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Several of the keyboard data languages were tabulated and analyzed. The key language chosen as a test vehicle was that used by the nonradar or flight data controllers. This application was undertaken to minimize effort in a cost efficient way and with less research and development.
The methodology and techniques used to collect and analyze look-point position data from a real-time ATC display-format comparison experiment are documented. That study compared the delivery precision and controller workload of three final approach spacing aid display formats. Using an oculometer, controller lookpoint position data were collected, associated with gaze objects (e.g., moving aircraft) on the ATC display, and analyzed to determine eye-scan behavior. The equipment involved and algorithms for saving, synchronizing with the ATC simulation output, and filtering the data are described. Target (gaze object) and cross-check scanning identification algorithms are also presented. Data tables are provided of total dwell times, average dwell times, and cross-check scans. Flow charts, block diagrams, file record descriptors, and source code are included. The techniques and data presented are intended to benefit researchers in other studies that incorporate non-stationary gaze objects and oculometer equipment.
A jointly funded (NASA/FAA) real-time simulation study was conducted at NASA Langley Research Center to gather comparative performance data among three candidate final-approach spacing aid (FASA) display formats. Several objective measures of controller performance and their display eye-scan behavior as well as subjective workload and rating questionnaires were used. For each of two representative pattern-speed procedures (a 170-knot procedure and a 210-knot procedure with speed control aiding), data were gathered, via twelve FAA controllers, using four final-controller display format conditions (manual/ARTS 3, graphic marker, DICE countdown, and centerline slot marker). Measured runway separations were more precise with both the graphic marker and DICE countdown formats than with the centerline slot marker and both (graphic and DICE) improved precision relative to the manual/ARTS 3 format. For three separate rating criteria, the subject controllers ranked the FASA formats in the same order: graphic marker, DICE countdown, and centerline slot marker. The increased precision measured with the 210-knot pattern-speed procedure may indicate the potential for the application of speed-control aiding where higher pattern speeds are practical after the base-to-final turn. Also presented are key FASA issues, a rationale for the formats selected for testing, and their description.
If human factors certification of aviation technologies aims to encompass the wide range of issues which need to be addressed for any new system, then human factors involvement must be present throughout the whole design process in a manner which relates to final certification. A certification process cannot simply be applied to the final product of design. Standards and guidelines will be required by designers at the outset of design for reference in preparing for certification. The most effective use of human factors principles, methods, and measures is made as part of an iterative design process, leading to a system which reflects these as far as possible. This particularly applies where the technology is complex and may be represented by a number of components or sub-systems. Some aspects of the system are best certified during early prototyping, when there is still scope to make changes to software or hardware. At this stage in design, financial and/or time pressures will not rule out the possibility of necessary changes, as may be the case later. Other aspects of the system will be best certified during the final phases of design when the system is in a more complete form and in a realistic environment.
The current debate over the concept of Free Flight has renewed interest in automated conflict detection and resolution in the enroute airspace. An essential requirement for effective conflict detection is accurate prediction of trajectories. Trajectory prediction is, however, an inexact process which accumulates errors that grow in proportion to the length of the prediction time interval. Using a model of prediction errors for the trajectory predictor incorporated in the Center-TRACON Automation System (CTAS), a computationally fast algorithm for computing conflict probability has been derived. Furthermore, a method of conflict resolution has been formulated that minimizes the average cost of resolution, when cost is defined as the increment in airline operating costs incurred in flying the resolution maneuver. The method optimizes the trade off between early resolution at lower maneuver costs but higher prediction error on the one hand and late resolution with higher maneuver costs but lower prediction errors on the other. The method determines both the time to initiate the resolution maneuver as well as the characteristics of the resolution trajectory so as to minimize the cost of the resolution. Several computational examples relevant to the design of a conflict probe that can support user-preferred trajectories in the enroute airspace will be presented.
