Trajectory Options Research Articles

Data-Driven Optimization for Air Traffic Flow Management with Trajectory Preferences

In this paper, we present a novel data-driven optimization approach for trajectory-based air traffic flow management (ATFM). A key aspect of the proposed approach is the inclusion of airspace users’ trajectory preferences, which are computed from traffic data by combining clustering and classification techniques. Machine learning is also used to extract consistent trajectory options, whereas optimization is applied to resolve demand-capacity imbalances by means of a mathematical programming model that judiciously assigns a feasible four-dimensional trajectory and a possible ground delay to each flight. The methodology has been tested on instances extracted from the Eurocontrol data repository. With more than 32,000 flights considered, we solve the largest instances of the ATFM problem available in the literature in short computational times that are reasonable from the practical point of view. As a by-product, we highlight the trade-off between preferences and delays as well as the potential benefits. Indeed, computing efficient solutions to the problem facilitates a consensus between the network manager and airspace users. In view of the level of accuracy of the solutions and the excellent computational performance, we are optimistic that the proposed approach can make a significant contribution to the development of the next generation of air traffic flow management tools.

Use of Trajectory Option Sets to Support Collaborative Constraint Propagation

Air traffic flow management is supported by a highly distributed work system in which airline dispatchers and Federal Aviation Administration (FAA) traffic managers must coordinate. To support asynchronous coordination between a dispatcher and a traffic manager, the FAA has developed software that allows the flight operators to submit multiple, prioritized alternative flight plans. This set of alternative flight plans, submitted along with a filed route, is referred to as a Trajectory Option Set (TOS). And some airlines have now developed initial versions of software capable of generating and submitting such TOSs. This paper reports on cognitive walkthroughs with 5 dispatchers and 3 traffic managers on 5 scenarios designed to evaluate the operational concept, procedures and supporting FAA and airline software. The findings provide guidance for application of the concept of collaborative constraint propagation to support distributed work, as well as 42 recommendations for enhancing associated procedures and supporting software designs.

Capacity of Sun-driven lunar swingby sequences and their application in asteroid retrieval

For deep-space mission design, the gravity of the Sun and the Moon can be first considered and utilized. Their gravity can provide the energy change for launching spacecraft and retrieving spacecraft as well as asteroids. Regarding an asteroid retrieval mission, it can lead to the mitigation of asteroid hazards and an easy exploration and exploitation of the asteroid. This paper discusses the application of the Sun-driven lunar swingby sequence for asteroid missions. Characterizing the capacity of this technique is not only interesting in terms of dynamic insights but also non-trivial for trajectory design. The capacity of a Sun-driven lunar swingby sequence is elucidated in this paper with the help of the "Swingby-Jacobi" graph. The capacity can be represented by a range of the Jacobi integral that encloses around 660 asteroids currently cataloged. To facilitate trajectory design, a database of Sun-perturbed Moon-to-Moon transfers, including multi-revolution cases is generated and employed. Massive trajectory options for spacecraft launch and asteroid capture can then be explored and optimized. Finally, a number of asteroid flyby, rendezvous, sample-return, and retrieval mission options enabled by the proposed technique are obtained.

Fast 4D flight planning under uncertainty through parallel stochastic path simulation

The Air Traffic Management system is evolving to deal with efficiency, capacity, safety and environmental challenges. Progress along these fronts requires the development of trajectory planning and prediction tools that can go beyond the current deterministic planning paradigm to deal with an uncertain meteorological and operational context. In this work, we introduce a novel flight planning methodology to generate weather-optimal 4D flight plans under uncertainty. By leveraging general-purpose computing on graphics processing units and combining continuous and discrete elements in an integrated fashion, we can simulate and evaluate multiple trajectory options under multiple scenarios in parallel, allowing us to provide quick iterations to a stochastic optimization algorithm. Our computational experiments show that our proposed solutions can provide efficient solutions in seconds, as required in practical settings, while allowing for simple integration of future extensions thanks to its simulation-based nature.

Pseudo multishot echo-planar imaging for geometric distortion improvement.

