Tokyo International Airport Research Articles

Impact of border control measures on public health center operations and staffing at international airports during the emergence of the SARS-CoV-2 B.1.1.529 (Omicron) variant of concern

Objective Ota City, located in southeastern Tokyo, including Haneda Tokyo International Airport, has numerous scattered lodging facilities. Shortly after the first case of SARS-CoV-2 B.1.1.529 (Omicron) variant was reported abroad, the Japanese government strengthened border control measures, including quarantine procedures and public health official involvement, for incoming travelers. This study aims to propose effective and efficient border control measures to prevent future outbreaks of emerging and re-emerging infectious diseases.Methods Border control measures implemented between November 2021 and mid-January 2022 were analyzed from three perspectives: chronological changes in government notifications, the situation of in-flight contacts and Omicron cases, and the support system for coronavirus-disease 2019 control department of the Ota City Public Health Center. Additionally, a questionnaire survey was conducted among public health centers with jurisdiction over the top four international airports. This survey aimed to assess the effectiveness of the support system, evaluate cooperation with related organizations, identify common issues faced by public health concerns, and gather suggestions for improvements in future border control measures.Results The definition and treatment of in-flight contacts of Omicron-positive individuals were initially outlined on November 30, 2021, and underwent frequent revisions until January 14, 2022. Between December 1, 2021, and January 12, 2022, only one Omicron case was identified among the 470 tests conducted on in-flight contacts. However, out of 136 additional domestic specimens collected (including 57 positives for genetic analysis), 40 were confirmed Omicron positive. The results of the questionnaire survey across the four public health centers largely mirrored the issues and suggestions identified by Ota City officials. A significant portion of these issues arose from managing temporary non-Japanese residents staying near international airports.Conclusion Border control measures should be implemented to delay the domestic spread of the virus. In this reason, it is crucial to avoid placing an undue burden on public health officials responsible for handling domestic infections. Since response policies and target definitions may need to adapt to unknown pathogens, they may be changed frequently, baffling the officials; however, a system for collecting real-time data from frontline sites and making evidence-based decisions is essential. Additionally, deploying liaisons from national and prefectural governments to focal points of emergency response would strengthen the support system by promoting unified instructions and information sharing.

Air traffic inefficiencies and predictability evaluation using route mapping—the Tokyo International Airport case

Air traffic inefficiencies lead to excess fuel burn, emissions and air traffic controller (ATCo) workload. Various stakeholders have developed metrics to assess the operation performance. Most metrics compare the actual trajectories to some benchmark ones to calculate excess time or distance. This research is inspired by cellular automata (CA) and develops a combined time-distance lateral inefficiency and predictability metric using discrete space and time mapping on published flight routes. The analysis is focused on Tokyo International Airport, but uses only track data and published routes, which makes it easily applicable to any other hub airport worldwide. The mapping and velocity analyses are used to investigate when and where ATCos are most likely to intervene to provide save separation. A metric which can be adjusted to evaluate both traffic flow predictability and efficiency is proposed. This metric can be applied to better understand current traffic and enable future improvements towards seamless air traffic flow management.

Economic impact analysis of developing the JR Haneda Airport Access Line

The East Japan Railway Company is planning a new access railway line to the Tokyo International (Haneda) Airport. This paper proposes an evaluation method for the development of the new airport access line considering the socioeconomic characteristics of the Greater Tokyo Area and indicates what is needed to increase its social value. As the evaluation method, we develop an econometric model that considers commuters’ trip behaviors across prefectures and the relationship between the increased number of Meeting, Incentive Travel, Convention, Exhibition and Event (MICE) visitors and the regional economy. We also conduct a simulation analysis using an empirical econometric model and a cost-effectiveness analysis based on multiple scenarios. The results indicate that a 50% increase in MICE visitors is needed to make the present discounted value of the total increase in the gross regional product larger than the construction cost of the line.

