Airport Surface Research Articles

Moving Object Detection for Airport Scene Using Patterns of Motion and Appearance

This paper presents a novel method for localization and recognition of moving objects in a real airport surface scene. Different from the traditional applications, moving object detection (MOD) in the airport surface is more challenging because the background is an open outdoor environment, which means that the target objects are usually low in resolution and the MOD task is vulnerable to many undesired changes, such as cloud movement and illumination variations. To address these issues, this paper proposes a unified and effective deep-learning-based MOD architecture, which combines both appearance and motion cues. Specifically, a novel moving region proposal generation module is first designed, which can effectively locate the regions of moving object based on the motion information. Meanwhile, a novel cascade multilayer feature fusion module with transposed convolution is applied to produce both enriched-semantics and fine-resolution convolutional feature maps for category recognition. Finally, a large-scale dataset acquired by the daily surveillance videos of a real airport surface is manually constructed. Results show that the proposed methods outperform state-of-the-art solutions in extracting moving objects from airport surface scenes.

Applicability of Fuzzy Logic and Artificial Neural Network for Unpaved Airfield Surface Bearing Strength Prediction.

The main objective of this paper is to describe a building process of a model predicting the soil strength at unpaved airport surfaces (unpaved runways, safety areas in runway proximity, runway strips, and runway end safety areas). The reason for building this model is to partially substitute frequent and meticulous inspections of an airport movement area comprising the bearing strength evaluation and provide an efficient tool to organize surface maintenance. Since the process of building such a model is complex for a physical model, it is anticipated that it might be addressed by a statistical model instead. Therefore, fuzzy logic (FL) and artificial neural network (ANN) capabilities are investigated and compared with linear regression function (LRF). Large data sets comprising the bearing strength and meteorological characteristics are applied to train the likely model variations to be subsequently compared with the application of standard statistical quantitative parameters. All the models prove that the inclusion of antecedent soil strength as an additional model input has an immense impact on the increase in model accuracy. Although the M7 model out of the ANN group displays the best performance, the M3 model is considered for practical implications being less complicated and having fewer inputs. In general, both the ANN and FL models outperform the LRF models well in all the categories. The FL models perform almost equally as well as the ANN but with slightly decreased accuracy.

Signal chain architectures for efficient airport surface movement radar video processing

Surface movement radar (SMR) is emerging as critical air traffic control to prevent runway incursion. In order to reach, or exceed, the demanding requirements for the International Civil Aviation Organization, this paper aims to develop an SMR signal chain architecture which extracts information about radar objects of interest in airport surveillance video. This research results can be integrated into radar analyzer and compressor data processor to enable the system to quickly detect objects of moving or stationary. It can work normally in the case of pulses are lost in burst transmission or the resources. The state-of-the-art performance of this signal chain architecture is verified by simulations with X-band radar trials data are collected at Kunming Changshui International Airport of China, which ensure the reliability of research. The work presented here is practical and straightforward; it brings an evident engineering application prospect.

Traffic congestion mechanism in mega-airport surface

In this paper, guided by macroscopic cell transmission models, a cell transmission model of aircraft traffic flow on runways, taxiways and aprons was established to deduce and analyze the evolution rules of an airport surface traffic. The model was simulated by adopting data from a large domestic airport in China. The relationship between three parameters of traffic flow on taxiways was evaluated, and the airport surface traffic flow characteristics were analyzed. Moreover, this paper macroscopically analyzed the characteristics of spatial–temporal distribution of airport surface recurrent and non-recurrent traffic congestion. Simulation results showed that arrival rates and pushback rates had significant influence on the formation and dissipation of recurrent traffic congestion in different phases of the surface aircraft traffic flow. When the arrival rate was 0.3 aircraft/minute and the pushback rate was 0.23 aircraft/minute, the speed of aircraft on taxiways was high, the density and flow were large, and the aircraft had a high degree of obstacle-free taxiing. At this time, the airport ran smoothly and the surface network operation efficiency was high. Compared with the arrival rate, the outward expansion trend of each parameter was more obvious when the pushback rate changed. Parallel taxiways are less robust than apron taxiways and connect taxiways.