Conventional echo-planar imaging (EPI) uses a radiofrequency pulse for excitation and a prolonged echo train to sample k space, while off-resonance and T2 * decay effects caused by magnetic susceptibility variation accumulate within each echo, leading to geometric distortion. Multishot EPI methods, which divide k space into segments, can shorten the effective echo spacing and reduce the distortion on EPI images. But multiple shots cost longer scan time and render susceptibility to motion. In this study, we propose a new "multishot" EPI method termed pseudo multishot EPI (pmsEPI), in which phase-encoding lines are segmented as in multishot EPI but are collected within a single shot. With the magnetization divided into different pathways via interleaved excitation instead of refocusing in a single long echo train, the total phase error accumulation is reduced in each segmented acquisition, thereby improving distortion of the resultant EPI image. The performance of the pmsEPI method is demonstrated by phantom and in vivo brain experiments on a 3-T scanner. The experimental results show that the distortion displacements of pmsEPI acquisition compared with conventional EPI decrease by 50% with two pseudo shots and 66% with three pseudo shots, validating the ability of the method to obtain images with reduced distortion in a single shot, although magnetization splitting may induce more than 40% SNR loss and minor artifacts. Specifically, the ability of pmsEPI in diffusion-weighted imaging with different trajectory options is highlighted, and the flexibility is demonstrated in a single-shot blip up and down acquisition.

An Integrated Approach for On-Demand Dynamic Capacity Management Service in U-Space

This article presents an integrated approach for on-demand dynamic capacity management (DCM) service to be offered in U-space. The approach involves three main threads, including flight planning (demand), airspace configuration (capacity), and demand-capacity balancing (DCB). The flight planning thread produces unmanned aerial systems (UAS) trajectories for each flight that together reflect the estimated traffic demand. The airspace configuration thread defines the fundamental airspace structure and proposes dynamic adjustment schemes that determine the capacity distribution. It also enables the flight planning to reschedule alternative trajectory options to route away from possible congested areas. The last DCB thread takes the previous inputs and then computes for the optimal slot allocation and trajectory selection, as well as the optimal airspace configuration. Simulation case studies have been performed through mimicking an envisioned U-space operating scenario. Results suggest that the integrated approach can achieve the best outcome in almost all the key performance areas than any other cases, where only partial functions are realized.

The Method of Trajectory Selection Based on Bayesian Game Model

To cope with the problem that most of the en-route spatial-temporal resource allocation in the collaborative trajectory options program (CTOP) only considers the air traffic control system command center (ATCSCC) while ignoring the needs of the airlines, which results in the loss of fairness, this study explores resource allocation methods oriented to airline trajectory preferences with optional trajectory and entry slots of flights over the flow constrained area (FCA) as the research object. Using game theory to analyze airline trajectory preference information and a Bayesian game model based on mixed strategies is constructed, the process of incomplete information game among airlines is studied. The equilibrium theory is used to solve the guarantee strategy of airline trajectory selection, which makes the airline trajectory selection strategy robust and provides a basis for the selection of schemes for ATCSCC to implement en-route network resource allocation under the CTOP. Experimental analysis was carried out to verify the feasibility of the method based on the actual operation data of high-altitude sectors of Shanghai. The results show that the solution obtained by the game can provide airlines with flight trajectory and entry slots over the FCA that are more in line with their actual operational needs and which provide data reference for the ATCSCC to select the final plan in multiple global Pareto optimal solutions in the subsequent process of the CTOP so as to better play the decision-making role of airlines in the CTOP while improving the fairness of en-route resource allocation.

Interstellar probe – Destination: Universe!

The idea of an “Outer solar system probe: to be aimed away from the Sun in the plane of the ecliptic” dates from a report of the “Simpson Committee” of the Space Science Board of the National Academy of Sciences in March of 1960. After many studies and name changes, what is now known as “Interstellar Probe” has matured as a concept for making new discoveries that can be made in no other way, by going places yet to be explored. The central technical question has always been propulsion with “near-future” capabilities taken as the backdrop for defining the mission requirements. However, the real issue has always been to unite compelling science with engineering and technical reality. With that perspective in mind the Johns Hopkins University Applied Physics Laboratory (APL) has been tasked by the NASA Heliophysics Division to (re-)study the mission and provide a Technical Report to be delivered late 2021 for input to next Solar and Space Physics Decadal Survey. This “pragmatic Interstellar Probe” of the study is a mission through the outer heliosphere and to the nearby “Very Local” interstellar medium (VLISM), uses today's technology to take the first explicit step on the path of interstellar exploration, and can pave the way, scientifically, technically, and programmatically for more ambitious future journeys (and more ambitious science goals). To enforce these goals broadly-based engineering requirements include (1) readiness to launch no later than January 1, 2030; (2) capability to transmit useful scientific data from 1000 au; (3) powered by no more than 600 W (electric) at the beginning of the mission and no more than half of that at mission's end; and, (4) lifetime of no less than 50 years. To travel as far and as fast as possible with available technology, the use of the Space Launch System Block 2 (SLS B2) cargo version is enabling: carrying the spacecraft as well as a 3rd and 4th stage, solar system escape speeds of at least twice that of Voyager 1 (i.e., up to 7.2 au/yr) should be possible. We provide a top-level summary of work accomplished to date, focusing on how the science goals drive and are affected by telecommunication options, guidance and control requirements, trajectory options, and the baseline system architecture and approach.“It isn't about where we are going. It's about the journey out there."

