Taxi Time Research Articles

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.

Unimpeded Taxi-Time Prediction Based on the Node–Link Model

This paper presents a new method for predicting unimpeded taxi time based on the airport node–link model through statistical analysis of the airport surface detection equipment surveillance data. The proposed method can predict taxi-out and taxi-in times for departure and arrival flights, respectively, by calculating the link travel times on a node–link model of the airport surface movement. The prediction performance of the proposed method was evaluated using recorded track data from Incheon International Airport during April 2015. Furthermore, the prediction performance was compared with three other methods well known for calculating unimpeded taxi times. The root-mean-squared error of the unimpeded taxi times predicted by the proposed method showed a prediction error of about 1 min for the departure and arrival flights. Moreover, the results showed significant improvement in the predictions of the unimpeded taxi time compared to the other methods.

항공기 지상 활주 연료소모량 예측모델 사례연구 (A380 중심)

In this paper, we established a prediction model of fuel consumption at the aircraft's taxi operation. To look for countermeasures to reduce fuel consumption and carbon emissions, Airbus A380's actual ground taxi data was used. As a result, the number of stops or turnings during the taxi operation was not related to fuel consumption. It was confirmed that the amount of fuel consumption in the taxi operation was the taxi time and the thrust change. It can be confirmed that ground control optimization, which is the result of close cooperation between the control organization and the airline, is absolutely necessary to reduce taxi time and minimize the occurrence of thrust change events.

Agent-Based Distributed Planning and Coordination for Resilient Airport Surface Movement Operations

Airport surface movement operations are complex processes with many types of adverse events which require resilient, safe, and efficient responses. One regularly occurring adverse event is that of runway reconfiguration. Agent-based distributed planning and coordination has shown promising results in controlling operations in complex systems, especially during disturbances. In contrast to the centralised approaches, distributed planning is performed by several agents, which coordinate plans with each other. This research evaluates the contribution of agent-based distributed planning and coordination to the resilience of airport surface movement operations when runway reconfigurations occur. An autonomous Multi-Agent System (MAS) model was created based on the layout and airport surface movement operations of Schiphol Airport in the Netherlands. Within the MAS model, three distributed planning and coordination mechanisms were incorporated, based on the Conflict-Based Search (CBS) Multi-Agent Path Finding (MAPF) algorithm and adaptive highways. MAS simulations were run based on eight days of real-world operational data from Schiphol Airport and the results of the autonomous MAS simulations were compared to the performance of the real-world human operated system. The MAS results show that the distributed planning and coordination mechanisms were effective in contributing to the resilient behaviour of the airport surface movement operations, closely following the real-world behaviour, and sometimes even surpassing it. In particular, the mechanisms were found to contribute to more resilient behaviour than the real-world when considering the taxi time after runway reconfiguration events. Finally, the highway included distributed planning and coordination mechanisms contributed to the most resilient behaviour of the airport surface movement operations.

Aircraft Emission Inventory and Characteristics of the Airport Cluster in the Guangdong–Hong Kong–Macao Greater Bay Area, China

In this study, a compound method using modified Boeing Fuel Flow Method 2 (BFFM2) and an updated First Order Approximation V3.0 (FOA3.0) method deploying the ICAO Time-in-Mode (TIM) was used to produce a more reliable aircraft emission inventory for the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The results show that compared with the International Standard Atmosphere (ISA) conditions, the total emission of nitrogen oxides(NOx) decreased by 17.7%, while carbon monoxide(CO) and hydrocarbons(HC) emissions increased by 11.2%. We confirmed that taxiing is the phase in which an aircraft emits the most pollutants. These pollutant emissions will decrease by 0.3% to 3.9% if the taxiing time is reduced by 1 minute. Furthermore, the impact of reducing taxi-out time on emissions is more significant than that of reducing the taxi-in time. Taking the total aircraft emission factors as the main performance indicators, Hong Kong International Airport (VHHH) contributes the most to the total emissions of the GBA, while the Zhuhai airport(ZGSD) contributes the least. The contribution of an individual airport to the total emissions of the GBA is mainly determined by the proportion of Boeing B77L, B77W, and B744.