Effectiveness of Aircraft Inter-Arrival Control in Upstream Traffic Flow via a Combined Tandem Fluid Queue Model and Integer Programming Approach

Conventionally, several studies indicated that controlling aircraft arrival time in the enroute airspace mitigates arrival aircraft congestion in the terminal airspace. Further research is required to clarify how to leverage this idea to design an air traffic management system, a so-called Extended Arrival MANager (E-AMAN), to reduce the arrival traffic flow while assisting air traffic controllers and boosting their effectiveness quantitatively. Under these circumstances, this research proposed aircraft inter-arrival time control within the en-route airspace and clarified its effectiveness in reducing arrival delay based on mathematical modeling and simulation evaluations. In this paper, we developed the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G_t/GI/s_t</i> + <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GI</i> tandem fluid model to analyze the time-varying delay time of flights in both en-route and terminal airspace and demonstrated the effect of inter-arrival time control in the upstream arrival traffic flow in the en-route airspace, combining the model with the nonlinear integer programming problem. The calculation results for 3,074 aircraft over 21 days, arriving at Tokyo International Airport between 17:00 and 22:00, show the possibility for the control to reduce the mean and maximum delay time for flights by 18.8% (5.0 s) and 16.5% (37.6 s) on average within the en-route airspace. Moreover, fast-time simulation by AirTOP is conducted to validate the control, revealing the scope to reduce mean and maximum delay times in the terminal airspace by 11.5% (36.5 s) and 19.2% (148.8 s) on average.

Controlling Aircraft Inter-Arrival Time to Reduce Arrival Traffic Delay via a Queue-Based Integer Programming Approach

Despite the importance of controlling the inter-arrival times of flights to propose strategies for efficient arrival management by the Arrival Manager (AMAN), the specific guidelines of such adjustments and their effect on reducing delays have not been explicitly considered. Accordingly, this paper proposes a novel approach, which integrates the Gt/GI/st+GI time-varying fluid model and nonlinear integer programming to flatten the arrival rate at terminal gates. This, in turn, is achieved by minimizing the variance in inter-arrival times by penalizing any excessive change in arrival time, considering operational constraints. The results for Tokyo International Airport show potential to significantly reduce arrival traffic delays by minimizing said variance. This study may also spawn subsequent work, which builds a queuing network comprising upstream and terminal airspace and demonstrates the scope to reduce delays in the terminal airspace by controlling inter-arrival times at the upstream airspace.

Improvement of Airport Surface Operation at Tokyo International Airport Using Optimization Approach

Congestion and delays occur on airport surfaces as a result of a rapid increase in the demand for air transport. The aim of this study is to determine the differences between optimized and observed operations to improve airport surface operation at Tokyo International Airport by using mixed-integer linear programming to minimize the total ground movement distance and time based on real-time flight information. Receding horizon schemes are considered to adapt to dynamic environments. The model obtains results that reduce the taxi distance by 18.54% and taxi time by 29.77% compared with the observed data. A comparison of taxiway usage patterns between the optimization results and observed data provides insight into the optimization process, for example, changes in runway cross strategies and taxiway direction rules. Factors such as the objective function weights and airline–terminal relationship were found to significantly affect the optimization result. This study suggests improvements that can be made at airports to achieve a more efficient surface operation.

Modeling Aircraft Departure at a Runway Using a Time-Varying Fluid Queue

Reducing the length of departure queues at runway entry points is one of the most important requirements for reducing aircraft traffic congestion and fuel consumption at airports. This study designs an aircraft departure model at a runway using a time-varying fluid queue. The proposed model enables us to determine the aircraft waiting time in the departure queue and to evaluate effective control approaches for assigning suitable holds at gates rather than runway entry points. As a case study, this study modeled the departure queue at runway 05 of Tokyo International Airport for an entire day of operations. Using actual traffic data of departures at the airport, the model estimates that aircraft spend a total of 2.5 h departure waiting time in a day at runway 05. Considering the stochastic nature of actual departure traffic, the relevance of the proposed model is discussed using validation criteria. The model estimation shows a reasonable, expected order of magnitude compared with the departure queue recorded in the actual traffic data. Furthermore, ecological and economic benefits are quantitatively evaluated assuming a reduction in the departure queue length. Our results show that about one kiloton of fuel oil per year is wasted due to aircraft waiting to depart from a single departure runway.

