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DOE OSTI2024

Human-Machine Shared Control for Path Following Considering Driver Fatigue Characteristics

Fatigue driving has been regarded as one of the most important factors that cause traffic accidents. This paper proposes a robust human-machine shared control strategy to improve the vehicle performance for different driver fatigue states. Firstly, the time-varying driver steering model is proposed to address the model mismatch caused by fatigue driving. And the driver fatigue evaluation system is established based on facial features to quantify driver fatigue levels. Based on the quantified fatigue levels, a novel strategy for allocating authorities of the driver and controller is developed for building the driver-vehicle interaction system. Then, to weaken the influence of parameter perturbations caused by the time-varying driver states, we design a fatigue-based shared controller through state feedback. The actuator saturation and system constraints are considered in the controller design through the robust set-invariance property to improve vehicle safety and driving comfort. The driver-in-the-loop platform is conducted to validate the effectiveness of the proposed shared steering controller. In conclusion, the experimental results show that the proposed strategy can adaptively optimize the human-machine authorities according to fatigue states and comprehensively improve vehicle performance.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2015

Scheduling and Delivering Aircraft to Departure Fixes in the NY Metroplex with Controller-Managed Spacing Tools

In this paper, successful Time-Based Flow Management (TBFM) scheduling systems for arrivals are considered and adapted to apply to departures. We present a concept of operations that integrates Controller-Managed Spacing tools for departures (CMS-D) with existing tactical departure scheduling tools to coordinate demand at departure fixes in a metroplex environment. We tested our concept in a Human-in-the-Loop simulation and compared the effect of two scheduling conditions: 1) "Departure Scheduling" consisting of an emulation of the Integrated Departure and Arrival Capability (IDAC) where Towers and a Planner (Traffic Management Coordinator at the appropriate facility) coordinate aircraft scheduled takeoff times to departure fixes; and 2) "Arrival Sensitive Departure Scheduling" where, in addition, the Tower and Planner also consider arrival Scheduled Time of Arrivals (STAs) at the airport's dependent runway. Results indicate little difference between the two scheduling conditions, but a large difference between the No Tools and the two scheduling conditions with CMS-D tools. The scheduling/CMS-D tools conditions markedly reduced heading, speed clearances, and workload for controllers who were merging flows at the departure fixes. In the tool conditions, departure controllers conditioned departures earlier rather than later when aircraft were tied near the departure fixes. In the scheduling/CMS-D tools conditions, departures crossed the departure fixes 50 seconds earlier and with an 8% error rate (consisting of time ahead or behind desired time of arrival) compared to a 19% error rate in the No Tool condition. Two exploratory runs showed that similar beneficial effects can be obtained only with the CMS-D tools without scheduling takeoff times, but at the cost of a somewhat higher workload for controllers, indicating the benefits of pre-departure scheduling of aircraft with minimal delays. Hence, we found that CMS-D tools were very beneficial in the metroplex environment we tested but that further research is needed to clarify the benefits of the various scheduling approaches.

terminal airspace↗

NASA NTRS2011

Surveillance Range and Interference Impacts on Self-Separation Performance

Self-separation is a concept of flight operations that aims to provide user benefits and increase airspace capacity by transferring traffic separation responsibility from ground-based controllers to the flight crew. Self-separation is enabled by cooperative airborne surveillance, such as that provided by the Automatic Dependent Surveillance-Broadcast (ADSB) system and airborne separation assistance technologies. This paper describes an assessment of the impact of ADS-B system performance on the performance of self-separation as a step towards establishing far-term ADS-B performance requirements. Specifically, the impacts of ADS-B surveillance range and interference limitations were analyzed under different traffic density levels. The analysis was performed using a batch simulation of aircraft performing self-separation assisted by NASA s Autonomous Operations Planner prototype flight-deck tool, in two-dimensional airspace. An aircraft detected conflicts within a look-ahead time of ten minutes and resolved them using strategic closed trajectories or tactical open maneuvers if the time to loss of separation was below a threshold. While a complex interaction was observed between the impacts of surveillance range and interference, as both factors are physically coupled, self-separation performance followed expected trends. An increase in surveillance range resulted in a decrease in the number of conflict detections, an increase in the average conflict detection lead time, and an increase in the percentage of conflict resolutions that were strategic. The majority of the benefit was observed when surveillance range was increased to a value corresponding to the conflict detection look-ahead time. The benefits were attenuated at higher interference levels. Increase in traffic density resulted in a significant increase in the number of conflict detections, as expected, but had no effect on the conflict detection lead time and the percentage of conflict resolutions that were strategic. With surveillance range corresponding to ADS-B minimum operational performance standards for Class A3 equipment and without background interference, a significant portion of conflict resolutions, 97 percent, were achieved in the preferred strategic mode. The majority of conflict resolutions, 71 percent, were strategic even with very high interference (over three times that expected in 2035).

