Flight behavior recognizing in terminal area based on support vector machine

Despite the recent economic recession and its adverse impact on air travel, the Federal Aviation Administration (FAA) continues to forecast an increase in air traffic demand that may see traffic double or triple by the year 2025. Increases in air traffic will burden the air traffic management system, and higher levels of safety and efficiency will be required. The air traffic controllers primary task is to ensure separation between aircraft in their airspace and keep the skies safe. As air traffic is forecasted to increase in volume and complexity [1], there is an increased likelihood of conflicts between aircraft, which adds risk and inefficiency to air traffic management and increases controller workload. To attenuate these factors, recent ATM research has shown that air and ground-based automation tools could reduce controller workload, especially if the automation is focused on conflict detection and resolution. Conflict Alert is a short time horizon conflict detection tool deployed in the Terminal Radar Approach Control (TRACON), which has limited utility due to the high number of false alerts generated and its use of dead reckoning to predict loss of separation between aircraft. Terminal Tactical Separation Assurance Flight Environment (T-TSAFE) is a short time horizon conflict detection tool that uses both flight intent and dead reckoning to detect conflicts. Results of a fast time simulation experiment indicated that TTSAFE provided a more effective alert lead-time and generated less false alerts than Conflict Alert [2]. TSAFE was previously tested in a Human-In-The-Loop (HITL) simulation study that focused on the en route phase of flight [3]. The current study tested the T-TSAFE tool in an HITL simulation study, focusing on the terminal environment with current day operations. The study identified procedures, roles, responsibilities, information requirements and usability, with the help of TRACON controllers who participated in the experiment. Metrics such as lead alert time, alert response time, workload, situation awareness and other measures were statistically analyzed. These metrics were examined from an overall perspective and comparisons between conditions (altitude resolutions via keyboard entry vs. ADS-B entry) and controller positions (two final approach sectors and two feeder sectors) were also examined. Results of these analyses and controller feedback provided evidence of T-TSAFE s potential promise as a useful air traffic controller tool. Heuristic analysis also provided information on ways in which the T-TSAFE tool can be improved. Details of analyses results will be presented in the full paper.

Dynamic airspace configuration (DAC) algorithms strive to restructure the U.S. National Airspace System (NAS) in ways that allow air traffic control to better manage aircraft flows. Although past research has largely focused on enroute airspace in clear weather conditions, the principle of better matching airspace structure to ambient conditions has potential to benefit airport terminal areas, which are often impacted by congestion due to convective weather, especially during summer months when travel demand is high. This paper studies the problem of dynamic airspace configuration in the terminal area given a stochastic model of route availability during convective weather conditions. An integer programming model is proposed for the dynamic reconfiguration of the terminal area. This model recommends small changes to airspace structure that alleviate airspace congestion, while limiting disruptions to air traffic control procedures. The model is tested against actual weather scenarios, and shows promising benefits to operations.

Data-driven prediction of Air Traffic Controllers reactions to resolving conflicts.

Air transportation is an important factor for the economic growth of the European Union, however, the current system is already approaching its capacity limits and needs to be reformed to meet the demands of further sustainable development (Commission of the European Communities, 2001). These limitations stem mainly from the current European air traffic control system. Air traffic control within Europe is fragmented due to political frontiers into regions with different legal, operational, and regulative contexts. This fragmentation decreases the overall capacity of the European air traffic control system and, as the system is currently approaching its capacity limits, causes significant congestion of the airspace. According to the European Commission airspace congestion and the delays caused by it cost airlines between €1.3 and €1.9 billion a year (European Commission, 2011). For this reason, the European Commission agreed to adopt a set of measures on air traffic management to ensure the further growth and sustainable development of European air transportation. The key enabler of this transformation is the establishment of a Single European Sky1 (SES). The objective of the SES is to put an end to the fragmentation of the European airspace and to create an efficient and safe airspace without frontiers. This will be accomplished by merging national airspace regions into a single European Flight Information Region (FIR) within which air traffic services will be provided according to the same rules and procedures. In addition to the fragmentation of the airspace the second limiting factor for the growth of European air transportation lies within the legacy Air Traffic Control (ATC) concept. In the current ATC system, which has been developed during the first half of the twentieth century, aircraft fly on fixed airways and change course only over navigation waypoints (e.g. radio beacons). This causes non-optimal paths as aircraft cannot fly directly to their destination and results in a considerable waste of fuel and time2. In addition, it concentrates aircraft onto airways requiring ATC controllers to ascertain their safe separation. The tactical control of aircraft by ATC controllers generates a high demand of voice communication which is proportional to the amount of air traffic. As voice communication