Multi-holed biplane drill guide-assisted percutaneous anterior odontoid screw fixation.

The use of percutaneous anterior screw fixation for odontoid fractures has been widely reported. Because the anatomical characteristics of the odontoid and the screw occupy three-dimensional space, it is challenging to establish the screw trajectory quickly and correctly during the operation. The purpose of this study was to introduce a multi-holed biplane drill guide that can be used to optimize the guide needle trajectory in percutaneous anterior odontoid screw fixation. Twenty-one patients with type II or rostral type III odontoid fractures were treated with percutaneous anterior single screw fixation. Of these, 12 patients had an unsatisfactory initial guide needle position. A drill guide was used to provide a variety of guide needle tracks. All 12 patients successfully underwent guided screw placement without vascular or neurological complications. Postoperative X-ray and/or CT scans showed that the internal fixation position was satisfactory. At the end of the follow-up period, all patients exhibited bony union without loosening or fractures of the internal fixation. With the imperfect initial position of the guide needle as a reference, the multi-holed biplane drill guide can provide a variety of needle trajectory options in the sagittal and coronal planes for percutaneous anterior odontoid screw fixation. The operator can quickly obtain the ideal guide needle trajectory.

Trajectory options for a manned mission to Mars using high-thrust propulsion systems

An analysis has been done of performance factors (mission duration, initial mass of the interplanetary crew transfer vehicle, velocity of the re-entry into the Earth atmosphere of the descent vehicle with the crew) for a single-spacecraft manned mission to Mars using high-thrust propulsion systems. Locally optimal solutions (in terms of delta-V budgets for the transfer) were found for the Earth–Mars–Earth transfer, with varying periods of waiting in Mars orbit, minimal distance to the Sun, as well as flight paths (direct Earth–Mars–Earth transfers vs. gravity assist maneuvers at Venus during Earth–Mars or Mars–Earth transfers). The proposed classification for locally optimal solutions is applicable to both high-thrust propulsion systems and low-thrust propulsion systems. A comparison of performance factors has been done for manned Martian mission options based on liquid-propellant engines and nuclear rocket engines with a 12,5 km/s constraint on the velocity of the manned re-entry vehicle in the Earth atmosphere. Key words: Manned mission to Mars, interplanetary transfer trajectory, high-thrust, liquid-propellant rocket engine, nuclear rocket engine, mission duration, initial mass of the interplanetary vehicle, re-entry velocity of a manned vehicle for returning the crew to Earth.

Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation

The accuracy of stockpile estimations is of immense criticality to process optimisation and overall financial decision making within manufacturing operations. Despite well-established correlations between inventory management and profitability, safe deployment of stockpile measurement and inspection activities remain challenging and labour-intensive. This is perhaps owing to a combination of size, shape irregularity as well as the health hazards of cement manufacturing raw materials and products. Through a combination of simulations and real-life assessment within a fully integrated cement plant, this study explores the potential of drones to safely enhance the accuracy of stockpile volume estimations. Different types of LiDAR sensors in combination with different flight trajectory options were fully assessed through simulation whilst mapping representative stockpiles placed in both open and fully confined areas. During the real-life assessment, a drone was equipped with GPS for localisation, in addition to a 1D LiDAR and a barometer for stockpile height estimation. The usefulness of the proposed approach was established based on mapping of a pile with unknown volume in an open area, as well as a pile with known volume within a semi-confined area. Visual inspection of the generated stockpile surface showed strong correlations with the actual pile within the open area, and the volume of the pile in the semi-confined area was accurately measured. Finally, a comparative analysis of cost and complexity of the proposed solution to several existing initiatives revealed its proficiency as a low-cost robotic system within confined spaces whereby visibility, air quality, humidity, and high temperature are unfavourable.

Planning Graphs for Efficient Generation of Desirable Narrative Trajectories

A goal of Experience Managers (EM) is to guide users through a space of narrative trajectories, or story branches, in an Interactive Narrative (IN). When a user performs an action that deviates from the intended trajectory, the EM uses a mediation strategy called accommodation to transition the user to a new desirable trajectory. However, generating the trajectory options then selecting the appropriate one is computationally expensive and at odds with the low-latency needs of an IN. We define three desirable properties (exemplar trajectories, narrative-theoretic comparison, and efficiency) that general solutions would possess and demonstrate how our plan-based Intention Dependency Graph addresses them.