Idris, Husni↗

DOE OSTI2023

Evaluating Connected and Automated Vehicles in Co-Simulation Environment of Traffic Microsimulation and Vehicle Dynamics

Connected and automated vehicles (CAVs) have the potential to improve many aspects of the current transportation systems such as safety, mobility, and energy efficiency. In order to evaluate the benefits and impacts of a CAV, the CAV control algorithm is typically implemented on vehicles simulated in a traffic microsimulation environment. However, traffic microsimulation usually lacks detailed vehicle and powertrain dynamics, making it challenging to fully understand how a CAV control algorithm will perform and respond on an actual vehicle. Whether the same benefits measured in the simulation will also be observed in real-world remains an open question. One potential approach to fill in this gap is to conduct a co-simulation of traffic microsimulation with detailed vehicle and powertrain dynamics models, often developed in MATLAB Simulink. However, current microsimulation tools such as VISSIM and SUMO do not have a ready-to-use interface for co-simulation with vehicle dynamics and Simulink. Also, even if such an interface exists, it will be tool-specific, making it challenging to shift from one tool to another or test CAV controls in different tools. There are needs for tool-agnostic co-simulation as different microsimulation tools have their pros and cons, and researchers often need to use different tools based on the purposes of the simulation, project needs, and applications. In this work, Flexible Interface for X-in-the-loop Simulation (FIXS) is developed that can support the co-simulation of microsimulation, CAV control algorithm, and vehicle dynamics model in Simulink. Enabled by the FIXS, the benefit and performance of a CAV control algorithm can be better understood with the consideration of vehicle responses and dynamics. The connection to VISSIM and SUMO is handled internally by the interface, and users can easily switch tools by changing a configuration file. The co-simulation capability is demonstrated for a VISSIM eco-approach and departure CAV scenario and a SUMO cooperative merging scenario for both a passenger CAV and a class 8 heavy-duty connected and automated trucks.

Shao, Yunli↗

NASA NTRS2012

Efficient Computation of Separation-Compliant Speed Advisories for Air Traffic Arriving in Terminal Airspace

A class of problems in air traffic management asks for a scheduling algorithm that supplies the air traffic services authority not only with a schedule of arrivals and departures, but also with speed advisories. Since advisories must be finite, a scheduling algorithm must ultimately produce a finite data set, hence must either start with a purely discrete model or involve a discretization of a continuous one. The former choice, often preferred for intuitive clarity, naturally leads to mixed-integer programs, hindering proofs of correctness and computational cost bounds (crucial for real-time operations). In this paper, a hybrid control system is used to model air traffic scheduling, capturing both the discrete and continuous aspects. This framework is applied to a class of problems, called the Fully Routed Nominal Problem. We prove a number of geometric results on feasible schedules and use these results to formulate an algorithm that attempts to compute a collective speed advisory, effectively finite, and has computational cost polynomial in the number of aircraft. This work is a first step toward optimization and models refined with more realistic detail.