Situational Awareness of Large Infrastructures Using Remote Sensing: The Rome–Fiumicino Airport during the COVID-19 Lockdown

Situational awareness refers to the process of aggregating spatio-temporal variables and measurements from different sources, aiming to improve the semantic outcome. Remote Sensing satellites for Earth Observation acquire key variables that, when properly aggregated, can provide precious insights about the observed area. This article introduces a novel automatic system to monitor the activity levels and the operability of large infrastructures from satellite data. We integrate multiple data sources acquired by different spaceborne sensors, such as Sentinel-1 Synthetic Aperture Radar (SAR) time series, Sentinel-2 multispectral data, and Pleiades Very-High-Resolution (VHR) optical data. The proposed methodology exploits the synergy between these sensors for extracting, at the same time, quantitative and qualitative results. We focus on generating semantic results, providing situational awareness, and decision-ready insights. We developed this methodology for the COVID-19 Custom Script Contest, a remote hackathon funded by the European Space Agency (ESA) and the European Commission (EC), whose aim was to promote remote sensing techniques to monitor environmental factors consecutive to the spread of the Coronavirus disease. This work focuses on the Rome–Fiumicino International Airport case study, an environment significantly affected by the COVID-19 crisis. The resulting product is a unique description of the airport’s area utilization before and after the air traffic restrictions imposed between March and May 2020, during Italy’s first lockdown. Experimental results confirm that the proposed algorithm provides remarkable insights for supporting an effective decision-making process. We provide results about the airport’s operability by retrieving temporal changes at high spatial and temporal resolutions, together with the airplane count and localization for the same period in 2019 and 2020. On the one hand, we detected an evident change of the activity levels on those airport areas typically designated for passenger transportation, e.g., the one close to the gates. On the other hand, we observed an intensification of the activity levels over areas usually assigned to landside operations, e.g., the one close to the hangar. Analogously, the airplane count and localization have shown a redistribution of the airplanes over the whole airport. New parking slots have been identified as well as the areas that have been dismissed. Eventually, by combining the results from different sensors, we could affirm that different airport surface areas have changed their functionality and give a non-expert interpretation about areas’ usage.

Robust Control of Arrivals Into a Queuing Network

Queuing networks have been widely-used to model congestion in transportation systems. Due to their interconnected nature, delays in a queuing network can propagate as customers traverse through the network; similarly, downstream resources can be underutilized due to poor control policies. This paper considers the regulation of arrivals into a queuing network in order to maintain a desired level of occupancy (queue length) in the system. The dynamics of the queuing network is represented by a fluid-flow model, which is then used to develop a robust controller for tracking the desired queue length. The controller is based on a sliding mode control approach, with predictor-based feedback to account for propagation delays. For a single queue, we determine sufficient conditions for tracking the queue length, and bounds on the tracking error. We also present an analysis of the tracking performance for queues in tandem. We demonstrate our approach for the example of airport surface congestion control. The proposed robust control framework is based on a queuing network model of the airport, and is used to tactically manage aircraft departures in order to reduce congestion on the airport tarmac.

Prospects of using penetrated cement concrete in the construction of transport infrastructure objects

This article presents the analysis of the international experience of the use of pervious concrete in transport infrastructure. It provides the advantages and disadvantages of the material and the results of personal laboratory tests of relevant concrete samples. The object of the research is the use of pervious concrete in the construction of transport infrastructure. The objective of the paper is to justify the use of pervious concrete in the construction of transport infrastructure by analyzing previous international experience and lab tests of the corresponding concrete samples. Research methods included a analysis of the international and domestic literature, the evaluation of the experience in the use of the pervious concrete, and laboratory tests of the corresponding concrete samples. A review of the world experience connected with research of pervious (draining) concrete, installation and operation of layers of aerodrome surface made of it, proved their technical and economic relevance and effectiveness of their application. Pervious concrete is a material with high open porosity, which provides good sound-absorbing properties and drainage ability together with roughness, smoothness, and transverse friction. These are advantages of pervious concrete pavements, according to foreign studies: a rapid removal of water from the surface of the pavements in case of rain and improved drainage of road and airfield pavements reduce the risk of aquaplaning vehicles and increase traffic safety in rainy weather; increased and stable surface roughness; reduced level of noise provided by vehicles. The draining ability of the pavements makes it almost dry. It also has a high degree of sound absorption. The results of the article can be implemented in various technologies of construction and repair of transport infrastructure. The search for the optimal composition of pervious concrete for its further use in the technology of construction and repair of various objects is the main purpose of predictive assumptions about the development of the object of study.

Coverage Enhance in Boundary Deployed Camera Sensor Networks for Airport Surface Surveillance

Unlike the conventional coverage issue in camera sensor networks, the airport surface surveillance brings new challenges for achieving the desirable coverage. One of the biggest challenges comes from the deployment of camera sensors, i.e. due to the consideration of safety, the cameras are always installed on the land-side facilities in airports. In this paper, we propose a coverage enhancing method by deploying additional cameras for the boundary deployed heterogeneous camera networks. We convert the area coverage problem to maximize the barrier coverage in the area of interest by a boundary deployed camera network. The proposed method is divided into three phases: detecting the uncovered gaps in barriers; finding the optimal positions for deploying additional cameras; and optimizing the orientation of the additional cameras to cover the uncovered gaps. The simulation results confirm that our algorithm has better performance in coverage improvement and additional camera usage compared with other related methods.