Should I Stay or Should I Go? Identifying Intrinsic and Extrinsic Factors in the Decision to Return to Duty Following Lower Extremity Injury.

Rehabilitation research of wounded service members (SMs) commonly focuses on physical ability to return to duty (RTD) as a measure of successful recovery. However, numerous factors or barriers may influence a SM's ability and/or desire to RTD after lower extremity musculoskeletal trauma. SMs themselves as well as the clinical care team that works with them daily, often for years at a time, both offer unique perspectives on the influential factors that weigh into decisions to RTD. The purpose of this study was to identify the intrinsic and extrinsic factors patients and clinicians recognized as influencing the decision to RTD after severe lower extremity trauma. Thirty-two SMs with severe lower extremity trauma (amputation and lower limb salvage) and 30 providers with at least 2 years' experience caring for SMs with similar injuries participated separately in either a SM or provider/clinician focus group. Open-ended questions on factors influencing RTD and other rehabilitation success were discussed. Data analysis consisted of qualitative transcription and participatory active sorting, followed by thematic coding and grouping of qualitative data. Individual (health condition, personal traits, and career consideration), interpersonal (clinician's impact, family influence, and peer influence), health care system (systems of care, transdisciplinary rehabilitation, and innovation availability), and institutional (policy, benefits, and unit/commander) themes emerged amongst SM patients and clinicians. Expected frequently occurring themes common to both groups were the influence of the team and family unit, as well as career trajectory options after a severe injury. An unexpected theme was acknowledgment of and dissatisfaction with the recent dismantling of institutional systems that support wounded SMs. Patients placed less emphasis on severity of injury and greater emphasis on system and policy barriers than did clinicians. Characterization and classification of these clinician and SM-identified factors that influence the decision to RTD after severe lower extremity trauma is expected to improve the efficacy of future rehabilitation efforts and clinical practice guidelines by providing the clinical team the knowledge necessary to recognize modifiable barriers to patient success. A better understanding of factors influencing RTD decision-making may support policies for mitigating RTD barriers, better monitoring of the changing landscape of RTD after lower extremity trauma, improving systems of health care, and/or reducing turnover and facilitating force readiness.

Method of forming a rational set of test trajectory options to increase the reliability of performance evaluation during testing of radar information tools

To get an objective picture of the state of near-earth space, it is necessary to update the fleet of information tools in a timely manner, which is characterized by the introduction of new tools and the modernization of old tools, while changing the system in stages as the funds are ready. The continuous build-up of the system's assets as they are ready allows us to improve its performance without waiting for all newly introduced and upgraded assets to be ready. To test monitoring systems in conditions of a large number of heterogeneous elements combined in a system to achieve a single goal, an experimental and theoretical method of evaluating effectiveness based on mathematical modeling is used. The essence of this method is to simulate information at the input of programs of the system tools using mathematical models implemented directly on the system tools themselves. In this case, the quality of test trajectories that would allow evaluating the characteristics of radar information tools and the capabilities of monitoring systems is of particular importance. The purpose of the study is to increase the reliability of the results of tests of radar information tools for monitoring space debris by selecting a rational set of trajectory options that allow for the worst possible implementation of the capabilities of radar information tools, taking into account the functioning of each specific radar information tool participating in the tests. Based on the features of the factor space for finding solutions to the problem of forming test trajectories, the algorithm for forming the initial population and the algorithm for generating a new generation should be supplemented with blocks for checking the observability and feasibility of trajectories. The developed method of forming a rational set of variants of test trajectories using genetic algorithms differs from the known ones in that it generates a set of variants of test trajectories optimized from the point of view of obtaining the worst implementations of the capabilities of radar systems during its testing, under conditions of restrictions on the feasibility and observability of trajectories, the application of the methodology allows automating the process of preparing initial data for testing space debris monitoring systems in order to evaluate their characteristics. The application of the developed method allows to obtain the maximum errors in determining the parameters of the trajectory of space debris elements.

