Aircraft Taxiing Research Articles

位置情報を用いた航空機の地上走行自動化に向けた基礎研究

In this study, as basic research toward the automation of aircraft taxiing, we developed an automatic running system using position information. Specifically, the travel position correction program developed in the previous year was improved to a program that uses two P-controls to change the amount of movement of the servomotor based on the amount of deviation from the straight route and the difference in the direction the aircraft is facing. As a result, it was confirmed that the improved traveling position correction program worked properly, but the amount of motion needed to be further examined. Future work includes adjustment of the proportional gain, improvement of the traveling position correction program for traveling in a curved line, installation of the automatic traveling system on the model aircraft and traveling experiments using the model aircraft.

Are anemometers at airports affected by taxiing aircraft?

This study provides evidence to discount any need to correct wind speeds measured at airports for jet exhaust from aircraft taxiing past the anemometer. The figure shows the manufacturer's data for an Airbus 320 engine at ‘ground idle’ extrapolated into the far field as a Gaussian wall jet model, showing that the jet exhaust is expected to pass underneath anemometers at 10m above ground. This is confirmed by matching 503 large-jet departures from runway 1L at Tampa International, FL, to the 1min interval gust speed and direction data recorded by the anemometer.

Predicting aircraft taxiing estimated time of arrival by cluster analysis

In order to predict the aircraft taxiing estimated time of arrival (ETA) to reduce scene conflicts and improve the operating efficiency of airports, the Kalman filter algorithm is employed to preprocess historical trajectory data for an airport scene. For the first time, in order to measure the distance between trajectory samples, the aircraft taxiing period and the number of aircraft in a scene are used as sample features for aircraft taxiing ETA prediction. The dynamic time warping algorithm is employed to extract the different features of the trajectory. The Euclidean distance between two sample features is taken as their similarity. The initial clustering centre is determined based on the divided difference maximum principle by using the K-means algorithm to cluster samples and selecting the cluster with the highest matching degree according to the time period of the aircraft under planning and the number of aircraft operating in the scene. The trajectory sequence for the sample at the cluster centre and the static path planned by the tower are combined to predict the aircraft taxiing ETA. The accuracy of this method at predicting the aircraft taxiing ETA was demonstrated in simulations by comparing and analysing actual trajectory data with predicted taxiing ETA.

A homogenization-planning-tracking method to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems

Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking (HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance, multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase. The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.

Experimental Investigation on Dynamic Tensile Behaviors of Engineered Cementitious Composites Reinforced with Steel Grid and Fibers

Engineered cementitious composites (ECC) used as runway pavement material may suffer different strain rate loads such as aircraft taxiing, earthquakes, crash impacts, or blasts. In this paper, the dynamic tensile behaviors of the steel grid-polyvinyl alcohol (PVA) fiber and KEVLAR fiber-reinforced ECC were investigated by dynamic tensile tests at medium strain rates. The mixture was designed with different volume fractions of fibers and layer numbers of steel grids to explore the reinforcement effectiveness on the dynamic performance of the ECC. The volume fractions of these two types of fibers were 0%, 0.5%, 1%, 1.5%, and 2% of the ECC matrix, respectively. The layer numbers of the steel grid were 0, 1, and 2. The dynamic tensile behaviors of the PVA fiber and the KEVLAR fiber-reinforced ECC were also compared. The experimental results indicate that under dynamic tensile loads, the PVA-ECC reveals a ductile and multi-cracking failure behavior, and the KEVLAR-ECC displays a brittle failure behavior. The addition of the PVA fiber and the KEVLAR fiber can improve the tensile peak stress of the ECC matrix. For the specimens A0.5, A1, A1.5, and A2.0, the peak stress increases by 84.3%, 149.4%, 209.6%, and 237.3%, respectively, compared to the matrix specimen. For the specimens K0.5, K1, K1.5, and K2, the peak stress increases by about 72.3%, 147.0%, 195.2%, and 263.9%, respectively, compared to the matrix specimen. The optimum fiber volume content is 1.5% for the PVA-ECC and the KEVLAR-ECC. The KEVLAR-ECC can supply a higher tensile strength than the PVA-ECC, but the PVA-ECC reveals more prominent deformation capacity and energy dissipation performance than the KEVLAR-ECC. Embedding steel grid can improve the tensile peak stress and the energy dissipation of the ECC matrix. For the strain rate of 10−3 s−1, the peak stress of the A0.5S1 and A0.5S2 specimens increases by about 49.1% and 105.7% compared to the A0.5 specimen, and the peak stress of the K0.5S1 and K0.5S2 specimens increases by about 61.5% and 95.8%, respectively, compared to the K0.5 specimen.