Adaptation of the LTO test to the local airports infrastructure

The paper focuses on emission of harmful exhaust gas compounds from aircraft engines and draws on its impact on human health and life. Air transport, as the most dynamically developing branch of transport, has a very strong impact on the human environment. The paper discusses the methodology for assessing emission of harmful exhaust compounds from airports and mainly focuses on universal and widely used Landing and Take-off (LTO) test. The theoretical part of this paper also outlines global research activities which rely on modeling airport emissions. The research part includes the infrastructural analysis of the aerodrome movement area in Warsaw Chopin Airport, located in Polish capital city. The infrastructure analysis presented in the paper attends to estimate the actual taxiing time in chosen airport. The method used in the research relies on scenario modes which attribute to airplanes specific routes directly from the aircraft stand to the runway and after landing from the runway to the aircraft stand. Adopted scenarios describe the specific route of the aircraft, including used taxiways, curves and calculate its lengths. The infrastructural analysis leads to LTO testing in two options. The first LTO test is based on actual taxiing time, whereas the second one uses only standard certified taxiing time. The research highlights significant differences in the total emission which actually result from aircraft taxiing time.

Taxi Event Extraction from Surveillance for Surface Performance Evaluation

Estimated unimpeded taxi times can be used to quantify a flight’s taxiing delay when compared with its actual taxi time. Currently, flight unimpeded taxi times are calculated by the Federal Aviation Administration using a regression method where flights in the Aviation System Performance Metrics data are clustered on the season of operation, airline, airport, and calendar year. The method uses the airline-reported gate-Out, wheels-Off, wheels-On, gate-In (OOOI) times rounded to the nearest minute. For nonreporting airlines, these times are estimated from similar flights. The purpose of this paper is to evaluate the unimpeded time using a surveillance-based approach by identifying the time a flight spent waiting in the system and comparing with the total taxi time. This study focuses on analyzing both arrivals and departures for six U.S. airports (Atlanta, Charlotte, Denver, Houston, New York Kennedy, and Chicago O'Hare) during the month of July 2015. The study results show how the non-surveillance-based and surveillance-based metrics compare, with nonsurveillance methods including the current regression method and the 5th-to-15th clustering method described in current literature. The benefits of using surveillance information for surface performance are explored, as spatial analyses allow for quick identification of taxiway locations that were the most susceptible to delays.

Multi-Objective Optimization of Aircraft Taxiing on the Airport Surface with Consideration to Taxiing Conflicts and the Airport Environment

High-efficiency taxiing for safe operations is needed by all types of aircraft in busy airports to reduce congestion and lessen fuel consumption and carbon emissions. This task is a challenge in the operation and control of the airport’s surface. Previous studies on the optimization of aircraft taxiing on airport surfaces have rarely integrated waiting constraints on the taxiway into the multi-objective optimization of taxiing time and fuel emissions. Such studies also rarely combine changes to the airport’s environment (such as airport elevation, field pressure, temperature, etc.) with the multi-objective optimization of aircraft surface taxiing. In this study, a multi-objective optimization method for aircraft taxiing on an airport surface based on the airport’s environment and traffic conflicts is proposed. This study aims to achieve a Pareto optimized taxiing scheme in terms of taxiing time, fuel consumption, and pollutant emissions. This research has the following contents: (1) Previous calculations of aircraft taxiing pathways on the airport’s surface have been based on unimpeded aircraft taxiing. Waiting on the taxiway is excluded from the multi-objective optimization of taxiing time and fuel emissions. In this study, the waiting points were selected, and the speed curve was optimized. A multi-objective optimization scheme under aircraft taxiing obstacles was thus established. (2) On this basis, the fuel flow of different aircraft engines was modified with consideration to the aforementioned environmental airport differences, and a multi-objective optimization scheme for aircraft taxiing under different operating environments was also established. (3) A multi-objective optimization of the taxiing time and fuel consumption of different aircraft types was realized by acquiring their parameters and fuel consumption indexes. A case study based on the Shanghai Pudong International Airport was also performed in the present study. The taxiway from the 35R runway to the 551# stand in the Shanghai Pudong International Airport was optimized by the non-dominant sorting genetic algorithm II (NSGA-II). The taxiing time, fuel consumption, and pollutant emissions at this airport were compared with those of the Kunming Changshui International Airport and Lhasa Gonggar International Airport, which have different airport environments. Our research conclusions will provide the operations and control departments of airports a reference to determine optimal taxiing schemes.

Research on Joint Optimization of Airport Surface Based on Improved A* Algorithm

Joint optimization of runway and taxiway will help increase the usage rate of airport’s existing hardware and software resources and ease flight delays. Firstly, the paper considers the relevant regulations of taxiing and the constraints of runway release interval, and takes the shortest total taxi time of each flight as the objective function to construct a joint optimization model based on the basic element layout of the airport. Secondly, the A* algorithm is improved for its characteristics and the actual situation of the airport surface, and the optimization model is solved by this improved method. Finally, taking Nanjing Lukou International Airport as an example, the optimal solution obtained by improved A* algorithm is compared with the actual running data to verify the applicability of the model.