Objective: The objectives of current study are to explore whether serious fatigue of Air Traffic Controller (ATC) exist in their duty, and to explore a sensitive fatigue index. Method: Number recognition task was used to explore ATC fatigue. Following results were found, firstly, significant fatigue effect was found in all 55 ATC. Besides, significant fatigue effects were only found in ATC in tower control area and terminal control area, but not in regional control area. Thirdly, only reaction time before and after ATC duty were found significant difference but not in accuracy. Conclusion: Fatigue effect really exist in ATC after their duty, and ATC in different work location suffer different work load. Finally, reaction time of number recognition task can be a very sensitive and reliable fatigue index.

Current study is aiming to find a more suitable behavioral fatigue index for Air Traffic Controllers(ATC) using PVT test and fatigue self-assessment questionnaires as tools, and gives these tests before and after ATC duty. Through PVT test and self-assessment questionnaire, this finding indicates hit rate and hit response time (the first 20% trials) of PVT can be potential fatigue index since we found first 2min hit response time of air traffic controller(ATC) after duty is significantly longer than before duty, together with the hit rate after duty is lower than before duty. 8 items in Stanford Sleepiness Scale(SSS) and Visual Analogy Scale(VAS) also show significant difference in self assessment on fatigue. ATCs think themselves are much more fatigue after duty than before duty.Besides, ATCs in regional control area show significant fatigue effect than those in terminal control area, indicating different work load in two different working areas. Those ATC work at night especially in midnight show much more significant fatigue than those work in the daytime showed by longer first 20% hit response time. In sum, hit rate and first 20% (first 2min) hit response time can be effective fatigue indexes of ATC.

Decision support system in tactical air traffic flow management for air traffic flow controllers

An exploration of the utility of mathematical modeling predicting fatigue from sleep/wake history and circadian phase applied in accident analysis and prevention: The crash of Comair Flight 5191

The complex tasks of air traffic control (ATC) and the various factors affecting its operation have shed light on the need to build a model to predict conflict detection and resolution (CDR) performance within a traffic situation. This study aimed at developing a fuzzy-hybrid framework for quantifying various aspects in ATC consisting of the software, hardware, environment, liveware and organisation (i.e. the SHELL model) to predict CDR performance. The proposed fuzzy-hybrid SHELL framework in this study was tested using metadata from 10 prior studies in ATC. The results showed a highly accurate prediction, as indicated by the RMSE and MAPE values of 0⋅09 and 5⋅36%, respectively, indicating a high consistency of 90⋅92% for predicting the CDR performance. This framework offers a promising approach for Air Navigation Service Providers (ANSPs) to maintain air traffic safety and improve ATC operations efficiency.

With growing air traffic density, air-traffic controllers (ATCOs) are facing more challenges in interpreting and analyzing air traffic information. As one of the solutions to this problem, automation supports such as tactile human computer interface, interactive 3D radar displays, and conflict resolution aid (CRA) are proposed for the enhancement of the current air traffic control (ATC) systems. To evaluate the proposed ATC systems, questionnaires are commonly used to get the feedback from ATCOs. However, the questionnaires are usually administered upon completion of each ATC simulation task thus provide only overall ratings towards the new ATC systems. In this paper, we propose and implement a novel Electroencephalogram (EEG)-based neurocognitive tools for evaluation of ATC systems. The nature of EEG-based technique is that the brain states can be monitored in a high resolution time, fitting the nature of time-critical ATC tasks. Thus, such EEG-based human factors study allows for real-time monitoring of ATCOs' mental workload during the task performance in ATC systems. We designed and conducted an experiment to evaluate the costs and benefits of the CRA and tactile user interface in future ATC systems. Thirty six participants participated in the experiment and were assigned into three groups of different display modes: Non-Display, Display, and Trajectory Prediction. In each group, three CRA conditions were given: Manual, Reliable and Unreliable. The EEG data were recorded during the tasks, and the traditional workload evaluation method NASA Task Load Index (TLX) was administered at the end of each task. The result shows that the ratings obtained from NASA TLX and from the EEG labeling are highly correlated. Thus, the EEG-based system is reliable to recognize workload during the task performance. With the proposed EEG-based system, we found that 1) relatively high workload was observed at the beginning of the experiment in each group which could be due to participants' unfamiliarity with the interfaces; 2) participants in the trajectory prediction group had much higher workload as compared to vertical display and non-display groups, which could be attributed to its complexity. The changes of workload are due to interaction between the type of display modes and time (p<0.05); 3) workload varied slightly with different CRA setting. The results show that the proposed EEG-based system for human factors study can provide better understanding of real-time mental workload changes during the task performance in new ATC systems, therefore enables the evaluation of current and future ATC systems.