Research on Aircraft Surface Taxi Path Planning and Conflict Detection and Resolution

Aircraft surface taxiing conflict avoidance is mostly adopted by waiting and rerouting methods, but this method does not consider the difference in total taxiing time that may be caused by different strategies. In this study, the airport taxiing path optimization model and taxiing area division model are constructed first. Then, the taxiway use is controlled by subregion based on the analysis of the surface activity area connection relationship. Based on the results of aircraft surface taxiway preselection, the time window of the taxiing area is solved and conflict detection is performed. For aircraft with taxiing conflicts, waiting or changing paths is selected to deconflict taxiing by comparing priorities. An improved A∗ algorithm solution is applied to generate conflict-free glide paths and new glide trajectory occupancy time windows, while the glide paths of aircraft without glide conflicts are not affected. The results of the study show that the use of time windows for conflict detection and deconfliction can further reduce the total taxiing time of aircraft operating on the surface, resulting in a significant reduction in the number of aircraft conflicts, and thus, airport operational safety is ensured. This study has a high practical value and is expected to be applied in the real-time control decision of aircraft taxiing in the future.

Structural Dynamic Response of a Shield Tunnel under Aircraft Taxiing Load

Dynamic load is an important factor affecting the safety and stability of subway tunnel structures. To obtain the variation law of shield tunnel structure dynamic response under aircraft taxiing load, a three-dimensional numerical simulation of such tunnel under the action of aircraft taxiing load is performed on the basis of a project involving a shield tunnel orthogonal underpass taxiway. The effects of sliding speed and tunnel depth on the structure of the shield tunnel are also analyzed. The results show that the transverse displacement and acceleration response of tunnel segment exhibit evident time-space effect under the action of aircraft taxiing load. The transverse displacement and arch waist acceleration of the shield segment increase first and then decrease. The transverse displacement of the arch waist reaches its maximum when the aircraft taxis directly above the tunnel. The sliding speed exhibits an evident influence on the dynamic response of shield tunnel structure. The vertical and convergence displacements of tunnel segments increase with the increase in sliding speed. The dynamic response of tunnel structure is significantly affected by the factors of tunnel buried depth. The vertical and convergence displacements of tunnel segments decrease with the increase in tunnel buried depth. Therefore, the safety of the shield tunnel structure can be ensured by controlling the taxiing speed when the aircraft taxis directly above the tunnel. The measures of increasing the buried depth of the tunnel or strengthening the tunnel structure need to be considered when the taxiing speed is large.

Multi-Objective Route Planning for Aircraft Taxiing Under Different Traffic Conflict Types

Aircraft taxiing in large airports is often delayed by traffic conflicts. The increased fuel consumption and pollutant emission lower the efficiency of airport surface operation and bring potential safety hazards. Previous studies on route planning for surface taxiing seldom involve refined delay analysis under different traffic conflict types and discussions on route planning at airports with various environmental parameters and under diverse aircraft types. In this study, dynamic models of crossing, head-on, and trailing conflicts during aircraft taxiing were constructed, and delays of these three conflict types were determined. The shortest route set of restricted routing was determined by the Yen algorithm according to the topological network, conflict-induced delay, and spatial distributions of taxiing at airports. Considering the three optimization objects, the aircraft route planning was optimized and determined from the shortest route set according to the differences in the environmental parameters and aircraft types. Experiment results show that the proposed method achieves 9.6–12.1% higher route planning precision in all traffic periods compared with previous route planning with considerations to taxiing conflict. This method also provides support to the dynamic decision of airport operation and control departments according to the environment and performance of aircraft.

Dynamic response analysis of airport pavements during aircraft taxiing for evaluating pavement bearing capacity

Dynamic response analysis of airport pavements during aircraft taxiing for evaluating pavement bearing capacity

Adaptive Fuzzy Active-Disturbance Rejection Control-Based Reconfiguration Controller Design for Aircraft Anti-Skid Braking System

The aircraft anti-skid braking system (AABS) is an essential aero electromechanical system to ensure safe take-off, landing, and taxiing of aircraft. In addition to the strong nonlinearity, strong coupling, and time-varying parameters in aircraft dynamics, the faults of actuators, sensors, and other components can also seriously affect the safety and reliability of AABS. In this paper, a reconfiguration controller-based adaptive fuzzy active-disturbance rejection control (AFADRC) is proposed for AABS to meet increased performance demands in fault-perturbed conditions as well as those concerning reliability and safety requirements. The developed controller takes component faults, external disturbance, and measurement noise as the total perturbations, which are estimated by an adaptive extended state observer (AESO). The nonlinear state error feedback (NLSEF) combined with fuzzy logic can compensate for the adverse effects and ensure that the faulty AABS maintains acceptable performance. Numerical simulations are carried out in different runway environments. The results validate the robustness and reconfiguration control capability of the proposed method, which improves AABS safety as well as braking efficiency.