INFLUENCE OF SURFACE CONDITION OF TAXIWAYS AND RUNWAYS ON TIME OF AIRCRAFT DEPARTURE

The state of the runway (RWY) under operating conditions, due to the possibility of formation of a layer of water, ice, slush, snow, decreases the friction coefficient of the aircraft landing gear to RWY, and may cause the aviation events. In addition, the condition of taxiways and airport runway affects the taxiing time of aircraft, which during high-traffic hours can lead to additional flight delays. To study the effect of friction coefficient on the runway occupancy time the methodology of collecting statistical data about the time of different types of aircraft spent on runway at various values of the friction coefficient is offered. The method is based on a full-scale experiment. To conduct the experiment as the object of analysis the process of moving the aircraft from the holding position up to reaching the height of 200 meters at Vnukovo airport was chosen. Since the observer cannot control the parameters affecting the object of study during the flight, the friction coefficient is recorded as an input parameter during the experiment and as the response – the time of moving aircraft from holding position up to reaching the height 200 meters after take-off on standard departure procedure. As a result of the experiment, according to the obtained data, a graph of Ttot versus friction coefficient was designed. The greatest influence of the friction coefficient is observed when taxiing from the holding position on runway to line-up position.

Uncertainty-Aware Flight Scheduling for Airport Throughput and Flight Delay Optimization

The continuous growth in the demand for air transportation exceeds the capacity of existing infrastructure, usually leading to unreliable flight schedules, i.e., long flight delays and uncertainties in arrival/departure and taxi times. We tackle the problem in this paper by designing an air traffic control algorithm, which can accommodate both airport throughput and flight quality of service in terms of flight delay on a given runway. The flight scheduling problem is formulated as an integer linear programming, and then converted to a multiobjective optimization problem which enables the computation of tradeoff between scheduling resolution and time complexity. Based on the multiobjective optimization, a heuristic algorithm considering uncertainties in flight arrival/departure time and taxi time is designed to achieve an improvement in airport throughput and a reduction in flight delay. Extensive simulations show that compared to benchmarking schemes, the proposed uncertainty-aware flight scheduling algorithm can improve the airport throughput and flight delay by up to 12.02% and 31.4%, respectively.

Understanding Collective Human Mobility Spatiotemporal Patterns on Weekdays from Taxi Origin-Destination Point Data.

With the availability of large geospatial datasets, the study of collective human mobility spatiotemporal patterns provides a new way to explore urban spatial environments from the perspective of residents. In this paper, we constructed a classification model for mobility patterns that is suitable for taxi OD (Origin-Destination) point data, and it is comprised of three parts. First, a new aggregate unit, which uses a road intersection as the constraint condition, is designed for the analysis of the taxi OD point data. Second, the time series similarity measurement is improved by adding a normalization procedure and time windows to address the particular characteristics of the taxi time series data. Finally, the DBSCAN algorithm is used to classify the time series into different mobility patterns based on a proximity index that is calculated using the improved similarity measurement. In addition, we used the random forest algorithm to establish a correlation model between the mobility patterns and the regional functional characteristics. Based on the taxi OD point data from Nanjing, we delimited seven mobility patterns and illustrated that the regional functions have obvious driving effects on these mobility patterns. These findings are applicable to urban planning, traffic management and planning, and land use analyses in the future.

An Empirical Study on Low Emission Taxiing Path Optimization of Aircrafts on Airport Surfaces from the Perspective of Reducing Carbon Emissions

Aircraft emissions are the main cause of airport air pollution. One of the keys to achieving airport energy conservation and emission reduction is to optimize aircraft taxiing paths. The traditional optimization method based on the shortest taxi time is to model the aircraft under the assumption of uniform speed taxiing. Although it is easy to solve, it does not take into account the change of the velocity profile when the aircraft turns. In view of this, this paper comprehensively considered the aircraft’s taxiing distance, the number of large steering times and collision avoidance in the taxi, and established a path optimization model for aircraft taxiing at airport surface with the shortest total taxi time as the target. The genetic algorithm was used to solve the model. The experimental results show that the total fuel consumption and emissions of the aircraft are reduced by 35% and 46%, respectively, before optimization, and the taxi time is greatly reduced, which effectively avoids the taxiing conflict and reduces the pollutant emissions during the taxiing phase. Compared with traditional optimization methods that do not consider turning factors, energy saving and emission reduction effects are more significant. The proposed method is faster than other complex algorithms considering multiple factors, and has higher practical application value. It is expected to be applied in the more accurate airport surface real-time running trajectory optimization in the future. Future research will increase the actual interference factors of the airport, comprehensively analyze the actual situation of the airport’s inbound and outbound flights, dynamically adjust the taxiing path of the aircraft and maintain the real-time performance of the system, and further optimize the algorithm to improve the performance of the algorithm.