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

The delegation to the flight crew of some tasks currently performed by air traffic controllers provides new perspectives to potentially increase air traffic control efficiency. More specifically, the task of establishing properly spaced landing sequences is very demanding in heavy traffic conditions for the air traffic controllers in charge of the terminal maneuvering area. Automatic merging and station keeping operations could relieve air traffic controller of providing time consuming radar vectoring instructions. The objective of this communication is to provide technical insight into the airborne devices and algorithms which may be used onboard aircraft to automatically achieve a specified distance or delay with respect to another aircraft at a specified meter fix. A nonlinear control law based on sliding mode control is proposed to control the lateral motion of the trailing aircraft. The design is followed by two illustrative examples which show the effectiveness of the proposed approach.

In this paper we attempt to answer the question of whether the display of cumulonimbus clouds on air traffic controller radar screens has a significant impact on air traffic control. The developed cumulonimbus cloud mapping simulator allowed the study to be performed by performing simulations with a flight control simulator. This allowed an assessment of how the air traffic controller makes decisions when cumulonimbus is displayed and when it is not. The benefits of cumulonimbus imaging for aircraft trajectories and flight time were also assessed. The research was conducted in the space of Vilnius terminal manoeuvring area.

Air traffic management (ATM) concepts of the future are committed towards significantly enhancing the capacity and making flying even safer. Since, these new ATM concepts will change the roles and responsibilities of pilots and the air traffic controllers, it is important that their impact on safety be evaluated. Many proposed schemes includes shifting the separation assurance function (maintaining safe distances between aircraft) to the cockpit from ground based air traffic control, and to assign a supervisory role to the air traffic controller, who would make decisions in exceptional cases. Some initial research in this direction has shown that controllers cannot intervene effectively without decision support tools like “conflict probes”. Furthermore controllers and pilots have different strategies for resolving conflicts about separation and airspace. Accordingly, there is a need to better understand and classify the decision-making behavior of different agents in the future proposed ATM system. This paper presents a theoretical discussion outlining the application of the Lens Model of Brunswik to provide insight into some of the research questions posed in conflict detection and resolution by future ATM concepts. We illustrate the approach through an example case study.

The continuously increasing air traffic density has become a major challenge in air traffic control (ATC) due to the current ATC systems are approaching maximum capacity. To deal with the problem, an automated conflict resolution aid (CRA) and a trajectory prediction aid (TPA) have been proposed to serve as additional safety layers in the ATC systems. However, whether the proposed automation aids are worth to be applied in the current ATC workplace and could better support air traffic controllers (ATCOs) remain unknown. This study aims to investigate the effects of the proposed automations on ATCOs' workload and situation awareness (SA). To do so, twenty-four participants were evenly divided into two groups corresponding to the presence and absence of the TPA. In each condition, participants were instructed to perform simulated ATC tasks with the double of current air traffic load under the presence and absence of the CRA. The results showed that the CRA benefits ATCOs' workload and SA. The application of the CRA alone could benefit ATCOs while the presence of the TPA alone did not offer valuable benefits for ATCOs. Importantly, the CRA could lower the workload substantially when it was integrated with the TPA. The automation design aspect and its application in enhancing safety of future ATC are also highlighted.