Current and future energy demands, end uses, and cost used to characterize typical applications services in the industrial sector of the United States are examined. A review and evaluation of existing industrial energy data bases was undertaken to assess their potential for supporting SERI research market suitability analysis; (2) market development; (3) end use matching; (4) industrial application studies; and (5) identification of cost and performance goals for solar systems and typical information requirements for industrial energy end use. The focus was on fuels and electric energy used for heat and power purchased by the manufacturing subsector and listed by 2, 3, and 4 digit SIC, primary fuel. The effects of federal and state industrial energy conservation programs on future industrial sector demands were assessed.
When a new system, concept, or tool is proposed in the aviation domain, one concern is the impact that this will have on operator workload. As an experience, workload is difficult to measure in a way that will allow comparison of proposed systems with those already in existence. Chatterji and Sridhar (2001) suggested a method by which airspace parameters can be translated into workload ratings, using a neural network. This approach was employed, and modified to accept input from a non-real time airspace simulation model. The following sections describe the preparations and testing work that will enable comparison of a future airspace concept with a current day baseline in terms of workload levels.
Method and system for analyzing and processing information on one or more aircraft flight paths, using a four-dimensional coordinate system including three Cartesian or equivalent coordinates (x, y, z) and a fourth coordinate .delta. that corresponds to a distance estimated along a reference flight path to a nearest reference path location corresponding to a present location of the aircraft. Use of the coordinate .delta., rather than elapsed time t, avoids coupling of along-track error into aircraft altitude and reduces effects of errors on an aircraft landing site. Along-track, cross-track and/or altitude errors are estimated and compared with a permitted error bounding space surrounding the reference flight path.
The purpose of this study was to investigate the usefulness of different input device configurations when trial planning new routes for aircraft in an advanced simulation of the en route workstation. The task of trial planning is one of the futuristic tools that is performed by the graphical manipulation of an aircraft's trajectory to reroute the aircraft without voice communication. In this study with two input devices, the FAA's current trackball and a basic optical computer mouse were evaluated with "pick" button in a click-and-hold state and a click-and-release state while the participant dragged the trial plan line. The trial plan was used for three different conflict types: Aircraft Conflicts, Weather Conflicts, and Aircraft + Weather Conflicts. Speed and accuracy were the primary dependent variables. Results indicate that the mouse conditions were significantly faster than the trackball conditions overall with no significant loss of accuracy. Several performance ratings and preference ratings were analyzed from post-run and post-simulation questionnaires. The release conditions were significantly more useful and likable than the hold conditions. The results suggest that the mouse in the release button state was the fastest and most well liked device configuration for trial planning in the en route workstation. Keywords-input devices, en route, controller, workstation, mouse, trackball, NextGen
A human-in-the-loop simulation was conducted that examined an approach to adjusting airport arrivals in such a way as to enable higher departure throughput while maintaining arrival throughput. This approach, referred to as Departure-Sensitive Arrival Spacing (DSAS), leverages the capabilities of the Terminal Sequencing and Spacing (TSS) system with an additional Decision Support Tool (DST) to assign more precise arrival spacing interval. This presentation will focus on the changes observed in the task distribution and control strategies among three Terminal Radar Approach Control (TRACON) controller participants and the workload associated with those changes across three conditions: Baseline, TSS, and DSAS. Results showed that the application of the DSTs in the TSS condition and those in the DSAS condition enabled a progressive reduction in the number of clearances issued and for the clearances to be issued earlier, further away from the airport. In doing so, there was also a greater use of speed control versus vectoring and altitude for schedule conformance in the TSS and DSAS conditions respectively and relative to Baseline. Workload also shifted in conjunction with the clearance distribution with an overall reduction across conditions. The changes in task and workload distribution enabled a shift from tactical to strategic control, which allowed for a more predictable and efficient delivery of arrivals.
Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.
Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.
Applications of wide range broadcast procedures to improve air traffic control and make more airspace available are discussed. A combination of the Omega navigation system and the very high frequency omnirange (VOR) is recommended as a means for accomplishing improved air traffic control. The benefits to be derived by commercial and general aviation are described. The air/ground communications aspects of the improved air traffic control system are explained. Research and development programs for implementing the broadcast concept are recommended.