PREVISÃO DE NEVOEIRO PARA O AEROPORTO DE MACEIÓ USANDO O MODELO BRAMS


 
 
 
 Nos aeroportos, eventos de nevoeiro podem causar prejuízos socioeconômicos durante o pouso ou decolagem. Para o Aeroporto Internacional Zumbi dos Palmares foi criada uma ferramenta para a previsão de visibilidade baixa pelo laboratório de Meteorologia Sinótica e Física da Universidade Federal de Alagoas, o Fog VISibility Version 1 (FogVISv1.0). O presente estudo visa, portanto, através dos dados de previsão do modelo de mesoescala Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) simular a visibilidade horizontal através do conteúdo de água líquida (LWC) e a concentração do número de gotas (N​d)​ para seis episódios de nevoeiro ocorridos no Aeroporto Internacional Zumbi dos Palmares entre 2008 a 2014, com duração igual ou superior a 1 hora, com o objetivo de analizar a capacidade da ferramenta FogVISv1.0 tendo como condições iniciais dados do modelo BRAMS, na detecção da visibilidade baixa associada a eventos de nevoeiro. Resultados prévios, obtidos no presente trabalho, ilustram que a ferramenta conseguiu detectar visibilidade baixa em 87% dos eventos de nevoeiro registrados pela estação de superfície do aeroporto, o que totaliza cinco dos seis casos avaliados.
 
 
 

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.

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.

Analysis of airport weather impact on on-time performance of arrival flights for the Brazilian domestic air transportation system

Air traffic operations are significantly impacted by weather conditions. These external factors may impose operational constraints and generate demand-capacity imbalances, leading to reduced on-time performance, additional airline costs and inconveniences to passengers. Efficient management of such disruptions requires an understanding of the main causes of flight delays towards increasing their predictability. In this study, we investigate the impacts of airport surface weather conditions on the likelihood of flight delays for the Brazilian domestic air transportation system. We use historical flight schedule, on-time performance and weather data and estimate a logit model to analyze how different meteorological variables at the airport of destination affect the probability of a delayed arrival. We obtain empirical evidence for the impacts of low ceiling and visibility conditions, precipitation and wind gusts on the likelihood of arrival delays for the set of Brazilian airports analyzed.

Validation Measurement of Hybrid Propagation Analysis Suitable for Airport Surface in VHF Band and Its Application to Realistic Situations

Validation Measurement of Hybrid Propagation Analysis Suitable for Airport Surface in VHF Band and Its Application to Realistic Situations

Empirical Method for Estimating Aircraft Fuel Consumption in Ground Operations

This study proposes a novel procedure for estimating aircraft fuel burn during ground operations using aircraft trajectory data acquired from an airport surface surveillance system. A fundamental assumption employed throughout the study is that aircraft fuel burn on the ground depends on taxi phases and corresponding thrust settings. The computational process is split into three steps: (1) define a taxi phase for each data point by analyzing the trajectory data; (2) find the fuel flow index appropriate for each taxi phase of each engine type from the International Civil Aviation Organization (ICAO) Engine Emissions Databank which contains fuel flow indices for four flight status of every commercial engine; and (3) estimate the total fuel burn on the ground for each flight by multiplying the time duration at each taxi phase by the corresponding fuel flow rate. Using 24-hour surface trajectory data collected from the Airport Surface Detection Equipment (ASDE) system at Seoul/Incheon International Airport, all flights operated on the day were analyzed applying this procedure. The results indicate that suggested taxi fuel burn rates are estimated to be about 17% lower than the ICAO values. The proposed procedure is expected to be used as an alternative method for ground fuel burn estimation.

A digital model of airport surface traffic

The article proposes a digital model for determining permissible trajectories of objects moving within the air-port landside area. This model can be used for assessing the reliability of information provided by automatic dependent surveillance systems, as well as for filtering false targets. False targets can arise due to reflection of radio signals emitted by surveillance systems from large objects, as well as due to active interference or spoofing attacks. The developed model is of particular importance for assessing the reliability of information provided by automatic dependent surveillance-broadcast systems at aerodromes with an average level of traffic complexity, since it allows simpler solutions in terms of surveillance compared to multilateration systems or secondary surveillance radar systems operating in Mode S.