Optimising aircraft taxi speed: Design and evaluation of new means to present information on a head-up display

AbstractThe objective of this study was to design and evaluate new means of complying to time constraints by presenting aircraft target taxi speeds on a head-up display (HUD). Four different HUD presentations were iteratively developed from paper sketches into digital prototypes. Each HUD presentation reflected different levels of information presentation. A subsequent evaluation included 32 pilots, with varying flight experience, in usability tests. The participants subjectively assessed which information was most useful to comply with time constraints. The assessment was based on six themes including information, workload, situational awareness, stress, support and usability. The evaluation consisted of computer-simulated taxi-runs, self-assessments and statistical analysis. Information provided by a graphical vertical tape descriptive/predictive HUD presentation, including alpha-numerical information redundancy, was rated most useful. Differences between novice and expert pilots can be resolved by incorporating combinations of graphics and alpha-numeric presentations. The findings can be applied for further studies of combining navigational and time-keeping HUD support during taxi.

Electrification of airport taxiway operations: A simulation framework for analyzing congestion and cost

Aircraft taxiing with external electric towing could significantly reduce carbon dioxide (CO2) emissions from ground operations. We develop a discrete event simulation and cost model to investigate taxiway congestion and develop a comprehensive equivalent annual cost (EAC) estimate from using electric towing tractors (e-tractors). The model incorporates collision and conflict avoidance and towing service interruptions. Experiments identify the number of e-tractors generating the lowest EAC. A case study considers three electric taxi scenarios at Montréal-Trudeau International Airport. Our findings suggest significant potential for reducing fuel consumption and CO2 emissions with limited impact on taxi time when e-tractor capacity is aligned with demand. However, high uncertainty prevents definitive conclusions about cost effectiveness. The modeling approach can be updated based on ongoing field test data and input from airlines, airports, and handling agents and used to test novel taxi strategies, develop e-tractor implementation plans, and inform the capital budgeting process.

Resident air transport subsidy impact on airport ground operations: Gran Canaria airport case study

This paper seeks to analyze the impact of regional aviation subsidies for Gran Canary airport; specifically, the effect on airport capacity, air carrier economics and the environment. It was found that aircraft taxiing operations time increased producing negative effects on airport capacity management, air carrier economies and the environment in terms of decreasing airport capacity available and the increased fuel and emissions costs. However, those losses have to be balanced against the social benefit of increased resident mobility.

Overview of Emissions at Montreal’s Pierre Elliott Trudeau International Airport and Impact of Local Weather on Related Pollutant Concentrations

This study used AEDT 2.d to estimate the pollutant emissions at Montreal’s Pierre Elliott Trudeau International Airport (YUL) for 2015 while quantifying the impact of the airport’s taxi time and atmospheric conditions on aircraft emissions. Using the more airport-specific parameters available and ICAO standard values otherwise, the yearly emissions of NOx, HC, CO, PM10, SOx, and CO2 at YUL were, respectively, 7.64 102, 1.18 102, 1.33 103, 1.35 101, 6.77 101, and 2.31 105 tonnes/year. The results show that reducing aircraft taxi time by 31 % reduced aircraft emissions by 6 % (NOx) and 27 % (CO). Atmospheric conditions impact aircraft emissions of NOx, CO and HC with a seasonal effect. Summer conditions reduced NOx emissions by 5 % and increased CO emissions by 2 %, while winter conditions reduced HC and CO emissions by approximately 15 % and increased NOx emissions by 1 %. To further investigate the impact of atmospheric conditions, dispersion calculations of NOx and CO emissions were carried out using identical air-traffic and weather data from the warmest and coldest weeks in 2015. The results demonstrate that pollutant concentrations were higher during the winter and that pollutants were also dispersed further during the winter than the summer according to the dominant wind direction. A 1-h NOx and CO concentrations greater than 10 μg/m3 were found up to 24 km and 30 km, respectively, away during the winter compared to 14 km and 20 km during the summer. Yet, local air quality standards were satisfied as pollutant concentrations found outside the airport enclosure were below those standards.