Analyzing Stochastic Features in Airport Surface Traffic Flow Using Cellular Automaton: Tokyo International Airport

Global air passenger transport demand is expected to increase, and there is concern that the current airport operation will not be able to cope with aircraft overcrowding. In this study, we developed a cellular automaton simulator that can model the surface traffic of the entire Tokyo International Airport in detail, including aircraft that are arriving, taxiing, parking, and departing, using actual track data. The simulator can reproduce stop-and-go aircraft taxiing based on aircraft interactions and runway rules. It can simulate the stochastic features of the surface traffic flow. To validate the developed CA simulation, the taxiing speed distribution, local delays, and taxiing times for each route were compared with the actual track data. They were in good agreement. The effects of stochastic surface traffic features, such as arrival rate, runway occupancy time, and taxiing route, on airport operations were quantitatively analyzed. This tool could lead to a better prediction of future air traffic and improve airport operations.

Data-Driven Simulation for Evaluating the Impact of Lower Arrival Aircraft Separation on Available Airspace and Runway Capacity at Tokyo International Airport

Although the application of new wake turbulence categories, the so-called “RECAT (wake turbulence category re-categorization)”, will realize lower aircraft separation minima and directly increase runway throughput, the impacts of increasing arrival traffic on the surrounding airspace and arrival traffic flow as a whole have not yet been discussed. This paper proposes a data-driven simulation approach and evaluates the effectiveness of the lower aircraft separation in the arrival traffic at the target airport. The maximum runway capacity was clarified using statistics on aircraft types, stochastic distributions of inter-aircraft time and runway occupancy time, and the levels of the automation systems that supported air traffic controllers’ separation work. Based on the estimated available runway capacity, simulation models were proposed by analyzing actual radar track and flight plan data during the 6 months between September 2019 and February 2020, under actual operational constraints and weather conditions. The simulation results showed that the application of RECAT would reduce vectoring time in the terminal area by 7% to 10% under the current airspace and runway capacity when following a first-come first-served arrival sequence. In addition, increasing airspace capacity by 10% in the terminal area could dramatically reduce en-route and takeoff delay times while keeping vectoring time the same as under the current operation in the terminal area. These findings clarified that applying RECAT would contribute to mitigating air traffic congestion close to the airport, and to reducing delay times in arrival traffic as a whole while increasing runway throughput. The simulation results demonstrated the relevance of the theoretical results given by queue-based approaches in the authors’ past studies.

Multi-Objective Takeoff Time Optimization Using Cellular Automaton-Based Simulator

Although schedule design has further potential to reduce airline operation costs and flight delay, the effectiveness of the globally optimal schedule design integrating air traffic flow has not been discussed thus far. This paper presents a global multi-objective takeoff time optimization to design efficient flight schedules that lead to minimal congestion and provide sufficient resilience against traffic problems. NSGA-II is adopted as the multi-objective optimization technique in this study. The objective functions include minimization of the total arrival delay and total fuel consumption because these are key performance indicators of air traffic management (ATM). The design variable used in this study is the takeoff time offset of each flight landing at the Tokyo International Airport. 607 design variables were used in this study. The range of the design variables was ±300 s to investigate the effect of a minor variation in the takeoff time. A cellular automaton-based model was utilized to simulate the interaction of the flights with each other. The results of the simulations demonstrated that the obtained optimal solutions could drastically reduce the total arrival delay and total fuel consumption by 1500 min and 80 tons, respectively. The spacing adjustments of one of the optimum flight schedules, in comparison to the original flight schedule, were reduced by 80% in the en-route and terminal airspaces. Additional analyses suggest that it is preferable to have longer takeoff time intervals for flights originating from the same point during congestion hours than those during non-congestion hours. This indicates that the optimization of ground movements in airports improves the efficiency of air traffic operations.