A framework for collaborative air traffic flow management minimizing costs for airspace users: Enabling trajectory options and flexible pre-tactical delay management

This paper proposes a collaborative air traffic flow management (ATFM) framework, in the scope of trajectory based operations, aiming to improve the cost-efficiency for airspace users (AUs) when facing ATFM regulations. The framework consists of four modules. The first one involves the AUs initially scheduling their preferred trajectories for all their flights. Based on this initial demand, the second module (assumed to be on the Network Manager -NM- side) detects time-varying hotspots (i.e. overloaded sectors along the day). In the third module, hotspot information is shared back to the AUs who plan alternative trajectory options to avoid crossing these congested airspace volumes (in the lateral and vertical domain); as well as providing to the NM different pre-tactical delay management preferences (including ground holding, linear holding, air holding and pre-tactical delay recovery); based on their internal cost breakdown structures. Incorporating all these potential combined options, the last module computes the best trajectory selections and the optimal distribution of delay assignments, such that the cost deviation from the initial status (all the user-preferred trajectories) is minimized. This model is formulated as mixed integer linear programming (MILP) and validated by a real-world case study focused on 24 h of traffic over the French airspace. Results using the proposed framework suggest a significant system delay reduction by nearly 97% over the existing method, whilst yielding an average of less than 100 kg extra fuel consumption and 50 Euro extra route charges for the 11% flights diverted to their alternative trajectories.

Relative trajectory cost estimation for CTOP applications using multivariate nonparametric finite mixture logit

We study airline decision-making in response to the Federal Aviation Administration’s Airspace Flow Program (AFP) to empirically describe policy-relevant behavioral strategies and preference structure of air carriers. Using observed responses made by airlines, we infer utility functions of different route options in AFP with respect to flight time and arrival delay using a finite mixture latent class choice model. We empirically describe the trade-off that airlines face between flight time and departure or arrival delay. The average estimated cost of airborne delay is 24 times greater than the cost of ground delay. Airborne cost per minute is over 100 greater than ground delay cost for large carriers and 4–20 times greater for small airlines. The results are applicable to future traffic flow management programs, such as Collaborative Trajectory Options Program (CTOP).

Contingency target assessment, trajectory design, and analysis for NASA’s NEA scout solar sail mission

The presented study examines contingency target selection and trajectory design for NASA’s Near-Earth Asteroid Scout mission under the assumption of a missed lunar gravity assist. Two previously considered asteroids are selected as potential targets for the given scenario based on favorable orbital characteristics for launch dates ranging from June 27, 2020 through July 26, 2020. Initially, a simplified circular restricted 3-body problem + ideal solar sail model is utilized to survey trajectory options for a month-long launch window. Selected solutions from this data set are then converged in an N-body ephemeris + non-ideal sail model. Results suggest that NEA Scout can still perform asteroid rendezvous mission under the missed lunar gravity assist scenario with new targets, 2019 GF1, 2018 PK21, and 2007 UN12, based on the target launch dates. Further target assessment is carried out for 165 days beyond the current June 27, 2020 launch date.

Near-Optimal Methodology for In-Flight Synthesis of Trajectory Options Set

This paper presents an algorithm for in-flight synthesis of near-optimal trajectory options sets in the presence of time-varying airspace constraints during the en route phase of an aircraft flight to support NextGen trajectory-based operations. The en route structure of the National Airspace System is modeled as a graph with airports, waypoints, and navigational aids as the vertices, and en route airways representing the edges between them. To represent a more realistic situation, the network is subject to constraints due to factors such as convective weather and prevailing winds, which are assumed to vary with time. Furthermore, Federal Aviation Administration imposed flight restrictions and protocols such as temporary flight restrictions, and special use airspaces are also introduced as the network constraints. The costs for traversing each link are evaluated based on a user-defined, wind-dependent cost function. A novel near-optimal route generation methodology, based on A* algorithm, is developed to deal with the time-varying nature of the network constraints. The algorithm is fast enough to allow in-flight synthesis of trajectory options set. Further, it is sufficiently robust in adapting to varying severity of weather. These characteristics are demonstrated in the paper with trajectory generation examples.

Mitigating Air Delay: An analysis of the Collaborative Trajectory Options Program

Mitigating Air Delay: An analysis of the Collaborative Trajectory Options Program

Mitigating Air Delay: An analysis of the Collaborative Trajectory Options Program

Congestion is a problem at major airports in the world. Airports, especially high-traffic ones, tend to be the bottleneck in the air traffic control system. The problem that arises for the airspace planner is how to mitigate air congestion and its consequent delay, which causes increased cost for airlines and discomfort for passengers. Most congestion problems are fixed on the day of operations in a tactically manner using operational enhancements measures. Collaborative Trajectory Options Program (CTOP) aims to improve air traffic management (ATM) considering National Airspace System (NAS) users business goals, particularities faced by each flight and airspace restrictions, making this process more flexible and financially stable for those involved. In CTOP, airlines share their route preferences with the air control authority, combining delay and reroute. When CTOP is created, each airline might decide its strategy without knowledge of other airline’s flights. Current solutions for this problem are based on greedy methods and game theory. There is potential space to improve. This paper examines CTOP and identifies important strategic changes to ATM adopting this philosophy, particularly in Brazil.