Simulation of Runway Operations with Application of Dynamic Wake Separations to Study Runway Limitations

This paper presents an evaluation of runway operations at Chicago O’Hare International Airport to estimate the impact of proposed wake vortex separation including Recategorization Phase II and III dynamic separations. The evaluation uses a Monte Carlo simulation model that considers arrival and departure operations. The simulation accounts for static and dynamic wake vortex separations, aircraft fleet mix, runway occupancy times, aircraft approach speeds, aircraft wake circulation capacity, environmental conditions, and operational error buffers. Airport data considered for this analysis are based on Airport Surface Detection Equipment Model X records from Chicago O’Hare International Airport from January to November 2016. Dynamic wake separations are tailored to each unique set of conditions by using environmental and aircraft performance parameters as input and allowing aircraft to be exposed to the same wake vortex strength as in Recategorization Phase II (RECAT II). The analysis shows that further reductions beyond RECAT II for aircraft pairs separated by 2 nautical miles or less is not operationally feasible. These wake separations already result in little to no wake dependency. When this is the case, the challenges in wake separation are to meet runway occupancy times and to make sure aircraft separations allow for human operational variations without resulting in aircraft turnarounds or double-aircraft-occupancy runway violations.

CFD simulation of exhaust gases jet from aircraft engine

The growth of world aviation traffic leads to an increase of the impact on the environment that is now becoming one of the main factors determining the development of the aviation industry.Computational fluid dynamics (CFD) has become an attractive tool to predict pollutant concentration in the real environment. CFD software represents the most advanced mathematics that can be applied to simulation different physical process, including the transfer and dilution of fluid flow from aircraft, vehicle and other sources. This paper is an attempt to compare numerical simulation results of exhaust gases jet from aircraft near aerodrome surface by three CFD codes: Fluent 6.3, OpenFOAM and SolidWorks. The work is also focused on assessment of the aerodrome surface influence on jet’s parameters (height and longitudinal coordinate of buoyancy effect) and on providing of initial data for further dispersion modeling. The obtained results are also aimed to improve complex model PolEmiCa.

Reactive Temporal Logic-Based Precursor Detection Algorithm for Terminal Airspace Operations

The air traffic management system is one of the most complex manmade systems, with stringent standards for safety and operational performance. Modern surveillance systems make available detailed flight and airport information through onboard and ground recording systems. These recorded datasets can be used for detecting and/or predicting anomalies that hinder safe and efficient operations. The prediction of an anomaly is performed by identifying events that precede the occurrence of an anomaly, which are called precursors. In this paper, we propose a precursor detection algorithm that can identify precursors for flight anomalies through data-driven models designed with surveillance data recorded in the terminal airspace. The proposed algorithm is demonstrated to detect precursors of flight anomalies in the terminal airspace around LaGuardia Airport in New York City using real traffic data obtained from the Airport Surface Detection Equipment–Model X and the terminal automation information service surveillance datasets.

The Influence of the Aircraft Operating Fluids on the Mechanical Parameters of the Airport Surface Concrete.

The authors of the article assessed the impact of operating fluids used to service aircraft on changing mechanical parameters of cement concrete intended for airport pavement. The research concerned concrete designed with the use of CEM I 42.5N LH NA low-alkali cement, broken granite aggregate, fine washed aggregate, and admixtures. The analysis included the assessment of changes in differences in endurance parameters over various research periods of up to 140 days. The obtained results allowed to carry out statistical analysis using the student’s T-test. Research has shown a significant impact of operational fluids used in aircraft on the surface concrete properties of the airport. A reduction in the compressive strength of concrete exposed to one of the tested operating liquid to a reduction of 7.2% was observed over a period of 140 days, while there was no significant impact of operating fluids on tensile strength at splitting.

Impact of Off-Block Time Uncertainty on the Control of Airport Surface Operations

Congestion at major airports worldwide results in increased taxi times, fuel burn, and emissions. Regulating the pushback of aircraft from their gates, also known as departure metering, is a promising approach to mitigating surface congestion. Departure metering algorithms require models of airport surface traffic and knowledge of when a flight would be to be ready for pushback, which is called the earliest off-block time (EOBT). While EOBTs are known to be inaccurate due to several reasons, there has been little prior research on characterizing EOBT uncertainty and its impact on departure metering. We present a new class of queuing network models for the airport surface that are capable of capturing congestion at multiple locations. We demonstrate our modeling approach using operational data from three major U.S. airports: Newark Liberty International Airport, Dallas/Fort Worth International Airport, and Charlotte Douglas International Airport. We analyze the current levels of uncertainty in the EOBT information published by the airlines and conduct a parametric analysis of the reduction in departure metering benefits due to errors in the EOBT information. Our analysis indicates that the current levels of EOBT uncertainty lead to a 50% reduction in benefits at some airports when compared with an ideal case with no EOBT uncertainty. Two approaches to departure metering are considered: the National Aeronautics and Space Administration’s Airspace Technology Demonstration-2 logic and a new optimal control approach. We show that our queuing network models can help design and evaluate both approaches and that the optimal control approach is more effective in accommodating EOBT uncertainty while maintaining runway utilization.