Analyzing tactical control strategies for aircraft arrivals at an airport using a queuing model

This paper proposes to analyze control strategies for arrival air traffic at an airport using a classical queuing model. The parameters of our model are estimated by means of a data-driven analysis of two years of radar tracks and flight plans for arrival flights at Tokyo International Airport from 2016 to 2017. Our results show that increasing the capacity with one or two more aircraft in the airspace up to 60 NM around the airport significantly mitigates arrival delays, even when assuming future, increased arrival traffic volumes. The outcomes of this study provide insights into the effectiveness of arrival control strategies and are seen as a means to recommend scenarios to be further analyzed with human-in-the-loop simulations.

Pilot-Centered Evaluation of Flight-Deck Interval Management Control Laws Using an A320 Simulator

Recent research on flight-deck interval management technology, including the findings of a flight-test demonstration conducted by NASA, led to the development of an alternative control logic for flight-deck interval management, termed as “interval management–speed planning.” As this logic demonstrated promising results in numerical simulations, for the first time, test pilots and airline pilots were invited to evaluate the system in an Airbus A320 simulator, using an avionics setup similar to the one employed in NASA’s flight test, on an approach for the Tokyo International Airport. A qualitative and quantitative survey was conducted in which the pilots’ opinions pertaining to their acceptance of the interval management operation and comprehension of the system behavior using both the original and alternative control logic, as well as a modified graphical user interface, were sought. The results indicated that the new control logic was well accepted by the pilots, confirming some of the results and hypotheses from the numerical simulation; nevertheless, it was indicated that further research on the user interface is needed to make full use of the logic’s capability.

On the Use of Lateral Wave for the Interlayer Debonding Detecting in an Asphalt Airport Pavement Using a Multistatic GPR System

In this article, we focus on the detection of the interlayer debonding of the asphalt airport pavement by the ground-penetrating radar (GPR) system. Since the interlayer debonding usually occurs in the shallow region of the asphalt airport pavement (several centimeters), it is difficult to interpret the anomalies or the defects from the GPR signals composed of many waves under the boundary conditions. Moreover, the wavelength of the ordinary GPR system is over several centimeters. Therefore, the spatial resolution of the system is not accurate enough to consider the millimeter thickness of the debonding layer. To overcome these problems, we propose a new method based on evaluating the lateral wave behavior of common midpoint (CMP) gathers collected by a multiple static GPR system. The multistatic GPR system is a stepped frequency continuous wave (SFCW) radar system, which consists of eight transmitting and eight receiving bowtie antennas. The system operates in the frequency range from 50 MHz to 1.5 GHz. After the validation of the simulation, the results of the interlayer debonding detection were evaluated by a field experiment obtained at Tokyo International Airport. The proposed method can detect the debonding layers which are less than 1 mm. Also, it is shown that our proposed method has a high consistency with the conventional acoustic finding method in the field measurement. It provides an innovative and effective method for the interlayer debonding detection of a partially damaged airport asphalt pavement, which is difficult to be observed by the ordinary GPR signals.

Evaluating the impact of new aircraft separation minima on available airspace capacity and arrival time delay

AbstractAlthough the application of new, reduced aircraft separation minima can directly increase runway throughput, the impact thereof on the traffic flow of aircraft arriving at the destination airport has not been discussed yet. This paper proposes a data-driven and queue-based modeling approach and presents an analysis of the impact on the delay time of arriving aircraft in the airspace within a radius of 100 nautical miles around an airport. The parameters of our queuing model were estimated by analysing the data contained in the radar tracks and flight plans for flights that arrived at Tokyo International Airport during the 2 years of 2016 and 2017. The results clarified the best arrival strategy according to the distance from the arrival airport: The combination of airspace capacity control and reduction of the flight time and separation variance is the most powerful solution to mitigate delays experienced by arriving traffic while also allowing an increase in the amount of arrival traffic. The application of new wake vortex categories would enable us to increase the arrival traffic to 120%. In addition, the arrival delay time could be minimised by implementing the proposed arrival traffic strategies together with automation support for air traffic controllers.