Sadovsky, Alexander V.↗

NASA NTRS2014

UAS Integration into the NAS: HSI Full Mission Simulation Preliminary Results

The goal of the Full Mission Sim was to examine the effects of different command and control interfaces on UAS pilots' ability to respond to ATC commands and traffic advisories. Results suggest that higher levels of automation (i.e., waypoint-to-waypoint control interfaces) lead to longer initial response times and longer edit times. The findings demonstrate the importance of providing pilots with interfaces that facilitate their ability to get back "in the loop."

ground control stations↗

NASA NTRS2014

UAS Integration into the NAS: HSI Full Mission Simulation Analysis by Input Method

ground control stations↗

NASA NTRS2019

Effectiveness of Redundant Communications Systems in Maintaining Operational Control of Small Unmanned Aircraft

As a part of NASA’s Unmanned Aircraft System (UAS) Traffic Management (UTM) research, a test was performed to evaluate the effectiveness of the redundant Command and Control (C2) communications system for maintaining operational control of small UAS in the airspace over a rural area. In the test, operators set up a primary and a secondary UAS C2 communications system, sent a maneuver command to an Unmanned Aircraft (UA) with and without a functioning primary system, then verified the execution of the sent command to confirm the operator control. Operators reported that the tested redundancy configurations were effective in maintaining operational control in the test airspace over rural locations. Since the next phase of UTM research focuses on operations in an urban area where an increased level of Radio Frequency (RF) activities occur compared to a rural area, four recommendations are provided to sustain the effectiveness of redundancy in urban operations. First, the operator should not include C2 systems that use the industrial, scientific, and medical (ISM) radio bands in redundancy configurations. Second, the operator should verify the RF characteristics of the intended operation area and examine the area’s radio noise floor. Third, the operator should monitor the availability, quality, and reliability of communications services used by a redundant system. Fourth, the small UAS community should adopt a standard set of contingency steps to handle the loss of C2 communications so that such events are managed in a consistent manner across the airspace. The insights from the test will be used to accommodate the FAA’s UAS integration effort.

Jung, Jaewoo↗

NASA NTRS2010

Impact of Conflict Avoidance Responsibility Allocation on Pilot Workload in a Distributed Air Traffic Management System

Pilot workload was examined during simulated flights requiring flight deck-based merging and spacing while avoiding weather. Pilots used flight deck tools to avoid convective weather and space behind a lead aircraft during an arrival into Louisville International airport. Three conflict avoidance management concepts were studied: pilot, controller or automation primarily responsible. A modified Air Traffic Workload Input Technique (ATWIT) metric showed highest workload during the approach phase of flight and lowest during the en-route phase of flight (before deviating for weather). In general, the modified ATWIT was shown to be a valid and reliable workload measure, providing more detailed information than post-run subjective workload metrics. The trend across multiple workload metrics revealed lowest workload when pilots had both conflict alerting and responsibility of the three concepts, while all objective and subjective measures showed highest workload when pilots had no conflict alerting or responsibility. This suggests that pilot workload was not tied primarily to responsibility for resolving conflicts, but to gaining and/or maintaining situation awareness when conflict alerting is unavailable.

Ligda, Sarah V.↗

NASA NTRS1999

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Caines, P. E.↗

DOE OSTI2022

Peer-to-Peer Communication Trade-Offs for Smart Grid Applications: Preprint

Peer-to-peer energy management systems for smart grids require developers to consider the trade-offs between the amount of communication traffic generated and the quality and speed of convergence of the control algorithms that are deployed. Employing a fully connected communication causes messages to scale exponentially with the number of nodes, while using a sparse connectivity causes less information dissemination leading to degradation of the algorithm performance. The best communication topology for a particular application lies somewhere in between and often requires empirical evaluation by application designers. Existing methods do not put focus on the needs for smart grid applications, which is information dissemination throughout the network and they do not provide a flexible solution for application developers to prototype and deploy different topologies without modifying the application code. This paper introduces a configurable virtual communication topology framework TopLinkMgr, allowing users to specify any chosen communication topology and deploy peer-to-peer applications using it. It also introduces a self-adaptive, fault-tolerant topology management algorithm, Bounded Path Dissemination that can ensure the dissemination of information to all peers within a specified threshold for a sparsely connected topology. Experiments show that the algorithm improves on convergence speed and accuracy over state-of-the-art methods and is also robust against node failures. The results indicate the possibility of achieving a close-to optimal convergence without overloading the network allowing the realization of peer-to-peer control platforms covering larger and more complex power systems.

