a natural antecedent of workload is task load. In this paper, queueing theory is applied to a 1:N Urban Air Mobility (UAM) air taxi operation in order to estimate pilot task load for managing radio communications with air traffic controllers (ATCs) under increasing N. An M/M/1 queueing system is used to model the RIPC’s servicing of calls and clearance requests (e.g., departure, arrival, or airspace transition) to ATC for the N aircraft. Important parameters for the queueing model are the task arrival rate and the average service time for task completion. Radio communication times from past human-in-the-loop simulation studies are used to measure service times for a 1:4 and 1:12 UAM operation and to interpolate service times for 4 < N < 12. A Monte Carlo method is then employed, using the measured and interpolated service times, to estimate arrival rate and related queueing statistics. The paper concludes by considering the estimated queuing statistics, particularly the RPIC’s utilization (i.e., proportion of time actively servicing tasks), the length of the task queue over time, and the implications for task-balanced system design.

task load↗

A Method for Scheduling Air Traffic with Uncertain En Route Capacity Constraints

A method for scheduling ground delay and airborne holding for flights scheduled to fly through airspace with uncertain capacity constraints is presented. The method iteratively solves linear programs for departure rates and airborne holding as new probabilistic information about future airspace constraints becomes available. The objective function is the expected value of the weighted sum of ground and airborne delay. In order to limit operationally costly changes to departure rates, they are updated only when such an update would lead to a significant cost reduction. Simulation results show a 13% cost reduction over a rough approximation of current practices. Comparison between the proposed as needed replanning method and a similar method that uses fixed frequency replanning shows a typical cost reduction of 1% to 2%, and even up to a 20% cost reduction in some cases.

Arneson, Heather↗

A Web-Based Negotiation Tool for Conflict Resolution in Upper Class E Traffic Management

In Upper Class E airspace 60,000 feet (or Flight level / FL600), vehicles such as High Altitude Long Endurance (HALE) balloons and slow fixed-wing gliders have diverse vehicle characteristics and limited maneuverability. Due to these unique characteristics of high-altitude operations, a new type of strategic negotiation-based conflict resolution method has been proposed to avoid potential conflict between vehicles in Upper Class E airspace, well in advance of the conflict point and with ample time for bilateral negotiation. This paper introduces the first real-time web-based negotiation tool for high-altitude operations. To facilitate negotiation, this tool incorporates a bilateral negotiation model with an algorithm to assess conflict risks and generate new flight trajectories with a given flight path deviation. This tool allows users to make decisions during negotiation manually and automatically while enforcing the needed constraints for negotiation to be successful. Operators can make decisions at every step while they interact with each other on separate devices. To conduct sensitivity analysis, a mechanism that automates human inputs to the user interface is also developed for this web-based negotiation tool, such that fast-time simulations can be constructed and used to explore various scenarios to gain insights into this web-based negotiation model. Using this tool, a study was conducted to evaluate the impact of different negotiation strategies, vehicle types, vehicle crossing angles, and operator response times during the negotiations on metrics such as total negotiation completion time, number of negotiation rounds, and extra flight distance to avoid the conflict due to negotiation, compared to ones without negotiation. The results suggest that operators benefit from using negotiated flight paths with quick response times, across various crossing angles and vehicle types. Various Negotiation Strategies are investigated to simulate the behaviors associated with different types of negotiations. The findings demonstrate that, in comparison to the conventional method where a single operator assumes full responsibility, negotiation-based strategic deconfliction reduces the total extra flight distance by an average of 24% - 27%. On an individual basis, each operator may be able to save an average of 65% of their extra flight distance.

Upper Class E Traffic Management (ETM)↗

Synthesized speech rate and pitch effects on intelligibility of warning messages for pilots

In civilian and military operations, a future threat-warning system with a voice display could warn pilots of other traffic, obstacles in the flight path, and/or terrain during low-altitude helicopter flights. The present study was conducted to learn whether speech rate and voice pitch of phoneme-synthesized speech affects pilot accuracy and response time to typical threat-warning messages. Helicopter pilots engaged in an attention-demanding flying task and listened for voice threat warnings presented in a background of simulated helicopter cockpit noise. Performance was measured by flying-task performance, threat-warning intelligibility, and response time. Pilot ratings were elicited for the different voice pitches and speech rates. Significant effects were obtained only for response time and for pilot ratings, both as a function of speech rate. For the few cases when pilots forgot to respond to a voice message, they remembered 90 percent of the messages accurately when queried for their response 8 to 10 sec later.

Simpson, C. A.↗