Traffic congestion is a serious problem in the US, and traffic signal control is one of the effective solutions to congestion. Previous research on model predictive control (MPC)-based traffic signal control showed substantial benefits over conventional methods. This study focused on implementing MPC over a large-scale network with complex intersections and the impact of cycle length, network size, and imperfect state estimation on performances. This study implemented a virtual phase link (VPL)-based model predictive control method which used the number of vehicles in each VPL as input state variables and was suitable for National Electrical Manufacturing Association (NEMA) ring-barrier control. To test the impact of network size, the performance of distributed MPC (36 intersections in the network are divided into five subnetworks) was compared with that of MPC over the full network for a set of cycle lengths. To test the impact of imperfect state estimation, we synthetically infused estimation error and developed two scenarios, MPC-error and MPC-error narrow, which had higher and lower estimation errors, respectively. The performance of these MPC methods was compared with that of the existing time-of-day (TOD) method and an offline method that used Webster's method for split and MULTIBAND for cycle length and offset optimization. Trajectory and linkwise signal performance measures were collected from the simulation to evaluate performance. The distributed MPC method with perfect state estimation had the lowest delay and highest energy efficiency of all the methods. The performance of MPC decreased as the prediction inaccuracy increased. MPC-error had 7% and 11% more delay than MPC-error narrow in the morning and evening peaks, respectively. Overall, simulation results suggest that even with imperfect state estimation, MPC methods will outperform offline methods significantly.
Smart traffic signals bring together transportation infrastructure and advance technologies to improve the mobility and efficiency of urban transportation network. Adaptive traffic signal control studies can be categorized into modeling-based approaches and learning-based approaches. In order to take advantages of these two systems, this study developed an offline-online combined Partial Observable Imitation Network for Traffic signal control (POINT). In the offline system, the traffic signal timing optimization problem was formulated as a Mixed Integer Nonlinear Programming (MINLP) given complete traffic information, i.e., second-by-second speeds and locations of all vehicles. Furthermore, the objective of MINLP is to minimize total travel delays considering individual vehicle trajectories under Connected Vehicle (CV) environment. The calculated optimal solutions under various traffic conditions were considered as the ”expert” decisions. In the online system, an imitation neural network model was developed to learn the ”expert” signal plans generated from offline system. Given partial observable traffic conditions in real time, e.g., the aggregate-level of traffic volume, the POINT model can compute the signal timing parameters in the online system. The numerical results demonstrated that the proposed method outperformed other state-of-the-art signal control method under high and unbalanced traffic demand levels in terms of reducing travel delays and queue length.
Concepts of increased pilot participation in air traffic control are presented. The design of an air traffic control system for pilot usage is considered. The operating and safety benefits of LF/VLF approaches in comparison to current nonprecision approach procedures and systems are discussed. With a good national system plan, flight testing and validation, and the use of local differential, or general diurnal, corrections, the LF/VLF system would provide service superior to that presently available.
Traffic congestion leads to severe problems especially in urban traffic networks. It increases the chance of accidents, energy waste, and social costs. In order to address these problems, an adaptive linear quadratic regulator (LQR) approach is developed for traffic signal control at multiple intersections in an urban area. The proposed method controls the green time of the traffic signals to reduce traffic congestion and smooth traffic flow. Real-world data from vision-based traffic sensors are used to build the traffic network model, which mimics the real-world traffic behavior. In addition, the proposed control utilizes recursive least square parameter estimation, which is capable of tracking dynamic changes in traffic conditions. Simulation of Urban MObility (SUMO) is used to analyze the efficacy of the proposed method. Results of the simulation show that the proposed method outperforms pretimed control in various aspects.
Reduced runway separation standards are among the means which have been proposed for increasing airport capacity. The probability of a blunder will dominate the calculation of safe separation standards. Then the determinant of safe system performance will be the system reaction time comprised of the air traffic controller's detection, decision and communication delays, and the response times of the pilot and aircraft in executing a collision avoidance manuever. Estimates of these times, based on existing data, show that the delays ascribable to the human portions of the man-machine system are comparatively unimportant. New developments in radar, computers, and data links will be required to provide any substantial improvement of the existing system, and the goal of 2500 ft of separation may not be achievable.