Bounded Path Dissemination↗

DOE OSTI2021

A Multirange Vehicle Speed Prediction With Application to Model Predictive Control-Based Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Abstract Connectivity and automated driving technologies have opened up new research directions in the energy management of vehicles which exploit look-ahead preview and enhance the situational awareness. Despite this advancement, the vehicle speed preview that can be obtained from vehicle-to-vehicle/infrastructure (V2V/I) communications is often limited to a relatively short time-horizon. The vehicular energy systems, specifically those of the electrified vehicles, consist of multiple interacting power and thermal subsystems that respond over different time-scales. Consequently, their optimal energy management can greatly benefit from long-term speed prediction beyond that available through V2V/I communications. Accurately extending the look-ahead preview, on the other hand, is fundamentally challenging due to the dynamic nature of the traffic environment. To address this challenge, we propose a data-driven multirange vehicle speed prediction strategy for arterial corridors with signalized intersections, providing the vehicle speed preview for three different ranges, i.e., short-, medium-, and long-range. The short-range preview is obtained by V2V/I communications. The medium-range preview is realized using a neural network (NN), while the long-range preview is predicted based on a Bayesian network (BN). The predictions are updated in real-time based on the current state of traffic and incorporated into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city driving are reported.

Automation & Control Systems↗

NASA NTRS2012

Investigating the Impact of Off-Nominal Events on High-Density "Green" Arrivals

Trajectory-based controller tools developed to support a schedule-based terminal-area air traffic management (ATM) concept have been shown effective for enabling green arrivals along Area Navigation (RNAV) routes in moderately high-density traffic conditions. A recent human-in-the-loop simulation investigated the robustness of the concept and tools to off-nominal events events that lead to situations in which runway arrival schedules require adjustments and controllers can no longer use speed control alone to impose the necessary delays. Study participants included a terminal-area Traffic Management Supervisor responsible for adjusting the schedules. Sector-controller participants could issue alternate RNAV transition routes to absorb large delays. The study also included real-time winds/wind-forecast changes. The results indicate that arrival spacing accuracy, schedule conformance, and tool usage and usefulness are similar to that observed in simulations of nominal operations. However, the time and effort required to recover from an off-nominal event is highly context-sensitive, and impacted by the required schedule adjustments and control methods available for managing the evolving situation. The research suggests ways to bolster the off-nominal recovery process, and highlights challenges related to using human-in-the-loop simulation to investigate the safety and robustness of advanced ATM concepts.

Callatine, Todd J.↗

NASA NTRS2015

Enabling Performance-Based Navigation Arrivals: Development and Simulation Testing of the Terminal Sequencing and Spacing System

NASA has developed an advanced arrival management capability for terminal controllers, known as Terminal Sequencing and Spacing (TSS). TSS increases use of performance-based navigation (PBN) arrival procedures during periods of high traffic demand. It extends two Federal Aviation Administration's operational systems with terminal metering and controller spacing tools. Sixteen high-fidelity human-in-the-loop simulations, involving more than five hundred hours of evaluation time, were conducted to mature TSS from proof-of- concept design to fully functional prototype. These simulations modeled arrival procedures at several U.S. airports, incorporated a broad range of traffic demand profiles and wind conditions, and used controllers with extensive operational experience. Two fundamental metrics are evaluated for these simulations: PBN Success Rate and Inter-Arrival Spacing Error. The PBN Success Rate shows a definitive trend when TSS is used. It increases from 42 percent for today's operations to 68 percent for terminal metering only and 92 percent for terminal metering with controller-managed spacing tools. Meanwhile, the Inter-Arrival Spacing Error improves 25 to 35 percent when TSS is used compared to not used. The TSS technology was transferred to the FAA and, and it is targeted for deployment to several busy airports in the U.S. starting in 2018.

terminal metering↗

NASA NTRS1988

Future switching satellites

Communications satellites of the future are likely to use much narrower beams in order to increase the uplink G/T and the downlink EIRP so that small earth terminals of the VSAT class can achieve full mesh connectivity. These satellites will need onboard switches to route traffic from originating upbeams to destination downbeams. This paper presents a new approach to accomplishing this rerouting using destination-directed packets that inherently carry the information needed to control the onboard switch connections and to adjust the traffic flow among the beams and the stations. The method also inherently provides channel multiplication and DAMA advantages which result in maximally efficient utilization of the space segment resource.