Analysis of Achievable Airborne Delay and Compliance Rate by Speed Control: A Case Study of International Arrivals at Tokyo International Airport

Analysis of Achievable Airborne Delay and Compliance Rate by Speed Control: A Case Study of International Arrivals at Tokyo International Airport

Quantitative risk assessment of African swine fever virus introduction to Japan via pork products brought in air passengers' luggage.

The spread of African swine fever (ASF) has reached pandemic levels over the last decade, and outbreaks of this disease in China, Mongolia, Vietnam and Cambodia in 2018 and 2019 could accelerate its transmission to neighbouring Asian territories. Thus, the risk that the ASF virus (ASFV) will be introduced to disease-free territories increases each year. Since Japan is an island nation, the most likely way in which ASFV would be introduced is via pork products brought in air passengers' luggage (PPAP). Therefore, in the present study, we assessed the risk of ASFV introduction to Japan via PPAP. For the purposes of this analysis, we considered 214 international commercial flights travelling from 47 origin territories to 31 destination airports as potential routes of ASFV introduction via PPAP. The risk was estimated quantitatively through a stochastic model that considered the volume of air passengers' luggage, the amount of confiscated pork products that were carried in air passengers' luggage and the disease status of the origin territory. The overall mean annual probability of ASFV introduction to Japan via PPAP was found to be 0.941 [95% confidence interval (CI), 0.661-1.000], which approximately corresponds to one introduction every 1.06years. At the origin territory level, Mongolia was led as the highest risk territory, with a risk of 0.864 (95% CI, 0.434-1.000), followed by China (0.697; 0.223-0.999), Vietnam (0.662; 0.196-0.998) and the Russian Federation (0.136; 0.018-0.401). At the destination airport level, Narita International Airport had the highest risk (0.905; 0.537-1.000), followed by Kansai International Airport (0.496; 0.109-0.961), Tokyo International Airport (0.389; 0.072-0.879) and Chubu Centrair International Airport (0.338; 0.058-0.816). This information will help improve risk management activities and monitoring systems to prevent the introduction of ASFV to Japan.

Reducing speed commands in interval management with speed planning

ABSTRACTFlight-deck Interval Management (FIM) is a modern airborne self-spacing technology that improves arrival route throughput and runway utilisation and increases hourly arrival capacity by up to four aircraft per hour and per runway, compared to conventional air traffic controller guided arrivals. The National Aeronautics and Space Administration (NASA) has been the leader in FIM research and formulated a logic that was put to an actual flight test in 2017. Despite the overall success of the project, operational deficiencies concerning the number of speed commands, which led to several recommendations for future research before operational implementation, were discovered. In this study, a new logic that implements a two-stage rule-based selection algorithm was developed to overcome those deficiencies. The proposed logic was compared to NASA’s logic on an arrival in Tokyo International Airport with multiple induced error patterns. The results indicate that the new logic significantly decreases the number of speed commands with only minor aggravations in spacing performance. The results that highlight the strengths and weaknesses of both concepts are discussed, and an outlook on and ideas for future research on FIM and the proposed logic are presented.

Queue-Based Modeling of the Aircraft Arrival Process at a Single Airport

This paper proposes data-driven queuing models and solutions to reduce arrival time delays originating from aircraft arrival processing bottlenecks at Tokyo International Airport. A data-driven analysis was conducted using two years of radar tracks and flight plans from 2016 and 2017. This analysis helps not only to understand the bottlenecks and operational strategies of air traffic controllers, but also to develop mathematical models to predict arrival delays resulting from increased, future aircraft traffic. The queue-based modeling approach suggests that one potential solution is to expand the realization of time-based operations, efficiently shifting from traffic flow control to time-based arrival management. Furthermore, the proposed approach estimates the most effective range of transition points, which is a key requirement for designing extended arrival management systems while offering automation support to air traffic controllers.

Current status and issues of the emergency medical system at Tokyo International Airport resulted in the increase of users and visitors

Current status and issues of the emergency medical system at Tokyo International Airport resulted in the increase of users and visitors

Quantitative Analysis of Operational Efficiency for Arrival Flights Bound for Tokyo International Airport

Quantitative Analysis of Operational Efficiency for Arrival Flights Bound for Tokyo International Airport