Access and egress times to high-speed rail stations: a spatiotemporal accessibility analysis

Accessibility by high-speed rail (HSR) depends not only on station-to-station travel time, but also on access and egress times, which can be determining factors in total journey travel time. However, studies focusing on accessibility analyses of access/egress times to/from stations are less extended in the literature and centre mainly on the influence of access times to stations on HSR accessibility levels on a regional scale. This paper's aim is to evaluate the importance of access and egress times to/from HSR stations in an urban context. We carry out a spatiotemporal accessibility analysis that considers the temporal variations of both taxi and public transport travel times. General Transit Feed Specification (GTFS) files for public transport and TomTom Speed Profiles data for cars are used to measure access/egress times. These kinds of data allow for the calculation of travel times from/to HSR stations through network analysis GIS tools at different times of the day, and thus a spatiotemporal accessibility measure can be obtained. This accessibility measure is complemented by a mass factors representing the activity ‘hotspots’ in the visited city throughout the workday, which is derived from Twitter data, while population is considered for city of residence. This method was applied to the two largest metropolitan areas in Spain: Madrid and Barcelona, where the influence of access/egress times acquires a higher relevance for rail-based trips. The results obtained show that access and egress times vary significantly during the day, depending on the levels of traffic congestion and the frequency of public transport services, which are always more favourable for taxis. In addition, weighted average access and egress times at the home end are higher than those at the activity end since population tends to show more dispersed spatial patterns than activities. Another interesting finding is that the first and last mile of the HSR trip usually account for a high percentage increase in travel time (about 35% for taxis and 55% for public transport, respectively). These results have important policy implications. The paper suggests that HSR accessibility can be improved also by improving local transport services, scheduling coordination and land use policies.

Improved approach for time‐based taxi trajectory planning towards conflict‐free, efficient and fluent airport ground movement

The ever-growing air traffic demand arouses an urgent need for improved airport ground movement efficiency. New operational concepts are emerging which use time-based taxi trajectories to reduce uncertainty and make more efficient use of the airport resource. In this study, an improved approach is proposed for time-based taxi trajectory planning, which is formulated as the shortest path problem with time windows and the maximum traversal time constraint. With the introduction of the taxi time in the cost and the maximum traversal time constraint to limit the waiting time, more efficient and fluent ground movement of aircraft can be realised. An A*-based solution algorithm is developed for the investigated problem, which utilises the arrival time interval and dominance-based comparison to search for the best solution. Experimental results on real-world problem instances demonstrate the effectiveness of the proposed approach as well as its advantages over the existing approach.

A Study on the Strategy for Departure Aircraft Pushback Control from the Perspective of Reducing Carbon Emissions

In order to reduce the taxiing time of departing aircraft and reduce the fuel consumption and exhaust emissions of the aircraft, Shanghai Hongqiao Airport was taken as an example to study the control strategy for aircraft departure. In this paper, the influence of the number of departure aircraft on the runway utilization rate, the takeoff rate, and the departure rate of flight departures under the conditions of airport runway capacity constraints are studied. The influence of factors, such as the number of departure aircraft, the gate position of the aircraft, and the configuration of airport arrival and departure runways, on the aircraft taxiing time for departure is analyzed. Based on a multivariate linear regression equation, a time prediction model of aircraft departure taxiing time is established. The fuel consumption and pollutant emissions of aircraft are calculated. The experimental results show that, without reducing the utilization rate of the runway and the departure rate of flights, implementing a reasonable pushback number for control of departing aircraft during busy hours can reduce the departure taxiing time of aircraft by nearly 32%, effectively reducing the fuel consumption and pollutant emissions during taxiing on the airport surface.