Campanella, S. Joseph↗

DOE OSTI2025

String instability mitigation of adaptive cruise control without modifying control laws: trajectory shaper and parameter estimation

Vehicle automation technologies equip vehicles with adaptive cruise control (ACC) systems, which relieve driving fatigue. However, recent studies have shown that the current ACC systems are string-unstable (i.e., exacerbate traffic congestion). To achieve string stability, most existing studies directly modify the control algorithms of ACC systems. Alternatively, this study proposes a trajectory shaper (TS)-based method, which only modifies the trajectory information of the predecessor vehicle, so that the ego vehicle driven by a string-unstable ACC system leverages the modified trajectory information to achieve string stability. To devise the TS-based method, an offline-online parameter estimation method integrating batch optimization and an extended Kalman filter is applied to estimate the parameters of an ACC system. The proposed TS-based method is cost-effective during implementation, as it avoids modifying existing ACC control algorithms (which entails a complex analysis of control systems and parameter tuning). In conclusion, the effectiveness of the proposed TS-based method is validated through extensive numerical experiments.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2011

Characterization of Tactical Departure Scheduling in the National Airspace System

This paper discusses and analyzes current day utilization and performance of the tactical departure scheduling process in the National Airspace System (NAS) to understand the benefits in improving this process. The analysis used operational air traffic data from over 1,082,000 flights during the month of January, 2011. Specific metrics included the frequency of tactical departure scheduling, site specific variances in the technology's utilization, departure time prediction compliance used in the tactical scheduling process and the performance with which the current system can predict the airborne slot that aircraft are being scheduled into from the airport surface. Operational data analysis described in this paper indicates significant room for improvement exists in the current system primarily in the area of reduced departure time prediction uncertainty. Results indicate that a significant number of tactically scheduled aircraft did not meet their scheduled departure slot due to departure time uncertainty. In addition to missed slots, the operational data analysis identified increased controller workload associated with tactical departures which were subject to traffic management manual re-scheduling or controller swaps. An analysis of achievable levels of departure time prediction accuracy as obtained by a new integrated surface and tactical scheduling tool is provided to assess the benefit it may provide as a solution to the identified shortfalls. A list of NAS facilities which are likely to receive the greatest benefit from the integrated surface and tactical scheduling technology are provided.

Capps, Alan↗

NASA NTRS2011

Trajectory-Based Complexity (TBX): A Modified Aircraft Count to Predict Sector Complexity During Trajectory-Based Operations

In this paper we introduce a new complexity metric to predict -in real-time- sector complexity for trajectory-based operations (TBO). TBO will be implemented in the Next Generation Air Transportation System (NextGen). Trajectory-Based Complexity (TBX) is a modified aircraft count that can easily be computed and communicated in a TBO environment based upon predictions of aircraft and weather trajectories. TBX is scaled to aircraft count and represents an alternate and additional means to manage air traffic demand and capacity with more consideration of dynamic factors such as weather, aircraft equipage or predicted separation violations, as well as static factors such as sector size. We have developed and evaluated TBX in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center during human-in-the-loop studies of trajectory-based concepts since 2009. In this paper we will describe the TBX computation in detail and present the underlying algorithm. Next, we will describe the specific TBX used in an experiment at NASA's AOL. We will evaluate the performance of this metric using data collected during a controller-inthe- loop study on trajectory-based operations at different equipage levels. In this study controllers were prompted at regular intervals to rate their current workload on a numeric scale. When comparing this real-time workload rating to the TBX values predicted for these time periods we demonstrate that TBX is a better predictor of workload than aircraft count. Furthermore we demonstrate that TBX is well suited to be used for complexity management in TBO and can easily be adjusted to future operational concepts.

trajectories↗