Ground maneuver for front-wheel drive aircraft via deep reinforcement learning

The maneuvering time on the ground accounts for 10%–30% of their flight time, and it always exceeds 50% for short-haul aircraft when the ground traffic is congested. Aircraft also contribute significantly to emissions, fuel burn, and noise when taxiing on the ground at airports. There is an urgent need to reduce aircraft taxiing time on the ground. However, it is too expensive for airports and aircraft carriers to build and maintain more runways, and it is space-limited to tow the aircraft fast using tractors. Autonomous drive capability is currently the best solution for aircraft, which can save the maneuver time for aircraft. An idea is proposed that the wheels are driven by APU-powered (auxiliary power unit) motors, APU is working on its efficient point; consequently, the emissions, fuel burn, and noise will be reduced significantly. For Front-wheel drive aircraft, the front wheel must provide longitudinal force to tow the plane forward and lateral force to help the aircraft make a turn. Forward traction effects the aircraft’s maximum turning ability, which is difficult to be modeled to guide the controller design. Deep reinforcement learning provides a powerful tool to help us design controllers for black-box models; however, the models of related works are always simplified, fixed, or not easily modified, but that is what we care about most. Only with complex models can the trained controller be intelligent. High-fidelity models that can easily modified are necessary for aircraft ground maneuver controller design. This paper focuses on the maneuvering problem of front-wheel drive aircraft, a high-fidelity aircraft taxiing dynamic model is established, including the 6-DOF airframe, landing gears, and nonlinear tire force model. A deep reinforcement learning based controller was designed to improve the maneuver performance of front-wheel drive aircraft. It is proved that in some conditions, the DRL based controller outperformed conventional look-ahead controllers.

Trajectory control method for unmanned carrier aircraft taxiing

Trajectory control method for unmanned carrier aircraft taxiing

Research on aircraft taxiing path optimization based on digraph model and Dijkstra algorithm

in this paper, the ground structure diagram of an Airport is taken as an example, the specific flight information is substituted, and then the directed graph model is established, and various factors are transformed into weight offspring into the directed graph, and a multi factor constrained aircraft taxiing path optimization scheme is obtained. Through the specific analysis of the influence of each factor on the selection of aircraft taxiing path and the optimization scheme of taxiing path with the corresponding weight of various factors, the Dijkstra algorithm is used to calculate the specific case, and the specific optimal path of aircraft ground taxiing is obtained. The results show that the directed graph model and the optimal path of aircraft taxiing are reasonable, which can provide some reference for the controller’s command.

A Priority-Based Conflict Resolution Strategy for Airport Surface Traffic Considering Suboptimal Alternative Paths

Currently, the surface topology at large domestic airports with increasing traffic flow is becoming more complex. Taxiing conflicts grow as well. This paper proposed a strategy based on aircraft priority to solve the problem. Under the premise of ensuring aircraft priority, this strategy resolved the problem reasonably and improved the safety and efficiency of airport operation. With the purpose of minimizing time cost of all aircraft, an aircraft taxiing model was built. Simulation results showed the advantages of this strategy. Compared with a common conflict resolution strategy, taxiing routes of 9 aircraft changed. The total waiting time was reduced by 50% and the running time was reduced by 43.6s. In addition, to ensure taxiing efficiency of high-priority aircraft, low-priority aircraft tended to choose more tortuous routes when choosing suboptimal alternative routes.

Aircraft taxi time prediction: Feature importance and their implications

Taxiing remains a major bottleneck at many airports. Recently, several approaches to allocating efficient routes for taxiing aircraft have been proposed. The routing algorithms underpinning these approaches rely on accurate prediction of the time taken to traverse each segment of the taxiways. Many features impact on taxi time, including the route taken, aircraft category, operational mode of the airport, traffic congestion information, and local weather conditions. Working with real-world data for several international airports, we compare multiple prediction models and investigate the impact of these features, drawing conclusions on the most important features for accurately modelling taxi times. We show that high accuracy can be achieved with a small subset of the features consisting of those generally important across all airports (departure/arrival, distance, total turns, average speed and numbers of recent aircraft), and a small number of features specific to particular target airports. Moving from all features to this small subset results in less than a 1 percentage-point drop in movements correctly predicted within 1, 3 and 5 min.

4D Trajectory Planning of Aircraft Taxiing considering Time and Fuel

Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed, and the model is optimized based on the shortest taxi time. Although it is easy to solve, it does not consider the change of the speed profile when the aircraft turns, and the optimal taxiing time of the aircraft does not necessarily bring the optimal taxiing fuel consumption. In this paper, the aircraft’s taxi distance and the number of turns in the taxi are considered. The aircraft path planning model with the shortest total distance of the airport surface is established. The improved A ∗ algorithm is used to obtain the shortest path P. Based on this, the shortest path P is established. Considering the multitarget velocity profile model of time and fuel consumption, a heuristic search is used to generate an accurate velocity profile for each path to obtain a 4D trajectory of the aircraft and then quantitative analysis of the impact of aircraft pollutant emissions on the airport environment based on 4D trajectory taxi time. The experimental results show that, compared with the traditional optimization method without considering the turning times, the total taxiing distance and turning times of the aircraft are greatly reduced. By balancing the taxiing time and fuel consumption, a set of Pareto-optimal velocity profiles is generated for the aircraft taxiing path; at the same time, it will help the airport save energy and reduce emissions and improve the quality of the airport environment. It has a high practical application value and is expected to be applied in the real-time air traffic control decision of aircraft surface in the future.