Examining the Compellingness of electronic Low Visibility Taxi Charts

The purpose of this study was to examine whether the presentation of own-aircraft (ownship) position was compelling when presented on electronic low visibility taxi charts. Although airport charts showing ownship position have been in use for some time, ownship position was not available on low visibility taxi charts because these charts were not geo-referenced. Twenty Airline Transport Pilots (ATP) (10 flightcrews) participated in a simulator study in which they performed six taxi scenarios in three different levels of visibility (1200 Runway Visual Range (RVR), 600 RVR, 300 RVR) using an electronic chart application on an iPad. Ownship position was shown on the chart for half the scenarios. In one scenario, we simulated a position error. We collected objective data (taxi speed, taxi time, fixation and dwell time), and pilot opinions on the usability of the electronic chart application. The results showed that no incursions/excursions were committed. All flightcrews noticed the error in ownship position, when it occurred; in fact, they also noticed other errors in ownship position that were not planned as part of the experiment design. Captains looked more often at the electronic chart when ownship position was presented than when it was not, regardless of visibility conditions. Additionally, Captains’ percentage of fixations were almost equal between the electronic chart and out-the-window. Such behavior may reflect the perceived utility of showing ownship on the electronic chart and may be an indication of the compelling nature of that information source.

A two-stage taxi scheduling strategy at airports with multiple independent runways

Long taxiing times at large airports lead to fuel wastage and dissatisfied passengers. This paper investigates the 4D taxi scheduling problem in airports to minimize the taxiing time. We propose an iterative two-stage scheduling strategy. In the first stage, all aircrafts in a current schedule period are assigned initial 4D routes. In the second stage, landing aircrafts that are unavailable to fulfil their initially assigned routes are rescheduled using a shortest path algorithm based approach. In this paper, the simplified model used in most existing literature, that depicts a runway as having a single entrance and a single exit or even sets only one point to represent both of them has been discarded. Instead, we model the fact that a runway has multiple entrance and exit points and use an emerging concept—Runway Exit Availability (REA)—to measure the probability of clearing a runway from a specific exit during a specific time interval so that the taxiing scheduling model can be much higher approximation to the practical operation. An integer programming (IP) model factoring REA is proposed for assigning 4D taxiing routes in the first stage. The IP model covers most practical constraints faced in airport taxiing procedures, such as the rear-end/head-on conflict constraint, runway-crossing constraint, take-off/landing separation constraint, and taxi-out constraint. Besides, flight holding patterns at intersections are much more realistically modelled. Furthermore, to accelerate the solving process of the IP model, we have refined the formulation using several tricks. Simulation results by proposed scheduling approach for operations at the Beijing Capital International Airport (PEK) for an entire day demonstrate a surprising taxiing time saving against the empirical data and simulation results based on a strategy similar to what being used now days while showing an acceptable running time of our approach, which supports that our approach may help in real operation in the future.

Comprehensive Evaluation of Airspace and Ground Operation Simulation in Large-Scale Airport

The evaluation model of airport airspace and ground operation was constructed by using analytic hierarchy process (AHP). 5 airspace operation indexes were selected: potential impact to military aviation, airspace demand range, number of arriving and departure routes, flow equilibrium of entry and exit point, arrival air delays time. 7 evaluation indexes of ground operation were selected: number of daily departure and arrival flights, equilibrium of runway usage, departure ground delays time, ground taxiing time, usage equilibrium of main taxiway, turnover frequency of contact gate, air bridge ratio. The index scale method was used to determine the weight of each index, which had better ordering, consistency and uniformity. Taking Beijing New Airport as an example, the airspace and ground operational efficiency was evaluated comprehensively. The results show that the “3+1” runway configuration is better than “4+0”.

Airport Taxi Situation Awareness with a Macroscopic Distribution Network Analysis

This paper proposes a framework for airport taxi situation awareness to enhance the assessment of aircraft ground movements in complex airport surfaces. Through a macroscopic distribution network (MDN) of arrival and departure taxi processes in a spatial-temporal domain, we establish two sets of taxi situation indices (TSIs) from the perspectives of single aircraft and the whole network. These TSIs are characterized into five categories: aircraft taxi time indices (ATTIs), surface instantaneous flow indices (SIFIs), surface cumulative flow indices (SCFIs), aircraft queue length indices (AQLIs), and slot resource demand indices (SRDIs). The coverage of the TSIs system is discussed in detail based on the departure and arrival reference aircraft. A real-world case study of Shanghai Pudong airport demonstrates significant correlations among some of the proposed TSIs such as the ATTIs, SCFIs and AQLIs. We identify the most crucial influencing factors of the taxi process and propose two new metrics to assess the taxi situation at the aircraft and network levels, by establishing taxi situation assessment models instead of using two systems of multiple TSIs. The findings can provide significant references to decision makers regarding airport ground movements for the purposes of air traffic scheduling and congestion control in complex airports.